WO2021057244A1 - Light intensity adjustment method and apparatus, electronic device and storage medium - Google Patents

Light intensity adjustment method and apparatus, electronic device and storage medium Download PDF

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Publication number
WO2021057244A1
WO2021057244A1 PCT/CN2020/105260 CN2020105260W WO2021057244A1 WO 2021057244 A1 WO2021057244 A1 WO 2021057244A1 CN 2020105260 W CN2020105260 W CN 2020105260W WO 2021057244 A1 WO2021057244 A1 WO 2021057244A1
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Prior art keywords
distance
driving device
target object
target
luminous intensity
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PCT/CN2020/105260
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French (fr)
Chinese (zh)
Inventor
程光亮
石建萍
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北京市商汤科技开发有限公司
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Application filed by 北京市商汤科技开发有限公司 filed Critical 北京市商汤科技开发有限公司
Priority to KR1020227012602A priority Critical patent/KR20220062107A/en
Priority to JP2022518820A priority patent/JP2022550300A/en
Publication of WO2021057244A1 publication Critical patent/WO2021057244A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/06—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights adjustable, e.g. remotely-controlled from inside vehicle
    • B60Q1/08—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights adjustable, e.g. remotely-controlled from inside vehicle automatically
    • B60Q1/085—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights adjustable, e.g. remotely-controlled from inside vehicle automatically due to special conditions, e.g. adverse weather, type of road, badly illuminated road signs or potential dangers
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/14—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights having dimming means
    • B60Q1/1415—Dimming circuits
    • B60Q1/1423—Automatic dimming circuits, i.e. switching between high beam and low beam due to change of ambient light or light level in road traffic
    • B60Q1/143—Automatic dimming circuits, i.e. switching between high beam and low beam due to change of ambient light or light level in road traffic combined with another condition, e.g. using vehicle recognition from camera images or activation of wipers
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/06—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights adjustable, e.g. remotely-controlled from inside vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
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    • B60Q1/06—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights adjustable, e.g. remotely-controlled from inside vehicle
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    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/14—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights having dimming means
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/02—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
    • B60Q1/04—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights
    • B60Q1/14—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments the devices being headlights having dimming means
    • B60Q1/1415—Dimming circuits
    • B60Q1/1423—Automatic dimming circuits, i.e. switching between high beam and low beam due to change of ambient light or light level in road traffic
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F21—LIGHTING
    • F21S—NON-PORTABLE LIGHTING DEVICES; SYSTEMS THEREOF; VEHICLE LIGHTING DEVICES SPECIALLY ADAPTED FOR VEHICLE EXTERIORS
    • F21S41/00—Illuminating devices specially adapted for vehicle exteriors, e.g. headlamps
    • F21S41/60—Illuminating devices specially adapted for vehicle exteriors, e.g. headlamps characterised by a variable light distribution
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    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q2300/00—Indexing codes for automatically adjustable headlamps or automatically dimmable headlamps
    • B60Q2300/05—Special features for controlling or switching of the light beam
    • B60Q2300/054—Variable non-standard intensity, i.e. emission of various beam intensities different from standard intensities, e.g. continuous or stepped transitions of intensity
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q2300/00—Indexing codes for automatically adjustable headlamps or automatically dimmable headlamps
    • B60Q2300/05—Special features for controlling or switching of the light beam
    • B60Q2300/056—Special anti-blinding beams, e.g. a standard beam is chopped or moved in order not to blind
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q2300/00—Indexing codes for automatically adjustable headlamps or automatically dimmable headlamps
    • B60Q2300/40—Indexing codes relating to other road users or special conditions
    • B60Q2300/45—Special conditions, e.g. pedestrians, road signs or potential dangers
    • G—PHYSICS
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
    • Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection

Definitions

  • the present disclosure relates to the technical field of assisted driving, in particular to a light intensity adjustment method and device, electronic equipment and storage medium.
  • assisted driving technology can assist the safe driving of vehicles. More and more assisted driving functions have been applied to the automatic driving of vehicles, for example, lane keeping function, automatic parking function, brake assist function and so on. Assisted driving technology can assist users in driving safely.
  • the present disclosure proposes a technical solution for light intensity adjustment.
  • a light intensity adjustment method including:
  • the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
  • determining the distance between the target object and the smart driving device according to the image collected by the smart driving device includes:
  • the distance between the target object and the intelligent driving device is determined.
  • determining the position of the target object according to the image includes:
  • the position of the target object is determined.
  • determining the position of the target object based on the image coordinates of the target object in the image includes:
  • the determining the distance between the intelligent driving device and the target object according to the position of the target object includes:
  • the distance between the target object and the intelligent driving device is determined.
  • the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
  • the determining the distance between the target object and the smart driving device according to the image collected by the smart driving device includes:
  • the image determine the number of reference objects between the target object and the intelligent driving device; wherein the distance between two adjacent reference objects is known;
  • the distance between the intelligent driving device and the target object is determined according to the number of reference objects between the target object and the intelligent driving device and the distance between adjacent reference objects.
  • adjusting the luminous intensity of the illuminator of the smart driving device according to the distance between the smart driving device and the target object includes:
  • the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
  • adjusting the luminous intensity of the lighting lamp of the smart driving device according to the distance between the smart driving device and the target object includes:
  • the luminous intensity of the illuminator of the smart driving device is adjusted to a target luminous intensity corresponding to the distance between the smart driving device and the target object.
  • the determination of the distance between the intelligent driving device and the target object is based on the correspondence between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object.
  • the target luminous intensity corresponding to the distance of including:
  • the determination of the distance between the intelligent driving device and the target object is based on the correspondence between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object.
  • the target luminous intensity corresponding to the distance of including:
  • the second distance interval is a distance interval of the function
  • the method further includes:
  • the luminous intensity of the illuminating lamp of the intelligent driving device is adjusted to a preset luminous intensity, or the luminous intensity of the illuminating lamp of the intelligent driving device is maintained The intensity is unchanged.
  • the intelligent driving device in the embodiment of the present disclosure is a vehicle with an automatic driving function, or a vehicle with a driving assistance function.
  • a light intensity adjusting device including:
  • a determining module configured to determine the distance between the target object and the smart driving device according to the image collected by the smart driving device
  • the adjustment module is used to adjust the luminous intensity of the illuminator of the intelligent driving device according to the distance between the intelligent driving device and the target object.
  • the determining module is configured to determine the position of the target object according to the image; and determine the distance between the target object and the intelligent driving device according to the position of the target object. the distance.
  • the method when the determining module is configured to determine the position of the target object according to the image, the method includes:
  • the image coordinates of the target object in the image are determined; and the position of the target object is determined based on the image coordinates of the target object in the image.
  • the method when the determining module is configured to determine the position of the target object based on the image coordinates of the target object in the image, the method includes:
  • the determining module is configured to determine the distance between the target object and the intelligent driving device according to the position of the target object, including: according to the world coordinates of the target object and the world of the intelligent driving device The coordinates determine the distance between the target object and the intelligent driving device.
  • the determining module is further configured to determine the coordinate transformation relationship by adopting the following steps:
  • the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
  • the determining module is configured to determine the number of reference objects between the target object and the intelligent driving device according to the image; according to the target object and the intelligent driving device The number of reference objects between the devices and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object; wherein the distance between two adjacent reference objects is Known.
  • the adjustment module is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device.
  • the luminous intensity is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device.
  • the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the target luminous intensity corresponding to the distance between the target objects; the luminous intensity of the illuminator of the smart driving device is adjusted to the target luminous intensity corresponding to the distance between the smart driving device and the target object.
  • the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the target luminous intensity corresponding to the distance between target objects it includes:
  • the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the target luminous intensity corresponding to the distance between target objects it includes:
  • the second distance interval is a distance interval of the function
  • the determining module is further configured to determine, according to the image, that there is no target object in the image;
  • the adjustment module is also used to adjust the luminous intensity of the illuminating lamp of the smart driving device to a preset luminous intensity, or to keep the luminous intensity of the illuminating lamp of the smart driving device unchanged.
  • an electronic device including:
  • a memory for storing processor executable instructions
  • the processor is configured to execute the above light intensity adjustment method.
  • a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the above-mentioned light intensity adjustment method is realized.
  • a computer program including computer readable code, when the computer readable code is run in an electronic device, a processor in the electronic device executes the light intensity adjustment method.
  • the distance between the target object and the intelligent driving device and the target object can be determined based on the images collected by the intelligent driving device, and then the distance between the intelligent driving device and the target object can be adjusted according to the distance between the intelligent driving device and the target object.
  • the luminous intensity of the light In this way, the distance between pedestrians, vehicles, and other target objects and the intelligent driving device can be determined through the collected images, and the luminous intensity of the intelligent driving device's illuminating lamp can be automatically adjusted according to the distance, thereby providing convenience for vehicle driving and improving The safety of vehicle driving reduces the occurrence of traffic accidents.
  • Fig. 1 shows a flowchart of a light intensity adjustment method according to an embodiment of the present disclosure.
  • Fig. 2 shows a flowchart of an example of determining the image coordinates of a target object according to an embodiment of the present disclosure.
  • Fig. 3 shows a block diagram of an example of target detection using a neural network according to an embodiment of the present disclosure.
  • Fig. 4 shows a block diagram of a light intensity adjusting device according to an embodiment of the present disclosure.
  • Fig. 5 shows a block diagram of an example of an electronic device according to an embodiment of the present disclosure.
  • Fig. 6 shows a block diagram of an example of an electronic device according to an embodiment of the present disclosure.
  • the light intensity adjustment solution provided by the embodiments of the present disclosure can determine the distance between the target object and the intelligent driving device and the target object according to the image collected by the intelligent driving device, and then adjust according to the distance between the intelligent driving device and the target object The luminous intensity of the lighting of the intelligent driving device.
  • the distance between the smart driving device and the target object such as pedestrians and vehicles can be determined through the images collected by the smart driving device, and then the luminous intensity of the lighting lamp can be automatically adjusted according to the distance. For example, when there is no vehicle or pedestrian in front of it, The luminous intensity of the lights can be adjusted to a strong state.
  • the luminous intensity of the lights can be adjusted to a weaker state, which is convenient for the safe driving of the current vehicle or the vehicle in front, and improves The safety of vehicle driving reduces the occurrence of traffic accidents.
  • the light intensity adjustment solution provided by the embodiments of the present disclosure has a simple light intensity adjustment method, flexible and convenient application, and does not need to deploy other related devices, such as Bluetooth devices, hotspot devices, infrared devices, and other related devices for light intensity adjustment, thereby Reduce the cost of light intensity adjustment.
  • the light intensity adjustment solution provided by the embodiments of the present disclosure can determine the distance between the smart driving device and the target object through the image collected by the smart driving device, and automatically adjust the luminous intensity of the lighting lamp according to the distance, thereby improving the safety of the vehicle during driving , Bring great convenience to traffic.
  • the light intensity adjustment solution provided by the embodiments of the present disclosure can be applied to application scenarios such as automatic driving and assisted driving.
  • the intelligent driving device in an autonomous driving scenario, is a vehicle with automatic driving function, and the vehicle with automatic driving function can automatically adjust the luminous intensity of the lighting lamp according to the distance between the vehicle and the target object during the driving process;
  • the intelligent driving device In the driving scene, is a vehicle with assisted driving function.
  • the vehicle with assisted driving function can determine the target light intensity of the lights according to the distance between the vehicle and the target object during the driving process, and prompt the driver Adjust the light intensity of the car lights to the target light intensity.
  • Fig. 1 shows a flowchart of a light intensity adjustment method according to an embodiment of the present disclosure.
  • the light intensity adjustment method can be executed by a terminal device, a server, or other information processing equipment.
  • the terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, or a personal digital processing device. (Personal Digital Assistant, PDA), handheld devices, computing devices, smart driving devices, wearable devices, etc.
  • the light intensity adjustment method may be implemented by a processor invoking computer-readable instructions stored in a memory.
  • the light intensity adjustment solution of the embodiment of the present disclosure will be described below by taking the intelligent driving device as the execution subject as an example.
  • the light intensity adjustment method includes the following steps:
  • Step S11 Determine the distance between the target object and the smart driving device according to the image collected by the smart driving device.
  • the smart driving device can be a car, a robot, etc., which can drive on the road, and has a device that can illuminate under the condition of insufficient light.
  • the smart driving device can be equipped with an image collection device, such as a camera.
  • Intelligent driving equipment can collect images of the current scene in real time, and then perform target detection on the collected images. According to the detection result of the target detection on the image, it is determined whether there is a target object in the collected image.
  • the distance between the target object and the intelligent driving device can be determined by the image position of the target object in the image, or the distance between the target object and the intelligent driving device can be determined by the reference object between the target object and the intelligent driving device.
  • the number that is, the number of reference objects located between the target object and the intelligent driving device along the image acquisition direction in the captured image, determines the distance between the target object and the intelligent driving device.
  • a pre-trained neural network can be used to perform image feature extraction on the image to obtain the image position of the target object in the target image.
  • the target image can be matched with a pre-stored image template to determine whether there is a projection of the target object in the target image, and if there is a projection of the target object, the image position of the target object in the image can be further determined. Then from the image position of the target object, the position of the target object in the current scene can be further determined.
  • the position of the target object in the current scene may be an accurate position, for example, it may be a world coordinate in a world coordinate system, or it may be a rough position.
  • the target object can be a pedestrian, a motor vehicle or a non-motor vehicle that can pass on a traffic road.
  • the luminous intensity of the illuminator of the smart driving device can be adjusted to a preset luminous intensity, or the smart driving device's luminous intensity can be maintained. The luminous intensity of the lamp remains unchanged.
  • the luminous intensity of the lighting lamp can be adjusted to a preset luminous intensity, which can be a strong luminous intensity, so that it does not exist in the current scene
  • the lighting can be adjusted to a strong luminous intensity to provide good lighting conditions for intelligent driving equipment.
  • the luminous intensity of the lighting lamp can be kept constant, so that the intelligent driving device maintains the current lighting conditions.
  • the intelligent driving device can determine the location of the target object based on the collected images, and then determine the distance between the target object and the intelligent driving device according to the location of the target object.
  • the intelligent driving device can determine the position of the target object in the world coordinate system according to the image position of the target object in the image when it detects that the target object exists in the image. Then, the distance between the intelligent driving device and the target object can be determined according to the position of the target object in the world coordinate system and the current position of the intelligent driving device.
  • the distance between each target object and the intelligent driving device can be determined according to the position of each target object in the world coordinate system.
  • the image coordinates of the target object in the image can be determined according to the images collected by the intelligent driving device, and then the position of the target object can be determined based on the image coordinates of the target object in the image.
  • the image coordinates of the target object in the image can be understood as the image coordinates corresponding to the projection of the target object on the target image.
  • the image coordinates of the target object in the image can be determined.
  • the position of the target object in the current scene can be determined, and the position can be the world coordinates in the world coordinate system.
  • the current scene may be a scene where the lighting lamp is turned on in a dark environment, and the target detection on the collected target image may be when the lighting lamp is turned on.
  • the image coordinates of the target object in the image may be the center coordinates or average coordinates of the target object projected in the image, or may be the image coordinates of any point projected by the target object in the image.
  • the image coordinates of the target object can be converted into world coordinates in the world coordinate system according to the coordinate transformation relationship, and then the target object and the intelligent driving device can be determined according to the world coordinates of the target object and the world coordinates of the intelligent driving device.
  • the distance between devices can be converted into world coordinates in the world coordinate system according to the coordinate transformation relationship, and then the target object and the intelligent driving device can be determined according to the world coordinates of the target object and the world coordinates of the intelligent driving device. The distance between devices.
  • the coordinate transformation relationship may be the transformation relationship of the image coordinates of the target image collected by the intelligent driving device into the world coordinates.
  • the image coordinates of the three-dimensional space points projected in the image can be converted into the spatial points. World coordinates.
  • the image coordinates of the target object can be converted into world coordinates in the world coordinate system, so that the position of the target object can be quickly determined.
  • the intelligent driving device can obtain the world coordinates of the current position detected by the navigation system or the positioning system, so that the difference between the world coordinates of the current position of the intelligent driving device and the determined world coordinates of the target object can be used to obtain the intelligent driving device and the target The distance between objects. In this way, a more accurate distance between the intelligent driving device and the target object can be obtained.
  • the labeled image may be obtained, and then the image coordinates of the labeled point in the labeled image may be determined, and then the coordinate transformation relationship between the image coordinates and the world coordinates may be determined according to the image coordinates of the labeled point and the pre-labeled world coordinates.
  • the annotated image may be a collected image with annotated information.
  • the annotation information may be the world coordinates of the spatial point corresponding to the pixel point in the annotation image.
  • the coordinate transformation relationship from the image coordinates to the world coordinates can be determined, and the coordinate transformation relationship can be expressed by a transformation matrix.
  • the coordinate transformation relationship can be determined according to the image coordinates and world coordinates of four spatial points in an annotated image.
  • the coordinate transformation relationship can be determined according to the image coordinates and world coordinates of a space point of each of the four annotated images. In this way, the coordinate transformation relationship between the image coordinates and the world coordinates in the current scene can be quickly and accurately determined.
  • the number of reference objects between the target object and the intelligent driving device can be determined according to the images collected by the intelligent driving device, and then the number of reference objects between the target object and the intelligent driving device and the number of reference objects between the target object and the intelligent driving device can be determined according to the images collected by the intelligent driving device.
  • the distance between adjacent reference objects determines the distance between the intelligent driving device and the target object.
  • the distance between two adjacent reference objects is known.
  • the smart driving device can recognize the image collected by the smart driving device, and determine the target object and the reference object recognized in the image.
  • the reference object here may be a landmark object with location information, for example, the reference object may be a street lamp, a trash can, a green tree, and so on.
  • the position information of the reference object may be the distance between adjacent reference objects. Then the number of reference objects in the foreground of the target object in the image can be counted, and the number of reference objects existing in the foreground of the target object can be considered as the number of reference objects existing between the target object and the intelligent driving device.
  • the number of reference objects between the object and the intelligent driving device and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object.
  • the target object and the intelligent driving device are The distance between them is greater than or equal to 20 meters.
  • the position information of the reference object may be world coordinates.
  • the relative position relationship between the reference object and the target object can be used, for example, the target object is far away from the intelligent driving device relative to the reference object, so that the The world coordinates of the intelligent driving device and the world coordinates of the reference object are determined.
  • the distance between the intelligent driving device and the reference object is first determined, and then the distance between the target object and the intelligent driving device is estimated based on the distance between the intelligent driving device and the reference object.
  • the distance between the target object and the intelligent driving device is greater than the distance between the intelligent driving device and the reference object.
  • the smart driving device can determine the target distance between the target object and the smart driving device without configuring other ranging devices, for example, without configuring infrared devices, laser devices and other ranging devices, which is simple and easy.
  • the smart driving device can multiplex the collected target image. For example, when the target image is used to determine the distance between the target object and the smart driving device, the target image can also be used to determine whether the smart driving device deviates from the lane. And other operations.
  • Step S12 Adjust the luminous intensity of the lighting lamp of the intelligent driving device according to the distance between the intelligent driving device and the target object.
  • the smart driving device can adjust the luminous intensity of the lighting lamp according to the distance between the smart driving device and the target object, for example, when the distance between the smart driving device and the target object is greater than a preset threshold
  • the luminous intensity of the lighting lamp can be kept unchanged, or the luminous intensity can be adjusted to the first luminous intensity, which can be a relatively strong luminous intensity, so as to provide good lighting conditions for the intelligent driving device.
  • the luminous intensity of the illuminator can be adjusted to the second luminous intensity, and the second luminous intensity can be a weaker luminous intensity, so that Reduce the impact on pedestrians, vehicles and other target objects.
  • the target luminous intensity corresponding to the distance between the smart driving device and the target object can be determined according to the corresponding relationship between the target distance and the distance between the smart driving device and the target object, and then the smart driving device The luminous intensity of the lighting lamp is adjusted to the target luminous intensity.
  • the intelligent driving device may obtain the pre-stored correspondence between the target distance and the target luminous intensity, and then query the determined target luminous intensity corresponding to the distance between the determined target object and the intelligent driving device according to the correspondence.
  • the target distance and the target luminous intensity may be a piecewise function.
  • the target luminous intensity may be the first luminous intensity
  • the target The luminous intensity may be the second luminous intensity, so that the target luminous intensity corresponding to the distance between the target object and the intelligent driving device can be quickly determined through the correspondence between the target distance and the target luminous intensity.
  • the target distance and the target luminous intensity may also be a continuous function, so that the luminous intensity of the illuminator of the smart driving device can be continuously changed according to the distance between the target object and the smart driving device.
  • the corresponding relationship between the target distance and the target luminous intensity can be determined by data obtained from a large number of scene simulations. For example, in the case of a certain target distance, the acceptable luminous intensity for pedestrians or drivers at the target distance is determined, and the determined acceptable luminous intensity can be used as the target luminous intensity corresponding to the target distance. In some implementations, after determining the acceptable luminous intensity for pedestrians or drivers at a certain target distance, the acceptable luminous intensity can also be adjusted, for example, the acceptable luminous intensity can be reduced by a certain value, The reduced luminous intensity is used as the target luminous intensity corresponding to the target distance.
  • the distance between the smart driving device and the target object is in the first distance interval to which the list of the correspondence between the target distance and the target luminous intensity belongs, and then the distance corresponding to the first distance interval in the list Target luminous intensity, to determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object.
  • the corresponding relationship between the target distance and the target luminous intensity can be represented by a list.
  • the list can record multiple distance intervals and the luminous intensity or luminous intensity coefficient corresponding to each distance interval, so that the luminous intensity corresponding to the first distance interval can be found according to the first distance interval where the distance between the intelligent driving device and the target object is located
  • the intensity or luminous intensity coefficient determines the target luminous intensity corresponding to the distance between the intelligent driving device and the target object.
  • the luminous intensity coefficient can be multiplied by the maximum value of the intelligent driving device. Luminous intensity, the target luminous intensity corresponding to the distance between the intelligent driving device and the target object is obtained.
  • the target luminous intensity of the illuminator is set to 6 levels
  • the target luminous intensity coefficients are 0, 0.2, 0.4, 0.6, 0.8, and 1, respectively.
  • the corresponding relationship between the target distance and the target luminous intensity shown in Table 1 can be used to determine the distance between the intelligent driving device and the target object.
  • Target distance (m) Target luminous intensity coefficient 0-20 0.2 20-40 0.4 40-70 0.6 70-120 0.8 >120 1
  • the distance between the smart driving device and the target object can be determined according to the distance between the smart driving device and the target object and the function that characterizes the corresponding relationship between the target distance and the target luminous intensity. Two distance interval. Then, according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function, the target luminous intensity corresponding to the distance between the intelligent driving device and the target object is determined.
  • the second distance interval is a distance interval of the function.
  • This function can include the calculation method of the luminous intensity or luminous intensity coefficient corresponding to each distance interval.
  • the distance interval can be multiple, so that the second distance interval can be found according to the second distance interval of the distance between the intelligent driving device and the target object.
  • the distance interval corresponds to the target calculation method, and the target calculation method is used to calculate the target luminous intensity corresponding to the distance between the intelligent driving device and the target object.
  • the target luminous intensity coefficient of the maximum luminous intensity of the intelligent driving equipment is 1, and the target luminous intensity coefficient when the illuminator is not luminous is 0.
  • the target distance and the target luminous intensity coefficient can be expressed as a linear function. The function is shown in formula (1):
  • y can represent the target luminous intensity coefficient
  • x can represent the target distance.
  • the target luminous intensity corresponding to the distance between the intelligent driving device and the target object is determined by the calculation method of the target distance and the target luminous intensity coefficient shown in formula (1).
  • the distance between pedestrians, vehicles, and other target objects and the intelligent driving device can be determined, and the luminous intensity of the lighting lamp can be automatically adjusted according to the distance, so as to facilitate the driving of the vehicle and improve the vehicle.
  • Driving safety reduces the occurrence of traffic accidents.
  • the following describes the process of obtaining the image coordinates of the target object through an example.
  • Fig. 2 shows a flowchart of an example of determining the image coordinates of a target object according to an embodiment of the present disclosure, which may include the following steps:
  • Step S21 Perform feature extraction on the collected image to obtain image features of the image.
  • a neural network can be used to perform feature extraction on the collected image to obtain the image feature of the image.
  • the collected image can be used as the input of the neural network, and the neural network is used to perform convolution operation on the input image to obtain the image characteristics of the image.
  • Product operation to obtain the image features of the image which can improve the efficiency and quality of image feature extraction.
  • Step S22 Determine an image area belonging to the target feature class in the image according to the image feature of the image.
  • the image area belonging to the target feature class in the image can be determined based on the image features extracted by the neural network.
  • the target feature class can represent the image features of each type of target object.
  • the target object can be a pedestrian.
  • the target feature class can be a feature class formed by the image features of pedestrians.
  • the target object may include one or more of pedestrians, non-motorized vehicles, and motor vehicles.
  • the target feature class may include one or more of the pedestrian feature class, the non-motorized vehicle feature class, and the motor vehicle feature class. class.
  • the branch network of each target feature class can be used to perform convolution operations on the image features of the target image to obtain the detection result of the image area of each target feature class, and then according to For the detection results of the image regions of the multiple target feature classes, determine at least one image region belonging to the multiple target feature classes in the target image.
  • the neural network may include multiple branch networks, and each branch network can perform convolution operations on the image features of the image in parallel to obtain the detection results for the image regions of each target feature class.
  • the detection results can be each The image area where the target object of the target feature class is located. Then, the detection results obtained by each branch network can be combined to obtain at least one image area belonging to multiple target feature classes.
  • Fig. 3 shows a block diagram of an example of target detection using a neural network according to an embodiment of the present disclosure.
  • the above-mentioned neural network may include three branch networks, the first branch network can correspond to the pedestrian feature class, so that the first branch network can be used to detect the image area of the pedestrian feature class, and the presence of the target image is detected
  • the image area of the pedestrian can be identified.
  • a box is used to identify the image area where the pedestrian is located, and the image area identified by the box may be the detection result of the image area of the pedestrian characteristic.
  • the second branch network can correspond to the non-motor vehicle feature class, and the second branch network can be used to obtain the image area detection result for the non-motor vehicle feature class.
  • the third branch network can correspond to motor vehicle feature classes, and the third branch network can be used to obtain image area detection results for motor vehicle feature classes. Then, the detection results obtained by each or at least one branch network can be combined to finally obtain the image areas where the pedestrians, motor vehicles, and non-motor vehicles are identified by the box.
  • Step S23 Determine the image coordinates of the target object in the image according to the image area belonging to the target feature class in the image.
  • the image coordinates of the area center of the image area can be determined according to the image coordinates of the image area belonging to the target feature class in the image, and the image coordinates of the area center can be determined as the image coordinates of the target object.
  • you can select any pixel in the image area determine the image coordinates of the pixel, and determine the image coordinates of the pixel as the image coordinates of the target object.
  • the average image coordinates of the pixels in the image area can be calculated, and the average image coordinates can be determined as the image coordinates of the target object.
  • the embodiments of the present disclosure do not limit the network structure of the foregoing neural network, and may be any neural network with a target detection function, for example, a neural network with a network structure such as faster RCNN, SSD, YOLO, etc.
  • a neural network with a network structure such as faster RCNN, SSD, YOLO, etc.
  • there are no special restrictions on the number and size of the neural network so that the light intensity adjustment scheme provided by the embodiments of the present disclosure has high practicability, and can be used in any scene where the luminous intensity of the light needs to be adjusted. .
  • the present disclosure also provides light intensity adjustment devices, electronic equipment, computer-readable storage media, and programs, all of which can be used to implement any light intensity adjustment method provided in the present disclosure.
  • light intensity adjustment devices electronic equipment, computer-readable storage media, and programs, all of which can be used to implement any light intensity adjustment method provided in the present disclosure.
  • the writing order of the steps does not mean a strict execution order but constitutes any limitation on the implementation process.
  • the specific execution order of each step should be based on its function and possibility.
  • the inner logic is determined.
  • Fig. 4 shows a block diagram of a light intensity adjustment device according to an embodiment of the present disclosure. As shown in Fig. 4, the light intensity adjustment device includes:
  • the determining module 41 is configured to determine the distance between the target object and the smart driving device according to the image collected by the smart driving device;
  • the adjustment module 42 is configured to adjust the luminous intensity of the lighting lamp of the intelligent driving device according to the distance between the intelligent driving device and the target object.
  • the determining module 41 is configured to determine the position of the target object according to the image; determine the position of the target object and the intelligent driving device according to the position of the target object The distance between.
  • the determining module 41 is configured to determine the position of the target object according to the image, including:
  • the image coordinates of the target object in the image are determined; and the position of the target object is determined based on the image coordinates of the target object in the image.
  • the determining module 41 is configured to determine the position of the target object based on the image coordinates of the target object in the image, including:
  • the determining module 41 is configured to determine the distance between the target object and the intelligent driving device according to the position of the target object, including: according to the world coordinates of the target object and the intelligent driving device The world coordinates determine the distance between the target object and the intelligent driving device.
  • the determining module 41 is further configured to determine the coordinate transformation relationship by adopting the following steps:
  • the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
  • the determining module 41 is configured to determine the number of reference objects between the target object and the intelligent driving device according to the image; according to the target object and the intelligent driving device The number of reference objects between driving devices and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object; wherein the distance between two adjacent reference objects is known.
  • the adjustment module 42 is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device.
  • the luminous intensity of the lamp is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device.
  • the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the target luminous intensity corresponding to the distance between the target objects includes:
  • the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object.
  • the target luminous intensity corresponding to the distance between the target objects includes:
  • the second distance interval is a distance interval of the function
  • the adjustment module 42 is further configured to adjust the luminous intensity of the illuminator of the intelligent driving device to a preset value when it is determined that there is no target object in the image according to the image. Or, keep the luminous intensity of the illuminating lamp of the intelligent driving device unchanged.
  • the intelligent driving device in the embodiments of the present disclosure is a vehicle with an automatic driving function, or a vehicle with a driving assistance function.
  • the functions or modules contained in the device provided in the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments.
  • the functions or modules contained in the device provided in the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments.
  • the embodiments of the present disclosure also provide a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above-mentioned method when executed by a processor.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium.
  • An embodiment of the present disclosure also provides an electronic device, including: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured as the above method.
  • the embodiment of the present disclosure also proposes a computer program, including computer readable code, when the computer readable code is executed in an electronic device, the processor in the electronic device executes to implement the above method.
  • the electronic device can be provided as a terminal, server or other form of device.
  • Fig. 5 is a block diagram showing an electronic device 800 according to an exemplary embodiment.
  • the electronic device 800 may be a mobile phone, a computer, a digital broadcasting terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, and other terminals.
  • the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, and a sensor component 814 , And communication component 816.
  • the processing component 802 generally controls the overall operations of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations.
  • the processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the foregoing method.
  • the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components.
  • the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.
  • the memory 804 is configured to store various types of data to support operations in the electronic device 800. Examples of these data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc.
  • the memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable and Programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read-only memory
  • EPROM erasable and Programmable read only memory
  • PROM programmable read only memory
  • ROM read only memory
  • magnetic memory flash memory
  • flash memory magnetic disk or optical disk.
  • the power supply component 806 provides power for various components of the electronic device 800.
  • the power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
  • the multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user.
  • the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user.
  • the touch panel includes one or more touch sensors to sense touch, sliding, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure related to the touch or slide operation.
  • the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.
  • the audio component 810 is configured to output and/or input audio signals.
  • the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal.
  • the received audio signal may be further stored in the memory 804 or transmitted via the communication component 816.
  • the audio component 810 further includes a speaker for outputting audio signals.
  • the I/O interface 812 provides an interface between the processing component 802 and a peripheral interface module.
  • the peripheral interface module may be a keyboard, a click wheel, a button, and the like. These buttons may include, but are not limited to: home button, volume button, start button, and lock button.
  • the sensor component 814 includes one or more sensors for providing the electronic device 800 with various aspects of state evaluation.
  • the sensor component 814 can detect the on/off state of the electronic device 800 and adjust the relative light intensity of the component.
  • the component is the display and the keypad of the electronic device 800, and the sensor component 814 can also detect the electronic device 800 or the electronic device.
  • the position of a component 800 changes, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration/deceleration of the electronic device 800, and the temperature change of the electronic device 800.
  • the sensor component 814 may include a proximity sensor configured to detect the presence of nearby objects when there is no physical contact.
  • the sensor component 814 may also include a light sensor, such as a complementary metal oxide semiconductor (CMOS) or charge coupled device (CCD) image sensor, for use in imaging applications.
  • CMOS complementary metal oxide semiconductor
  • CCD charge coupled device
  • the sensor component 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
  • the communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices.
  • the electronic device 800 can access a wireless network based on a communication standard, such as a wireless network (WiFi), a second-generation mobile communication technology (2G) or a third-generation mobile communication technology (3G), or a combination thereof.
  • the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel.
  • the communication component 816 further includes a near field communication (NFC) module to facilitate short-range communication.
  • the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field-available A programmable gate array (FPGA), controller, microcontroller, microprocessor, or other electronic components are implemented to implement the above methods.
  • ASIC application-specific integrated circuits
  • DSP digital signal processors
  • DSPD digital signal processing devices
  • PLD programmable logic devices
  • FPGA field-available A programmable gate array
  • controller microcontroller, microprocessor, or other electronic components are implemented to implement the above methods.
  • a non-volatile computer-readable storage medium or a volatile computer-readable storage medium is also provided, such as the memory 804 including computer program instructions, which can be processed by the electronic device 800.
  • the device 820 executes to complete the above-mentioned method.
  • Fig. 6 is a block diagram showing an electronic device 1900 according to an exemplary embodiment.
  • the electronic device 1900 may be provided as a server. 6
  • the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by the memory 1932, for storing instructions executable by the processing component 1922, such as application programs.
  • the application program stored in the memory 1932 may include one or more modules each corresponding to a set of instructions.
  • the processing component 1922 is configured to execute instructions to perform the above-described methods.
  • the electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input output (I/O) interface 1958 .
  • the electronic device 1900 can operate based on an operating system stored in the memory 1932, such as a Microsoft server operating system (Windows Server TM ), a graphical user interface operating system (Mac OS X TM ) launched by Apple, and a multi-user and multi-process computer operating system (Unix TM ), free and open source Unix-like operating system (Linux TM ), open source Unix-like operating system (FreeBSD TM ) or similar.
  • Microsoft server operating system Windows Server TM
  • Mac OS X TM graphical user interface operating system
  • Unix TM multi-user and multi-process computer operating system
  • FreeBSD TM open source Unix-like operating system
  • a non-volatile computer-readable storage medium or a volatile computer-readable storage medium is also provided, such as the memory 1932 including computer program instructions, which can be processed by the electronic device 1900.
  • the component 1922 executes to complete the above method.
  • the present disclosure may be a system, method and/or computer program product.
  • the computer program product may include a computer-readable storage medium loaded with computer-readable program instructions for enabling a processor to implement various aspects of the present disclosure.
  • the computer-readable storage medium may be a tangible device that can hold and store instructions used by the instruction execution device.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing.
  • Non-exhaustive list of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) Or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as a printer with instructions stored thereon
  • RAM random access memory
  • ROM read-only memory
  • EPROM erasable programmable read-only memory
  • flash memory flash memory
  • SRAM static random access memory
  • CD-ROM compact disk read-only memory
  • DVD digital versatile disk
  • memory stick floppy disk
  • mechanical encoding device such as a printer with instructions stored thereon
  • the computer-readable storage medium used here is not interpreted as the instantaneous signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (for example, light pulses through fiber optic cables), or through wires Transmission of electrical signals.
  • the computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to various computing/processing devices, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and/or a wireless network.
  • the network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers.
  • the network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network, and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing/processing device .
  • the computer program instructions used to perform the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or in one or more programming languages.
  • Source code or object code written in any combination, the programming language includes object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as "C" language or similar programming languages.
  • Computer-readable program instructions can be executed entirely on the user's computer, partly on the user's computer, executed as a stand-alone software package, partly on the user's computer and partly executed on a remote computer, or entirely on the remote computer or server carried out.
  • the remote computer can be connected to the user's computer through any kind of network-including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect to the user's computer) connection).
  • LAN local area network
  • WAN wide area network
  • an electronic circuit such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), can be customized by using the status information of the computer-readable program instructions.
  • FPGA field programmable gate array
  • PDA programmable logic array
  • the computer-readable program instructions are executed to realize various aspects of the present disclosure.
  • These computer-readable program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine that makes these instructions when executed by the processor of the computer or other programmable data processing device , A device that implements the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams is produced. It is also possible to store these computer-readable program instructions in a computer-readable storage medium. These instructions make computers, programmable data processing apparatuses, and/or other devices work in a specific manner. Thus, the computer-readable medium storing the instructions includes An article of manufacture, which includes instructions for implementing various aspects of the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of an instruction, and the module, program segment, or part of an instruction contains one or more components for realizing the specified logical function.
  • Executable instructions may also occur in a different order than the order marked in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart can be implemented by a dedicated hardware-based system that performs the specified functions or actions Or it can be realized by a combination of dedicated hardware and computer instructions.
  • the computer program product can be specifically implemented by hardware, software, or a combination thereof.
  • the computer program product is specifically embodied as a computer storage medium.
  • the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc. Wait.
  • SDK software development kit

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Abstract

A light intensity adjustment method and apparatus, an electronic device and a storage medium. The method comprises: determining, according to an image collected by an intelligent driving device, the distance between a target object and the intelligent driving device; and adjusting, according to the distance between the intelligent driving device and the target object, the luminous intensity of an illuminating light of the intelligent driving device. By means of the method, the light intensity of an illuminating light can be automatically adjusted.

Description

光强调节方法及装置、电子设备和存储介质Light intensity adjustment method and device, electronic equipment and storage medium
本公开要求在2019年9月27日提交中国专利局、申请号为201910925583.1、申请名称为“光强调节方法及装置、电子设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本公开中。This disclosure claims the priority of a Chinese patent application filed with the Chinese Patent Office on September 27, 2019, the application number is 201910925583.1, and the application name is "light intensity adjustment method and device, electronic equipment and storage medium", the entire content of which is incorporated by reference Incorporated in this disclosure.
技术领域Technical field
本公开涉及辅助驾驶技术领域，尤其涉及一种光强调节方法及装置、电子设备和存储介质。The present disclosure relates to the technical field of assisted driving, in particular to a light intensity adjustment method and device, electronic equipment and storage medium.
背景技术Background technique
近年来，随着车辆的普及，辅助驾驶技术应运而生。辅助驾驶技术可以辅助车辆的安全行驶，越来越多的辅助驾驶功能已经被应用在车辆的自动驾驶中，例如，车道保持功能、自动泊车功能、刹车辅助功能等。辅助驾驶技术可以辅助用户进行安全行驶。In recent years, with the popularization of vehicles, assisted driving technologies have emerged. Assisted driving technology can assist the safe driving of vehicles. More and more assisted driving functions have been applied to the automatic driving of vehicles, for example, lane keeping function, automatic parking function, brake assist function and so on. Assisted driving technology can assist users in driving safely.
发明内容Summary of the invention
本公开提出了一种光强调节技术方案。The present disclosure proposes a technical solution for light intensity adjustment.
根据本公开的一方面，提供了一种光强调节方法，包括：According to an aspect of the present disclosure, there is provided a light intensity adjustment method, including:
根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离；Determine the distance between the target object and the smart driving device according to the images collected by the smart driving device;
根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。According to the distance between the intelligent driving device and the target object, the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
在一种可能的实现方式中，根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离，包括：In a possible implementation manner, determining the distance between the target object and the smart driving device according to the image collected by the smart driving device includes:
根据所述图像，确定所述目标对象的位置；Determine the position of the target object according to the image;
根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离。According to the position of the target object, the distance between the target object and the intelligent driving device is determined.
在一种可能的实现方式中，根据所述图像，确定所述目标对象的位置，包括：In a possible implementation manner, determining the position of the target object according to the image includes:
根据所述图像，确定所述目标对象在所述图像中的图像坐标；Determine the image coordinates of the target object in the image according to the image;
基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置。Based on the image coordinates of the target object in the image, the position of the target object is determined.
在一种可能的实现方式中，基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置，包括：In a possible implementation manner, determining the position of the target object based on the image coordinates of the target object in the image includes:
根据坐标变换关系，将所述目标对象的图像坐标转换为世界坐标系下的世界坐标；According to the coordinate transformation relationship, converting the image coordinates of the target object into world coordinates in the world coordinate system;
所述根据所述目标对象的位置，确定所述智能驾驶设备与所述目标对象之间的距离，包括：The determining the distance between the intelligent driving device and the target object according to the position of the target object includes:
根据所述目标对象的世界坐标以及所述智能驾驶设备的世界坐标，确定所述目标对象与所述智能驾驶设备之间的距离。According to the world coordinates of the target object and the world coordinates of the intelligent driving device, the distance between the target object and the intelligent driving device is determined.
在一种可能的实现方式中，采用以下步骤确定所述坐标变换关系：In a possible implementation manner, the following steps are adopted to determine the coordinate transformation relationship:
获取标注图像；Obtain annotated images;
确定标注点在所述标注图像的图像坐标；Determining the image coordinates of the annotation point on the annotation image;
根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。According to the image coordinates of the marked points and the pre-marked world coordinates, the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
在一种可能的实现方式中，所述根据智能驾驶设备采集到的图像，确定所述目标对 象与所述智能驾驶设备之间的距离，包括：In a possible implementation manner, the determining the distance between the target object and the smart driving device according to the image collected by the smart driving device includes:
根据所述图像，确定所述目标对象与所述智能驾驶设备之间的参考对象的数量；其中，相邻的两个参考对象之间的间距是已知的；According to the image, determine the number of reference objects between the target object and the intelligent driving device; wherein the distance between two adjacent reference objects is known;
根据所述目标对象与所述智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定所述智能驾驶设备与所述目标对象之间的距离。The distance between the intelligent driving device and the target object is determined according to the number of reference objects between the target object and the intelligent driving device and the distance between adjacent reference objects.
在一种可能的实现方式中，所述目标对象为多个，根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度，包括：In a possible implementation manner, there are multiple target objects, and adjusting the luminous intensity of the illuminator of the smart driving device according to the distance between the smart driving device and the target object includes:
根据多个目标对象与所述智能驾驶设备之间的最小距离，调节所述智能驾驶设备的照明灯的发光强度。According to the minimum distance between the multiple target objects and the intelligent driving device, the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
在一种可能的实现方式中，根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度，包括：In a possible implementation manner, adjusting the luminous intensity of the lighting lamp of the smart driving device according to the distance between the smart driving device and the target object includes:
根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度；Determine the target luminous intensity corresponding to the distance between the smart driving device and the target object according to the correspondence between the target distance and the target luminous intensity and the distance between the smart driving device and the target object;
将所述智能驾驶设备的照明灯的发光强度调节至所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。The luminous intensity of the illuminator of the smart driving device is adjusted to a target luminous intensity corresponding to the distance between the smart driving device and the target object.
在一种可能的实现方式中，所述根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度，包括：In a possible implementation manner, the determination of the distance between the intelligent driving device and the target object is based on the correspondence between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object. The target luminous intensity corresponding to the distance of, including:
确定所述智能驾驶设备与所述目标对象之间的距离在目标距离与目标发光强度的对应关系的列表中所属的第一距离区间；Determine the first distance interval to which the distance between the intelligent driving device and the target object belongs in the list of correspondences between the target distance and the target luminous intensity;
根据所述列表中所述第一距离区间对应的目标发光强度，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the target luminous intensity corresponding to the first distance interval in the list.
在一种可能的实现方式中，所述根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度，包括：In a possible implementation manner, the determination of the distance between the intelligent driving device and the target object is based on the correspondence between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object. The target luminous intensity corresponding to the distance of, including:
根据所述智能驾驶设备与所述目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定所述智能驾驶设备与所述目标对象之间的距离所在的第二距离区间；所述第二距离区间为所述函数的一个距离区间；According to the distance between the intelligent driving device and the target object and a function that characterizes the correspondence between the target distance and the target luminous intensity, determine the second distance interval in which the distance between the intelligent driving device and the target object is located ; The second distance interval is a distance interval of the function;
根据所述函数中所述第二距离区间对应的目标距离与目标发光强度的计算方式，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function.
在一种可能的实现方式中，所述方法还包括：In a possible implementation manner, the method further includes:
在根据所述图像，确定所述图像中不存在目标对象时，将所述智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持所述智能驾驶设备的照明灯的发光强度不变。When it is determined according to the image that there is no target object in the image, the luminous intensity of the illuminating lamp of the intelligent driving device is adjusted to a preset luminous intensity, or the luminous intensity of the illuminating lamp of the intelligent driving device is maintained The intensity is unchanged.
在一种可能的实现方式中，本公开实施例中的智能驾驶设备为具有自动驾驶功能的车辆，或者为具有辅助驾驶功能的车辆。In a possible implementation manner, the intelligent driving device in the embodiment of the present disclosure is a vehicle with an automatic driving function, or a vehicle with a driving assistance function.
根据本公开的另一方面，提供了一种光强调节装置，包括：According to another aspect of the present disclosure, there is provided a light intensity adjusting device, including:
确定模块，用于根据智能驾驶设备采集到的图像，确定所述目标对象与所述智能驾驶设备之间的距离；A determining module, configured to determine the distance between the target object and the smart driving device according to the image collected by the smart driving device;
调节模块，用于根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。The adjustment module is used to adjust the luminous intensity of the illuminator of the intelligent driving device according to the distance between the intelligent driving device and the target object.
在一种可能的实现方式中，所述确定模块，用于根据所述图像，确定所述目标对象的位置；根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离。In a possible implementation manner, the determining module is configured to determine the position of the target object according to the image; and determine the distance between the target object and the intelligent driving device according to the position of the target object. the distance.
在一种可能的实现方式中，所述确定模块用于在根据所述图像确定所述目标对象的位置时，包括：In a possible implementation manner, when the determining module is configured to determine the position of the target object according to the image, the method includes:
根据所述图像，确定所述目标对象在所述图像中的图像坐标；基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置。According to the image, the image coordinates of the target object in the image are determined; and the position of the target object is determined based on the image coordinates of the target object in the image.
在一种可能的实现方式中，所述确定模块用于在基于所述目标对象在所述图像中的图像坐标确定所述目标对象的位置时，包括：In a possible implementation manner, when the determining module is configured to determine the position of the target object based on the image coordinates of the target object in the image, the method includes:
根据坐标变换关系，将所述目标对象的图像坐标转换为世界坐标系下的世界坐标；According to the coordinate transformation relationship, converting the image coordinates of the target object into world coordinates in the world coordinate system;
所述确定模块用于在根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离时，包括：根据所述目标对象的世界坐标以及所述智能驾驶设备的世界坐标，确定所述目标对象与所述智能驾驶设备之间的距离。The determining module is configured to determine the distance between the target object and the intelligent driving device according to the position of the target object, including: according to the world coordinates of the target object and the world of the intelligent driving device The coordinates determine the distance between the target object and the intelligent driving device.
在一种可能的实现方式中，所述确定模块还用于采用以下步骤确定所述坐标变换关系：In a possible implementation manner, the determining module is further configured to determine the coordinate transformation relationship by adopting the following steps:
获取标注图像；Obtain annotated images;
确定标注点在所述标注图像的图像坐标；Determining the image coordinates of the annotation point on the annotation image;
根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。According to the image coordinates of the marked points and the pre-marked world coordinates, the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
在一种可能的实现方式中，所述确定模块，用于根据所述图像，确定所述目标对象与所述智能驾驶设备之间的参考对象的数量；根据所述目标对象与所述智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定所述智能驾驶设备与所述目标对象之间的距离；其中，相邻的两个参考对象之间的间距是已知的。In a possible implementation manner, the determining module is configured to determine the number of reference objects between the target object and the intelligent driving device according to the image; according to the target object and the intelligent driving device The number of reference objects between the devices and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object; wherein the distance between two adjacent reference objects is Known.
在一种可能的实现方式中，所述目标对象为多个，所述调节模块，用于根据多个目标对象与所述智能驾驶设备之间的最小距离，调节所述智能驾驶设备的照明灯的发光强度。In a possible implementation manner, there are multiple target objects, and the adjustment module is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device. The luminous intensity.
在一种可能的实现方式中，所述调节模块，用于根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度；将所述智能驾驶设备的照明灯的发光强度调节至所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。In a possible implementation manner, the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. The target luminous intensity corresponding to the distance between the target objects; the luminous intensity of the illuminator of the smart driving device is adjusted to the target luminous intensity corresponding to the distance between the smart driving device and the target object.
在一种可能的实现方式中，所述调节模块用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：In a possible implementation manner, the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. When describing the target luminous intensity corresponding to the distance between target objects, it includes:
确定所述智能驾驶设备与所述目标对象之间的距离在目标距离与目标发光强度的对 应关系的列表中所属的第一距离区间；Determine the first distance interval to which the distance between the intelligent driving device and the target object belongs in the list of correspondences between the target distance and the target luminous intensity;
根据所述列表中所述第一距离区间对应的目标发光强度，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the target luminous intensity corresponding to the first distance interval in the list.
在一种可能的实现方式中，所述调节模块用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：In a possible implementation manner, the adjustment module is configured to determine the relationship between the smart driving device and the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. When describing the target luminous intensity corresponding to the distance between target objects, it includes:
根据所述智能驾驶设备与所述目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定所述智能驾驶设备与所述目标对象之间的距离所在的第二距离区间；所述第二距离区间为所述函数的一个距离区间；According to the distance between the intelligent driving device and the target object and a function that characterizes the correspondence between the target distance and the target luminous intensity, determine the second distance interval in which the distance between the intelligent driving device and the target object is located ; The second distance interval is a distance interval of the function;
根据所述函数中所述第二距离区间对应的目标距离与目标发光强度的计算方式，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function.
在一种可能的实现方式中，所述确定模块还用于在根据所述图像，确定所述图像中不存在目标对象；In a possible implementation manner, the determining module is further configured to determine, according to the image, that there is no target object in the image;
所述调节模块还用于将所述智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持所述智能驾驶设备的照明灯的发光强度不变。The adjustment module is also used to adjust the luminous intensity of the illuminating lamp of the smart driving device to a preset luminous intensity, or to keep the luminous intensity of the illuminating lamp of the smart driving device unchanged.
根据本公开的一方面，提供了一种电子设备，包括：According to an aspect of the present disclosure, there is provided an electronic device including:
处理器；processor;
用于存储处理器可执行指令的存储器；A memory for storing processor executable instructions;
其中，所述处理器被配置为：执行上述光强调节方法。Wherein, the processor is configured to execute the above light intensity adjustment method.
根据本公开的一方面，提供了一种计算机可读存储介质，其上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现上述光强调节方法。According to an aspect of the present disclosure, there is provided a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the above-mentioned light intensity adjustment method is realized.
根据本公开的一方面，提供了一种计算机程序，包括计算机可读代码，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现上述光强调节方法。According to an aspect of the present disclosure, there is provided a computer program, including computer readable code, when the computer readable code is run in an electronic device, a processor in the electronic device executes the light intensity adjustment method.
在本公开实施例中，可以根据智能驾驶设备采集到的图像，确定目标对象与智能驾驶设备与目标对象之间的距离，再根据智能驾驶设备与目标对象之间的距离，调节智能驾驶设备的照明灯的发光强度。这样，可以通过采集到的图像，确定行人、车辆等目标对象与智能驾驶设备之间的距离，并根据该距离远近自动调节智能驾驶设备的照明灯的发光强度，从而为车辆行驶提供便利，提高车辆行驶的安全性，减少交通事故的发生。In the embodiments of the present disclosure, the distance between the target object and the intelligent driving device and the target object can be determined based on the images collected by the intelligent driving device, and then the distance between the intelligent driving device and the target object can be adjusted according to the distance between the intelligent driving device and the target object. The luminous intensity of the light. In this way, the distance between pedestrians, vehicles, and other target objects and the intelligent driving device can be determined through the collected images, and the luminous intensity of the intelligent driving device's illuminating lamp can be automatically adjusted according to the distance, thereby providing convenience for vehicle driving and improving The safety of vehicle driving reduces the occurrence of traffic accidents.
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，而非限制本公开。It should be understood that the above general description and the following detailed description are only exemplary and explanatory, rather than limiting the present disclosure.
根据下面参考附图对示例性实施例的详细说明，本公开的其它特征及方面将变得清楚。According to the following detailed description of exemplary embodiments with reference to the accompanying drawings, other features and aspects of the present disclosure will become clear.
附图说明Description of the drawings
此处的附图被并入说明书中并构成本说明书的一部分，这些附图示出了符合本公开的实施例，并与说明书一起用于说明本公开的技术方案。The drawings here are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments that conform to the present disclosure, and are used together with the specification to explain the technical solutions of the present disclosure.
图1示出根据本公开实施例的光强调节方法的流程图。Fig. 1 shows a flowchart of a light intensity adjustment method according to an embodiment of the present disclosure.
图2示出根据本公开实施例的确定目标对象的图像坐标一示例的流程图。Fig. 2 shows a flowchart of an example of determining the image coordinates of a target object according to an embodiment of the present disclosure.
图3示出根据本公开实施例的利用神经网络进行目标检测一示例的框图。Fig. 3 shows a block diagram of an example of target detection using a neural network according to an embodiment of the present disclosure.
图4示出根据本公开实施例的光强调节装置的框图。Fig. 4 shows a block diagram of a light intensity adjusting device according to an embodiment of the present disclosure.
图5示出根据本公开实施例的一种电子设备示例的框图。Fig. 5 shows a block diagram of an example of an electronic device according to an embodiment of the present disclosure.
图6示出根据本公开实施例的一种电子设备示例的框图。Fig. 6 shows a block diagram of an example of an electronic device according to an embodiment of the present disclosure.
具体实施方式detailed description
以下将参考附图详细说明本公开的各种示例性实施例、特征和方面。附图中相同的附图标记表示功能相同或相似的元件。尽管在附图中示出了实施例的各种方面，但是除非特别指出，不必按比例绘制附图。Hereinafter, various exemplary embodiments, features, and aspects of the present disclosure will be described in detail with reference to the drawings. The same reference numerals in the drawings indicate elements with the same or similar functions. Although various aspects of the embodiments are shown in the drawings, unless otherwise noted, the drawings are not necessarily drawn to scale.
在这里专用的词“示例性”意为“用作例子、实施例或说明性”。这里作为“示例性”所说明的任何实施例不必解释为优于或好于其它实施例。The dedicated word "exemplary" here means "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" need not be construed as being superior or better than other embodiments.
本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中术语“至少一种”表示多种中的任意一种或多种中的至少两种的任意组合，例如，包括A、B、C中的至少一种，可以表示包括从A、B和C构成的集合中选择的任意一个或多个元素。The term "and/or" in this article is only an association relationship describing the associated objects, which means that there can be three relationships, for example, A and/or B, which can mean: A alone exists, A and B exist at the same time, exist alone B these three situations. In addition, the term "at least one" in this document means any one or any combination of at least two of the multiple, for example, including at least one of A, B, and C, may mean including A, Any one or more elements selected in the set formed by B and C.
另外，为了更好地说明本公开，在下文的具体实施方式中给出了众多的具体细节。本领域技术人员应当理解，没有某些具体细节，本公开同样可以实施。在一些实例中，对于本领域技术人员熟知的方法、手段、元件和电路未作详细描述，以便于凸显本公开的主旨。In addition, in order to better explain the present disclosure, numerous specific details are given in the following specific embodiments. Those skilled in the art should understand that the present disclosure can also be implemented without certain specific details. In some instances, the methods, means, elements, and circuits that are well known to those skilled in the art have not been described in detail in order to highlight the gist of the present disclosure.
本公开实施例提供的光强调节方案，可以根据智能驾驶设备采集到的图像，确定目标对象与智能驾驶设备与目标对象之间的距离，再根据智能驾驶设备与目标对象之间的距离，调节智能驾驶设备的照明灯的发光强度。这样，可以通过智能驾驶设备采集到的图像，确定智能驾驶设备与行人、车辆等目标对象的距离，然后根据该距离自动调节照明灯的发光强度，例如，在前方没有车辆或行人的情况下，可以将照明灯的发光强度调节到较强的状态，在前方存在车辆或行人的情况下，可以将照明灯的发光强度调节到较弱的状态，方便当前车车辆或前方车辆的安全驾驶，提高车辆行驶的安全性，减少交通事故的发生。并且，本公开实施例提供的光强调节方案，光强调节方式简单，应用灵活方便，无需部署其他相关设备，如，蓝牙设备、热点设备、红外设备等用于光强调节的相关设备，从而减少光强调节的成本。The light intensity adjustment solution provided by the embodiments of the present disclosure can determine the distance between the target object and the intelligent driving device and the target object according to the image collected by the intelligent driving device, and then adjust according to the distance between the intelligent driving device and the target object The luminous intensity of the lighting of the intelligent driving device. In this way, the distance between the smart driving device and the target object such as pedestrians and vehicles can be determined through the images collected by the smart driving device, and then the luminous intensity of the lighting lamp can be automatically adjusted according to the distance. For example, when there is no vehicle or pedestrian in front of it, The luminous intensity of the lights can be adjusted to a strong state. When there are vehicles or pedestrians ahead, the luminous intensity of the lights can be adjusted to a weaker state, which is convenient for the safe driving of the current vehicle or the vehicle in front, and improves The safety of vehicle driving reduces the occurrence of traffic accidents. In addition, the light intensity adjustment solution provided by the embodiments of the present disclosure has a simple light intensity adjustment method, flexible and convenient application, and does not need to deploy other related devices, such as Bluetooth devices, hotspot devices, infrared devices, and other related devices for light intensity adjustment, thereby Reduce the cost of light intensity adjustment.
在相关技术中，在光线较暗的环境中，如果车辆的灯光强度较强，例如在使用远光灯的情况下，由于远光灯的发光强度较大，会对行人或其他车辆的驾驶人员造成较大的影响，容易造成交通事故。本公开实施例提供的光强调节方案，可以通过智能驾驶设备采集到的图像确定智能驾驶设备与目标对象之间的距离，根据该距离自动调节照明灯的发光强度，提高车辆行驶过程中的安全，为交通行驶带来极大的便利。In the related art, in a low-light environment, if the light intensity of the vehicle is strong, for example, in the case of using high beams, due to the high luminous intensity of the high beams, it will be harmful to pedestrians or drivers of other vehicles. Cause greater impact and easily cause traffic accidents. The light intensity adjustment solution provided by the embodiments of the present disclosure can determine the distance between the smart driving device and the target object through the image collected by the smart driving device, and automatically adjust the luminous intensity of the lighting lamp according to the distance, thereby improving the safety of the vehicle during driving , Bring great convenience to traffic.
本公开实施例提供的光强调节调节方案可以应用在自动驾驶、辅助驾驶等应用场景。例如，在自动驾驶场景中，智能驾驶设备为具有自动驾驶功能的车辆，具有自动驾驶功 能的车辆可以在车辆行驶过程中根据其与目标对象之间的距离自动调节照明灯的发光强度；在辅助驾驶场景中，智能驾驶设备为具有辅助驾驶功能的车辆，具有辅助驾驶功能的车辆可以在车辆行驶的过程中根据其与目标对象之间的距离，确定车灯的目标光照强度，并提示驾驶员将车灯的光照强度调节至目标光照强度，进一步地，还可以在发出提示后的设定时间内检测到车灯的光照强度不是目标光照强度时，将车灯的光照强度调整为目标光照强度，为车辆行驶提供良好的照明条件。进一步地，在调整车灯的光照强度的过程中，还可以一定的调整速度调整光照强度，避免光线强弱变化过快，干扰驾驶员或者其他人员的视线。The light intensity adjustment solution provided by the embodiments of the present disclosure can be applied to application scenarios such as automatic driving and assisted driving. For example, in an autonomous driving scenario, the intelligent driving device is a vehicle with automatic driving function, and the vehicle with automatic driving function can automatically adjust the luminous intensity of the lighting lamp according to the distance between the vehicle and the target object during the driving process; In the driving scene, the intelligent driving device is a vehicle with assisted driving function. The vehicle with assisted driving function can determine the target light intensity of the lights according to the distance between the vehicle and the target object during the driving process, and prompt the driver Adjust the light intensity of the car lights to the target light intensity. Further, you can also adjust the light intensity of the car lights to the target light intensity when it is detected that the light intensity of the car lights is not the target light intensity within the set time after the prompt is issued , Provide good lighting conditions for vehicle driving. Further, in the process of adjusting the light intensity of the vehicle light, the light intensity can also be adjusted at a certain adjustment speed to avoid the light intensity changing too fast and disturbing the sight of the driver or other personnel.
下面通过实施例对本公开实施例提供的光强调节方案进行说明。The light intensity adjustment solution provided by the embodiments of the present disclosure will be described below through examples.
图1示出根据本公开实施例的光强调节方法的流程图。该光强调节方法可以由终端设备、服务器或其它信息处理设备执行，其中，终端设备可以为用户设备(User Equipment，UE)、移动设备、用户终端、终端、蜂窝电话、无绳电话、个人数字处理(Personal Digital Assistant，PDA)、手持设备、计算设备、智能驾驶设备、可穿戴设备等。在一些可能的实现方式中，该光强调节方法可以通过处理器调用存储器中存储的计算机可读指令的方式来实现。下面以智能驾驶设备作为执行主体为例对本公开实施例的光强调节方案进行说明。Fig. 1 shows a flowchart of a light intensity adjustment method according to an embodiment of the present disclosure. The light intensity adjustment method can be executed by a terminal device, a server, or other information processing equipment. The terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, or a personal digital processing device. (Personal Digital Assistant, PDA), handheld devices, computing devices, smart driving devices, wearable devices, etc. In some possible implementation manners, the light intensity adjustment method may be implemented by a processor invoking computer-readable instructions stored in a memory. The light intensity adjustment solution of the embodiment of the present disclosure will be described below by taking the intelligent driving device as the execution subject as an example.
如图1所示，所述光强调节方法包括以下步骤：As shown in Figure 1, the light intensity adjustment method includes the following steps:
步骤S11，根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离。Step S11: Determine the distance between the target object and the smart driving device according to the image collected by the smart driving device.
在本公开实施例中，智能驾驶设备可以是汽车，机器人等可以在路面上行驶，并且具有照明灯可以在光线不足的情况下照明的设备，智能驾驶设备可以配置图像采集设备，如摄像头等。智能驾驶设备可以实时采集当前场景的图像，然后针对采集的图像进行目标检测。根据对图像进行目标检测的检测结果，确定采集到的图像中是否存在目标对象。在确定图像中存在目标对象的情况下，可以通过目标对象在图像中的图像位置，确定目标对象与智能驾驶设备之间的距离，或者，可以通过目标对象与智能驾驶设备之间的参考对象的数量，也就是采集到的图像中沿着图像采集方向的位于目标对象与智能驾驶设备之间的参考对象的数量，确定目标对象与智能驾驶设备之间的距离。In the embodiments of the present disclosure, the smart driving device can be a car, a robot, etc., which can drive on the road, and has a device that can illuminate under the condition of insufficient light. The smart driving device can be equipped with an image collection device, such as a camera. Intelligent driving equipment can collect images of the current scene in real time, and then perform target detection on the collected images. According to the detection result of the target detection on the image, it is determined whether there is a target object in the collected image. When it is determined that the target object exists in the image, the distance between the target object and the intelligent driving device can be determined by the image position of the target object in the image, or the distance between the target object and the intelligent driving device can be determined by the reference object between the target object and the intelligent driving device. The number, that is, the number of reference objects located between the target object and the intelligent driving device along the image acquisition direction in the captured image, determines the distance between the target object and the intelligent driving device.
在对图像进行目标检测时，可以利用预先训练好的神经网络对图像进行图像特征提取，得目标对象在目标图像中的图像位置。或者，可以将目标图像与预存的图像模板进行匹配，判断该目标图像中是否存在目标对象的投影，如果存在目标对象的投影，则可以进一步确定目标对象在图像中的图像位置。然后由目标对象的图像位置，可以进一步确定目标对象在当前场景中的位置。目标对象在当前场景中的位置可以是精确的位置，例如，可以是世界坐标系下的世界坐标，或者，可以是一个大致的位置。目标对象可以是行人、机动车辆或非机动车辆等可以在交通道路中通行的对象。When performing target detection on an image, a pre-trained neural network can be used to perform image feature extraction on the image to obtain the image position of the target object in the target image. Alternatively, the target image can be matched with a pre-stored image template to determine whether there is a projection of the target object in the target image, and if there is a projection of the target object, the image position of the target object in the image can be further determined. Then from the image position of the target object, the position of the target object in the current scene can be further determined. The position of the target object in the current scene may be an accurate position, for example, it may be a world coordinate in a world coordinate system, or it may be a rough position. The target object can be a pedestrian, a motor vehicle or a non-motor vehicle that can pass on a traffic road.
在一个可能的实现方式中，在根据采集到的图像，确定图像中不存在目标对象时，可以将智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持智能驾驶设备的照明灯的发光强度不变。In a possible implementation, when it is determined that there is no target object in the image based on the collected image, the luminous intensity of the illuminator of the smart driving device can be adjusted to a preset luminous intensity, or the smart driving device's luminous intensity can be maintained. The luminous intensity of the lamp remains unchanged.
这里，如果在采集的图像中未检测到目标对象，可以将照明灯的发光强度调节为预设的发光强度，该预设的发光强度可以是较强的发光强度，从而在当前场景中不存在行人、车辆等目标对象的情况下，可以将照明灯调节为较强的发光强度，为智能驾驶设备提供良好的光照条件。或者，可以使照明灯的发光强度保持不变，使得智能驾驶设备保持当前的照明条件。Here, if the target object is not detected in the captured image, the luminous intensity of the lighting lamp can be adjusted to a preset luminous intensity, which can be a strong luminous intensity, so that it does not exist in the current scene In the case of pedestrians, vehicles and other target objects, the lighting can be adjusted to a strong luminous intensity to provide good lighting conditions for intelligent driving equipment. Or, the luminous intensity of the lighting lamp can be kept constant, so that the intelligent driving device maintains the current lighting conditions.
在一个可能的实现方式中，智能驾驶设备可以根据采集到的图像，确定目标对象的位置，然后根据目标对象的位置，确定目标对象和智能驾驶设备之间的距离。In a possible implementation, the intelligent driving device can determine the location of the target object based on the collected images, and then determine the distance between the target object and the intelligent driving device according to the location of the target object.
在该实现方式中，智能驾驶设备在检测到图像中存在目标对象的情况下，可以根据目标对象在图像中的图像位置，确定目标对象在世界坐标系下的位置。然后可以根据世界坐标系下目标对象的位置以及智能驾驶设备的当前位置，确定智能驾驶设备与目标对象之间的距离。In this implementation, the intelligent driving device can determine the position of the target object in the world coordinate system according to the image position of the target object in the image when it detects that the target object exists in the image. Then, the distance between the intelligent driving device and the target object can be determined according to the position of the target object in the world coordinate system and the current position of the intelligent driving device.
在目标对象为多个的情况下，可以在世界坐标系下根据每个目标对象的位置，确定每个目标对象与智能驾驶设备之间的距离。In the case of multiple target objects, the distance between each target object and the intelligent driving device can be determined according to the position of each target object in the world coordinate system.
在一个示例中，可以根据智能驾驶设备采集到的图像，确定目标对象在图像中的图像坐标，然后基于目标对象在图像中的图像坐标，确定目标对象的位置。In one example, the image coordinates of the target object in the image can be determined according to the images collected by the intelligent driving device, and then the position of the target object can be determined based on the image coordinates of the target object in the image.
在该示例中，目标对象在图像中的图像坐标可以理解为目标对象在目标图像的投影对应的图像坐标。通过对智能驾驶设备采集到的图像进行目标检测，可以确定目标对象在图像中的图像坐标。然后根据目标对象在图像中的图像坐标，可以确定目标对象在当前场景中的位置，该位置可以是在世界坐标系下的世界坐标。当前场景可以是光线较暗的环境中开启照明灯照明的场景，对采集的目标图像进行目标检测可以是在开启照明灯的情况下。目标对象在图像的图像坐标可以是目标对象在图像中投影的中心坐标或平均坐标，或者，可以是目标对象在图像中投影的任意一点的图像坐标。In this example, the image coordinates of the target object in the image can be understood as the image coordinates corresponding to the projection of the target object on the target image. By performing target detection on the image collected by the intelligent driving device, the image coordinates of the target object in the image can be determined. Then, according to the image coordinates of the target object in the image, the position of the target object in the current scene can be determined, and the position can be the world coordinates in the world coordinate system. The current scene may be a scene where the lighting lamp is turned on in a dark environment, and the target detection on the collected target image may be when the lighting lamp is turned on. The image coordinates of the target object in the image may be the center coordinates or average coordinates of the target object projected in the image, or may be the image coordinates of any point projected by the target object in the image.
在一个示例中，可以根据坐标变换关系，将目标对象的图像坐标转换为世界坐标系下的世界坐标，然后根据目标对象的世界坐标以及智能驾驶设备的世界坐标，确定目标对象与所述智能驾驶设备之间的距离。In one example, the image coordinates of the target object can be converted into world coordinates in the world coordinate system according to the coordinate transformation relationship, and then the target object and the intelligent driving device can be determined according to the world coordinates of the target object and the world coordinates of the intelligent driving device. The distance between devices.
这里，坐标变换关系可以是智能驾驶设备采集的目标图像的图像坐标转换为世界坐标的变换关系，通过坐标变换关系，可以将三维空间的空间点在图像中投影的图像坐标，转换为空间点的世界坐标。通过该坐标变换关系可以将目标对象的图像坐标转换为世界坐标系下的世界坐标，从而可以快速地确定目标对象的位置。智能驾驶设备可以获取导航***或者定位***检测的当前位置的世界坐标，从而可以利用智能驾驶设备在当前位置的世界坐标与确定的目标对象的世界坐标之间的差值，得到智能驾驶设备与目标对象之间的距离。通过这种方式，可以得到智能驾驶设备与目标对象之间较为准确的距离。Here, the coordinate transformation relationship may be the transformation relationship of the image coordinates of the target image collected by the intelligent driving device into the world coordinates. Through the coordinate transformation relationship, the image coordinates of the three-dimensional space points projected in the image can be converted into the spatial points. World coordinates. Through this coordinate transformation relationship, the image coordinates of the target object can be converted into world coordinates in the world coordinate system, so that the position of the target object can be quickly determined. The intelligent driving device can obtain the world coordinates of the current position detected by the navigation system or the positioning system, so that the difference between the world coordinates of the current position of the intelligent driving device and the determined world coordinates of the target object can be used to obtain the intelligent driving device and the target The distance between objects. In this way, a more accurate distance between the intelligent driving device and the target object can be obtained.
在一个示例中，可以获取标注图像，然后确定标注点在标注图像的图像坐标，再根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。In one example, the labeled image may be obtained, and then the image coordinates of the labeled point in the labeled image may be determined, and then the coordinate transformation relationship between the image coordinates and the world coordinates may be determined according to the image coordinates of the labeled point and the pre-labeled world coordinates.
在该示例中，标注图像可以是带有标注信息的采集图像。标注信息可以是标注图像中像素点所对应的空间点的世界坐标。根据多个空间点的图像坐标和标注信息中的世界 坐标，可以确定由图像坐标变换到世界坐标的坐标变换关系，该坐标变换关系可以通过变换矩阵进行表示。举例来说，可以根据一个标注图像中4个空间点的图像坐标和世界坐标，确定坐标变换关系。再例如，可以根据4个标注图像中每个标注图像的一空间点的图像坐标和世界坐标，确定坐标变换关系。通过这种方式，可以快速、准确地确定当前场景中图像坐标与世界坐标之间的坐标变换关系。In this example, the annotated image may be a collected image with annotated information. The annotation information may be the world coordinates of the spatial point corresponding to the pixel point in the annotation image. According to the image coordinates of multiple spatial points and the world coordinates in the label information, the coordinate transformation relationship from the image coordinates to the world coordinates can be determined, and the coordinate transformation relationship can be expressed by a transformation matrix. For example, the coordinate transformation relationship can be determined according to the image coordinates and world coordinates of four spatial points in an annotated image. For another example, the coordinate transformation relationship can be determined according to the image coordinates and world coordinates of a space point of each of the four annotated images. In this way, the coordinate transformation relationship between the image coordinates and the world coordinates in the current scene can be quickly and accurately determined.
在一种可能的实现方式中，可以根据智能驾驶设备采集到的图像，确定目标对象与智能驾驶设备之间的参考对象的数量，然后根据目标对象与智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定智能驾驶设备与目标对象之间的距离。这里，相邻的两个参考对象之间的间距是已知的。In a possible implementation manner, the number of reference objects between the target object and the intelligent driving device can be determined according to the images collected by the intelligent driving device, and then the number of reference objects between the target object and the intelligent driving device and the number of reference objects between the target object and the intelligent driving device can be determined according to the images collected by the intelligent driving device. The distance between adjacent reference objects determines the distance between the intelligent driving device and the target object. Here, the distance between two adjacent reference objects is known.
在该实现方式中，智能驾驶设备可以对智能驾驶设备采集到的图像进行识别，确定图像中识别出的目标对象以及参考对象。这里的参考对象可以是存在位置信息的标志性对象，例如，参考对象可以是路灯、垃圾箱、绿化的树木等。参考对象的位置信息可以是相邻参考对象之间的距离。然后可以统计图像中目标对象的前景中参考对象的数量，目标对象的前景中存在的参考对象的数量，可以认为是目标对象与智能驾驶设备之间存在的参考对象的数量，从而进一步可以根据目标对象与智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定智能驾驶设备与目标对象之间的距离。举例来说，假设根据采集到的图像，确定当前目标对象与智能驾驶设备之间路灯的数量是3个，如果相邻路灯之间的间距是10米，则可以确定目标对象与智能驾驶设备之间的距离大于或等于20米。In this implementation, the smart driving device can recognize the image collected by the smart driving device, and determine the target object and the reference object recognized in the image. The reference object here may be a landmark object with location information, for example, the reference object may be a street lamp, a trash can, a green tree, and so on. The position information of the reference object may be the distance between adjacent reference objects. Then the number of reference objects in the foreground of the target object in the image can be counted, and the number of reference objects existing in the foreground of the target object can be considered as the number of reference objects existing between the target object and the intelligent driving device. The number of reference objects between the object and the intelligent driving device and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object. For example, assuming that the number of street lights between the current target object and the intelligent driving device is 3 according to the collected images, if the distance between adjacent street lights is 10 meters, it can be determined that the target object and the intelligent driving device are The distance between them is greater than or equal to 20 meters.
在一个示例中，参考对象的位置信息可以是世界坐标，这种情况下，可以通过参考对象与目标对象之间的相对位置关系，例如，目标对象相对于参考对象远离智能驾驶设备，从而可以根据智能驾驶设备的世界坐标和参考对象的世界坐标，先确定智能驾驶设备和参考对象之间的距离，再根据智能驾驶设备和参考对象之间的距离估计目标对象与智能驾驶设备之间的距离，目标对象与智能驾驶设备之间的距离大于智能驾驶设备和参考对象之间的距离。In an example, the position information of the reference object may be world coordinates. In this case, the relative position relationship between the reference object and the target object can be used, for example, the target object is far away from the intelligent driving device relative to the reference object, so that the The world coordinates of the intelligent driving device and the world coordinates of the reference object are determined. The distance between the intelligent driving device and the reference object is first determined, and then the distance between the target object and the intelligent driving device is estimated based on the distance between the intelligent driving device and the reference object. The distance between the target object and the intelligent driving device is greater than the distance between the intelligent driving device and the reference object.
这里，智能驾驶设备可以无需配置其他测距设备，例如，无需配置红外设备、激光设备等测距设备，就可以确定目标对象与智能驾驶设备之间的目标距离，简单易行。此外，在一些实施方式中，智能驾驶设备可以对采集的目标图像进行复用，例如，在利用目标图像确定目标对象与智能驾驶设备的距离时，还可以利用目标图像判断智能驾驶设备是否偏离车道等其他操作。Here, the smart driving device can determine the target distance between the target object and the smart driving device without configuring other ranging devices, for example, without configuring infrared devices, laser devices and other ranging devices, which is simple and easy. In addition, in some embodiments, the smart driving device can multiplex the collected target image. For example, when the target image is used to determine the distance between the target object and the smart driving device, the target image can also be used to determine whether the smart driving device deviates from the lane. And other operations.
步骤S12，根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。Step S12: Adjust the luminous intensity of the lighting lamp of the intelligent driving device according to the distance between the intelligent driving device and the target object.
在本公开实施例中，智能驾驶设备可以根据智能驾驶设备与目标对象之间的距离，对照明灯的发光强度进行调节，例如，在智能驾驶设备与目标对象之间的距离大于预设阈值的情况下，可以使照明灯的发光强度保持不变，或者，将发光强度调节为第一发光强度，该第一发光强度可以是较强的发光强度，从而可以为智能驾驶设备提供良好的光照条件。在智能驾驶设备与目标对象之间的距离小于或等于预设阈值的情况下，可以使 照明灯的发光强度调节为第二发光强度，该第二发光强度可以是较弱的发光强度，从而可以减少对行人、车辆等目标对象的影响。In the embodiments of the present disclosure, the smart driving device can adjust the luminous intensity of the lighting lamp according to the distance between the smart driving device and the target object, for example, when the distance between the smart driving device and the target object is greater than a preset threshold Next, the luminous intensity of the lighting lamp can be kept unchanged, or the luminous intensity can be adjusted to the first luminous intensity, which can be a relatively strong luminous intensity, so as to provide good lighting conditions for the intelligent driving device. In the case that the distance between the smart driving device and the target object is less than or equal to the preset threshold, the luminous intensity of the illuminator can be adjusted to the second luminous intensity, and the second luminous intensity can be a weaker luminous intensity, so that Reduce the impact on pedestrians, vehicles and other target objects.
在一种可能的实现方式中，可以根据目标距离的对应关系以及智能驾驶设备与目标对象之间的距离，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度，然后将智能驾驶设备的照明灯的发光强度调节至目标发光强度。In a possible implementation manner, the target luminous intensity corresponding to the distance between the smart driving device and the target object can be determined according to the corresponding relationship between the target distance and the distance between the smart driving device and the target object, and then the smart driving device The luminous intensity of the lighting lamp is adjusted to the target luminous intensity.
在该实现方式中，智能驾驶设备可以获取预先存储的目标距离与目标发光强度的对应关系，然后根据该对应关系，查询确定的目标对象与智能驾驶设备之间的距离对应的目标发光强度。这里，目标距离与目标发光强度可以是一个分段函数，例如，在目标距离在小于第一距离时，目标发光强度可以是第一发光强度，在目标距离在大于或等于第一距离时，目标发光强度可以是第二发光强度，这样可以快速地通过目标距离与目标发光强度之间的对应关系，确定目标对象与智能驾驶设备之间的距离对应的目标发光强度。这里，目标距离与目标发光强度还可以是一个连续函数，这样可以实现根据目标对象与智能驾驶设备之间距离，使得智能驾驶设备的照明灯的发光强度连续变化。In this implementation manner, the intelligent driving device may obtain the pre-stored correspondence between the target distance and the target luminous intensity, and then query the determined target luminous intensity corresponding to the distance between the determined target object and the intelligent driving device according to the correspondence. Here, the target distance and the target luminous intensity may be a piecewise function. For example, when the target distance is less than the first distance, the target luminous intensity may be the first luminous intensity, and when the target distance is greater than or equal to the first distance, the target The luminous intensity may be the second luminous intensity, so that the target luminous intensity corresponding to the distance between the target object and the intelligent driving device can be quickly determined through the correspondence between the target distance and the target luminous intensity. Here, the target distance and the target luminous intensity may also be a continuous function, so that the luminous intensity of the illuminator of the smart driving device can be continuously changed according to the distance between the target object and the smart driving device.
这样，可以通过预先存储的目标距离与目标发光强度的对应关系，快速地确定当前智能驾驶设备的照明灯的目标发光强度，实现根据目标对象与智能驾驶设备之间的距离自动对照明灯进行调节，为车辆提供合适的光照环境，减少交通事故的发生。In this way, it is possible to quickly determine the current target luminous intensity of the lighting of the intelligent driving device through the pre-stored corresponding relationship between the target distance and the target luminous intensity, and realize the automatic adjustment of the lighting according to the distance between the target object and the intelligent driving device. Provide a suitable lighting environment for vehicles to reduce the occurrence of traffic accidents.
这里，目标距离与目标发光强度的对应关系，可以是通过大量的场景模拟得到的数据进行确定的。例如，在目标距离一定的情况下，确定行人或驾驶人员在该目标距离下可接受的发光强度，确定的可接受的发光强度可以作为该目标距离对应的目标发光强度。在一些实现方式中，在确定某个目标距离下行人或驾驶人员可接受的发光强度之后，还可以对可接受的发光强度进行调整，例如，将该可接受的发光强度减小一定的数值，将减小后得到的发光强度作为该目标距离对应的目标发光强度。这样，可以考虑不同的行人或驾驶人对灯光的敏感度不同，还可以考虑相向行驶过程中由于距离不断减小灯光对行人或驾驶人造成的影响，从而可以将目标距离对应的目标发光强度设置为小于行人或驾驶人员可接受的发光强度。Here, the corresponding relationship between the target distance and the target luminous intensity can be determined by data obtained from a large number of scene simulations. For example, in the case of a certain target distance, the acceptable luminous intensity for pedestrians or drivers at the target distance is determined, and the determined acceptable luminous intensity can be used as the target luminous intensity corresponding to the target distance. In some implementations, after determining the acceptable luminous intensity for pedestrians or drivers at a certain target distance, the acceptable luminous intensity can also be adjusted, for example, the acceptable luminous intensity can be reduced by a certain value, The reduced luminous intensity is used as the target luminous intensity corresponding to the target distance. In this way, it can be considered that different pedestrians or drivers have different sensitivity to lights, and the impact of lights on pedestrians or drivers due to the continuous reduction of distance during driving in opposite directions can be considered, so that the target luminous intensity corresponding to the target distance can be set It is less than the luminous intensity acceptable to pedestrians or drivers.
在该实现方式的一个示例中，可以确定智能驾驶设备与目标对象之间的距离在目标距离与目标发光强度的对应关系的列表所属的第一距离区间，然后根据列表中第一距离区间对应的目标发光强度，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度。在该示例中，目标距离与目标发光强度的对应关系，可以用列表进行表示。列表中可以记录多个距离区间以及每个距离区间对应的发光强度或者发光强度系数，从而可以根据智能驾驶设备与目标对象之间的距离所在的第一距离区间，查找第一距离区间对应的发光强度或者发光强度系数，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度。这里，在列表中记录的是距离区间与发光强度系数之间的对应关系的情况下，在通过第一距离区间得到对应的发光强度系数之后，可以将该发光强度系数乘以智能驾驶设备的最大发光强度，得到智能驾驶设备与目标对象之间的距离对应的目标发光强度。In an example of this implementation, it can be determined that the distance between the smart driving device and the target object is in the first distance interval to which the list of the correspondence between the target distance and the target luminous intensity belongs, and then the distance corresponding to the first distance interval in the list Target luminous intensity, to determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object. In this example, the corresponding relationship between the target distance and the target luminous intensity can be represented by a list. The list can record multiple distance intervals and the luminous intensity or luminous intensity coefficient corresponding to each distance interval, so that the luminous intensity corresponding to the first distance interval can be found according to the first distance interval where the distance between the intelligent driving device and the target object is located The intensity or luminous intensity coefficient determines the target luminous intensity corresponding to the distance between the intelligent driving device and the target object. Here, in the case where the correspondence between the distance interval and the luminous intensity coefficient is recorded in the list, after the corresponding luminous intensity coefficient is obtained through the first distance interval, the luminous intensity coefficient can be multiplied by the maximum value of the intelligent driving device. Luminous intensity, the target luminous intensity corresponding to the distance between the intelligent driving device and the target object is obtained.
举例来说，假设智能驾驶设备的照明灯的最大发光强度的发光强度系数1，照明灯不发光时的发光强度系数为0，如表1所示，照明灯的目标发光强度设置有6个档位，目标发 光强度系数分别是0、0.2、0.4、0.6、0.8和1，则可以通过表1示出的目标距离与目标发光强度的对应关系，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度。For example, suppose that the luminous intensity coefficient of the maximum luminous intensity of the intelligent driving equipment is 1, and the luminous intensity coefficient when the illuminator is not emitting light is 0. As shown in Table 1, the target luminous intensity of the illuminator is set to 6 levels The target luminous intensity coefficients are 0, 0.2, 0.4, 0.6, 0.8, and 1, respectively. The corresponding relationship between the target distance and the target luminous intensity shown in Table 1 can be used to determine the distance between the intelligent driving device and the target object. The target luminous intensity.
表1Table 1
目标距离(米)Target distance (m) 目标发光强度系数Target luminous intensity coefficient
0-200-20 0.20.2
20-4020-40 0.40.4
40-7040-70 0.60.6
70-12070-120 0.80.8
>120>120 11
在该实现方式的另一个示例中，可以根据智能驾驶设备与目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定智能驾驶设备与目标对象之间的距离所在的第二距离区间。然后根据函数中第二距离区间对应的目标距离与目标发光强度的计算方式，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度。这里，第二距离区间为函数的一个距离区间。该函数可以包括每个距离区间对应的发光强度或发光强度系数的计算方式，距离区间可以是多个，从而可以根据智能驾驶设备与目标对象之间的距离所在的第二距离区间，查找第二距离区间对应目标计算方式，利用目标计算方式计算智能驾驶设备与目标对象之间的距离对应的目标发光强度。In another example of this implementation, the distance between the smart driving device and the target object can be determined according to the distance between the smart driving device and the target object and the function that characterizes the corresponding relationship between the target distance and the target luminous intensity. Two distance interval. Then, according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function, the target luminous intensity corresponding to the distance between the intelligent driving device and the target object is determined. Here, the second distance interval is a distance interval of the function. This function can include the calculation method of the luminous intensity or luminous intensity coefficient corresponding to each distance interval. The distance interval can be multiple, so that the second distance interval can be found according to the second distance interval of the distance between the intelligent driving device and the target object. The distance interval corresponds to the target calculation method, and the target calculation method is used to calculate the target luminous intensity corresponding to the distance between the intelligent driving device and the target object.
举例来说，假设智能驾驶设备的照明灯的最大发光强度的目标发光强度系数1，照明灯不发光时的目标发光强度系数为0，目标距离与目标发光强度系数可以表示为线性函数，该线性函数如公式(1)所示：For example, suppose the target luminous intensity coefficient of the maximum luminous intensity of the intelligent driving equipment is 1, and the target luminous intensity coefficient when the illuminator is not luminous is 0. The target distance and the target luminous intensity coefficient can be expressed as a linear function. The function is shown in formula (1):
Figure PCTCN2020105260-appb-000001
Figure PCTCN2020105260-appb-000001
其中，y可以表示目标发光强度系数，x可以表示目标距离。通过公式(1)示出的目标距离与目标发光强度系数的计算方式，确定智能驾驶设备与目标对象之间的距离对应的目标发光强度。Among them, y can represent the target luminous intensity coefficient, and x can represent the target distance. The target luminous intensity corresponding to the distance between the intelligent driving device and the target object is determined by the calculation method of the target distance and the target luminous intensity coefficient shown in formula (1).
通过本公开实施例提供的光强调节方案，可以确定行人、车辆等目标对象与智能驾驶设备之间的距离，根据该距离自动调节照明灯的发光强度，从而可以为车辆行驶提供便利，提高车辆行驶的安全性，减少交通事故的发生。下面通过一示例对得到目标对象的图像坐标的过程进行说明。Through the light intensity adjustment scheme provided by the embodiments of the present disclosure, the distance between pedestrians, vehicles, and other target objects and the intelligent driving device can be determined, and the luminous intensity of the lighting lamp can be automatically adjusted according to the distance, so as to facilitate the driving of the vehicle and improve the vehicle. Driving safety reduces the occurrence of traffic accidents. The following describes the process of obtaining the image coordinates of the target object through an example.
图2示出根据本公开实施例的确定目标对象的图像坐标一示例的流程图，可以包括以下步骤：Fig. 2 shows a flowchart of an example of determining the image coordinates of a target object according to an embodiment of the present disclosure, which may include the following steps:
步骤S21，对采集的图像进行特征提取，得到图像的图像特征。Step S21: Perform feature extraction on the collected image to obtain image features of the image.
在该示例中，可以利用神经网络对采集的图像进行特征提取，得到图像的图像特征。这里，采集的图像可以作为神经网络的输入，利用神经网络对输入的图像进行卷积操作，得到图像的图像特征。或者，还可以先对采集的图像进行预处理，如，对图像进行放缩、裁剪、旋转等预处理，再将预处理后的图像输入神经网络，利用神经网络对预处理后的图像进行卷积操作，得到图像的图像特征，这样可以提高图像特征提取的效率和质量。In this example, a neural network can be used to perform feature extraction on the collected image to obtain the image feature of the image. Here, the collected image can be used as the input of the neural network, and the neural network is used to perform convolution operation on the input image to obtain the image characteristics of the image. Or, you can also preprocess the collected images first, such as preprocessing the image, such as zooming, cropping, and rotating, and then input the preprocessed image into the neural network, and use the neural network to roll the preprocessed image. Product operation to obtain the image features of the image, which can improve the efficiency and quality of image feature extraction.
步骤S22，根据图像的图像特征，确定图像中属于目标特征类的图像区域。Step S22: Determine an image area belonging to the target feature class in the image according to the image feature of the image.
在该示例中，可以根据神经网络提取的图像特征，确定图像中属于目标特征类的图像区域，该目标特征类可以表征每类目标对象的图像特征，举例来说，目标对象可以是行人的情况下，目标特征类可以是行人的图像特征形成的特征类。这里，目标对象可以包括行人、非机动车和机动车中的一个或多个，相应地，目标特征类可以包括行人特征类、非机动车特征类以及机动车特征类中的一个或多个特征类。In this example, the image area belonging to the target feature class in the image can be determined based on the image features extracted by the neural network. The target feature class can represent the image features of each type of target object. For example, the target object can be a pedestrian. Below, the target feature class can be a feature class formed by the image features of pedestrians. Here, the target object may include one or more of pedestrians, non-motorized vehicles, and motor vehicles. Correspondingly, the target feature class may include one or more of the pedestrian feature class, the non-motorized vehicle feature class, and the motor vehicle feature class. class.
在目标特征类为多个的情况下，可以利用每个目标特征类的分支网络对所述目标图像的图像特征进行卷积操作，得到对于每个目标特征类的图像区域的检测结果，然后根据对于多个目标特征类的图像区域的检测结果，确定所述目标图像中属于多个目标特征类的至少一个图像区域。In the case of multiple target feature classes, the branch network of each target feature class can be used to perform convolution operations on the image features of the target image to obtain the detection result of the image area of each target feature class, and then according to For the detection results of the image regions of the multiple target feature classes, determine at least one image region belonging to the multiple target feature classes in the target image.
这里，神经网络可以包括多个分支网络，每个分支网络可以并行对图像的图像特征进行卷积操作，得到针对每个目标特征类的图像区域进行检测的检测结果，该检测结果可以是每个目标特征类的目标对象所在的图像区域。然后可以结合每个分支网络得到的检测结果，得到属于多个目标特征类的至少一个图像区域。Here, the neural network may include multiple branch networks, and each branch network can perform convolution operations on the image features of the image in parallel to obtain the detection results for the image regions of each target feature class. The detection results can be each The image area where the target object of the target feature class is located. Then, the detection results obtained by each branch network can be combined to obtain at least one image area belonging to multiple target feature classes.
图3示出根据本公开实施例的利用神经网络进行目标检测一示例的框图。Fig. 3 shows a block diagram of an example of target detection using a neural network according to an embodiment of the present disclosure.
举例来说，上述神经网络可以包括三个分支网络，第一个分支网络可以对应行人特征类，从而可以利用第一个分支网络针对行人特征类的图像区域进行检测，在检测到目标图像中存在行人的情况下，可以标识出行人的图像区域，例如，使用方框标识行人所在的图像区域，该方框标识的图像区域可以是对于行人特征类的图像区域的检测结果。类似地，第二个分支网络可以对应非机动车特征类，可以利用第二个分支网络得到针对非机动车特征类的图像区域检测结果。第三个分支网络可以对应机动车特征类，可以利用第三个分支网络得到针对机动车特征类的图像区域检测结果。然后可以结合每个或至少一个分支网络得到的检测结果，最终得到利用方框标识的行人、机动车以及非机动车所在的图像区域。For example, the above-mentioned neural network may include three branch networks, the first branch network can correspond to the pedestrian feature class, so that the first branch network can be used to detect the image area of the pedestrian feature class, and the presence of the target image is detected In the case of a pedestrian, the image area of the pedestrian can be identified. For example, a box is used to identify the image area where the pedestrian is located, and the image area identified by the box may be the detection result of the image area of the pedestrian characteristic. Similarly, the second branch network can correspond to the non-motor vehicle feature class, and the second branch network can be used to obtain the image area detection result for the non-motor vehicle feature class. The third branch network can correspond to motor vehicle feature classes, and the third branch network can be used to obtain image area detection results for motor vehicle feature classes. Then, the detection results obtained by each or at least one branch network can be combined to finally obtain the image areas where the pedestrians, motor vehicles, and non-motor vehicles are identified by the box.
步骤S23，根据图像中属于目标特征类的图像区域，确定图像中目标对象的图像坐标。Step S23: Determine the image coordinates of the target object in the image according to the image area belonging to the target feature class in the image.
在该示例中，可以根据图像中属于目标特征类的图像区域的图像坐标，确定该图像区域的区域中心的图像坐标，将区域中心的图像坐标可以确定为目标对象的图像坐标。或者，可以在图像区域中选择任意一个像素点，确定该像素点的图像坐标，将该像素点的图像坐标确定为目标对象的图像坐标。或者，可以计算该图像区域中像素点的平均图像坐标，将平均图像坐标确定为目标对象的图像坐标。In this example, the image coordinates of the area center of the image area can be determined according to the image coordinates of the image area belonging to the target feature class in the image, and the image coordinates of the area center can be determined as the image coordinates of the target object. Or, you can select any pixel in the image area, determine the image coordinates of the pixel, and determine the image coordinates of the pixel as the image coordinates of the target object. Alternatively, the average image coordinates of the pixels in the image area can be calculated, and the average image coordinates can be determined as the image coordinates of the target object.
需要说明的是，本公开实施例不对上述神经网络的网络结构进行限制，可以是任意的具有目标检测功能的神经网络，例如，faster RCNN、SSD、YOLO等网络结构的神经网络。此外，对于神经网络的网络层数和尺寸均没有特殊的限制，从而使本公开实施例提供的光强调节方案具有较高的实用性，可以使用在任何需要对灯光的发光强度进行调节的场景。It should be noted that the embodiments of the present disclosure do not limit the network structure of the foregoing neural network, and may be any neural network with a target detection function, for example, a neural network with a network structure such as faster RCNN, SSD, YOLO, etc. In addition, there are no special restrictions on the number and size of the neural network, so that the light intensity adjustment scheme provided by the embodiments of the present disclosure has high practicability, and can be used in any scene where the luminous intensity of the light needs to be adjusted. .
可以理解，本公开提及的上述各个方法实施例，在不违背原理逻辑的情况下，均可以彼此相互结合形成结合后的实施例，限于篇幅，本公开不再赘述。本领域技术人员可 以理解，在具体实施方式的上述方法中，各步骤的具体执行顺序应当以其功能和可能的内在逻辑确定。It can be understood that the various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle and logic. The length is limited, and the details of this disclosure will not be repeated. Those skilled in the art can understand that, in the above method of the specific implementation, the specific execution order of each step should be determined by its function and possible internal logic.
此外，本公开还提供了光强调节装置、电子设备、计算机可读存储介质、程序，上述均可用来实现本公开提供的任一种光强调节方法，相应技术方案和描述和参见方法部分的相应记载，不再赘述。In addition, the present disclosure also provides light intensity adjustment devices, electronic equipment, computer-readable storage media, and programs, all of which can be used to implement any light intensity adjustment method provided in the present disclosure. For the corresponding technical solutions and descriptions, refer to the method section. The corresponding records will not be repeated here.
本领域技术人员可以理解，在具体实施方式的上述方法中，各步骤的撰写顺序并不意味着严格的执行顺序而对实施过程构成任何限定，各步骤的具体执行顺序应当以其功能和可能的内在逻辑确定。Those skilled in the art can understand that in the above-mentioned methods of the specific implementation, the writing order of the steps does not mean a strict execution order but constitutes any limitation on the implementation process. The specific execution order of each step should be based on its function and possibility. The inner logic is determined.
图4示出根据本公开实施例的光强调节装置的框图，如图4所示，所述光强调节装置包括：Fig. 4 shows a block diagram of a light intensity adjustment device according to an embodiment of the present disclosure. As shown in Fig. 4, the light intensity adjustment device includes:
确定模块41，用于根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离；The determining module 41 is configured to determine the distance between the target object and the smart driving device according to the image collected by the smart driving device;
调节模块42，用于根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。The adjustment module 42 is configured to adjust the luminous intensity of the lighting lamp of the intelligent driving device according to the distance between the intelligent driving device and the target object.
在一种可能的实现方式中，所述确定模块41，用于根据所述图像，确定所述目标对象的位置；根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离。In a possible implementation manner, the determining module 41 is configured to determine the position of the target object according to the image; determine the position of the target object and the intelligent driving device according to the position of the target object The distance between.
在一种可能的实现方式中，所述确定模块41用于在根据所述图像确定所述目标对象的位置时，包括：In a possible implementation manner, the determining module 41 is configured to determine the position of the target object according to the image, including:
根据所述图像，确定所述目标对象在所述图像中的图像坐标；基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置。According to the image, the image coordinates of the target object in the image are determined; and the position of the target object is determined based on the image coordinates of the target object in the image.
在一种可能的实现方式中，所述确定模块41用于在基于所述目标对象在所述图像中的图像坐标确定所述目标对象的位置时，包括：In a possible implementation manner, the determining module 41 is configured to determine the position of the target object based on the image coordinates of the target object in the image, including:
根据坐标变换关系，将所述目标对象的图像坐标转换为世界坐标系下的世界坐标；According to the coordinate transformation relationship, converting the image coordinates of the target object into world coordinates in the world coordinate system;
所述确定模块41用于在根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离时，包括：根据所述目标对象的世界坐标以及所述智能驾驶设备的世界坐标，确定所述目标对象与所述智能驾驶设备之间的距离。The determining module 41 is configured to determine the distance between the target object and the intelligent driving device according to the position of the target object, including: according to the world coordinates of the target object and the intelligent driving device The world coordinates determine the distance between the target object and the intelligent driving device.
在一种可能的实现方式中，所述确定模块41还用于采用以下步骤确定所述坐标变换关系：In a possible implementation manner, the determining module 41 is further configured to determine the coordinate transformation relationship by adopting the following steps:
获取标注图像；Obtain annotated images;
确定标注点在所述标注图像的图像坐标；Determining the image coordinates of the annotation point on the annotation image;
根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。According to the image coordinates of the marked points and the pre-marked world coordinates, the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
在一种可能的实现方式中，所述确定模块41，用于根据所述图像，确定所述目标对象与所述智能驾驶设备之间的参考对象的数量；根据所述目标对象与所述智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定所述智能驾驶设备与所述目标对象之间的距离；其中，相邻的两个参考对象之间的间距是已知的。In a possible implementation, the determining module 41 is configured to determine the number of reference objects between the target object and the intelligent driving device according to the image; according to the target object and the intelligent driving device The number of reference objects between driving devices and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object; wherein the distance between two adjacent reference objects is known.
在一种可能的实现方式中，所述目标对象为多个，所述调节模块42，用于根据多个目标对象与所述智能驾驶设备之间的最小距离，调节所述智能驾驶设备的照明灯的发光强度。In a possible implementation manner, there are multiple target objects, and the adjustment module 42 is configured to adjust the lighting of the intelligent driving device according to the minimum distance between the multiple target objects and the intelligent driving device. The luminous intensity of the lamp.
在一种可能的实现方式中，所述调节模块42，用于根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度；将所述智能驾驶设备的照明灯的发光强度调节至所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。In a possible implementation, the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. Target luminous intensity corresponding to the distance between the target objects; adjusting the luminous intensity of the illuminator of the smart driving device to the target luminous intensity corresponding to the distance between the smart driving device and the target object.
在一种可能的实现方式中，所述调节模块42用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：In a possible implementation, the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. The target luminous intensity corresponding to the distance between the target objects includes:
确定所述智能驾驶设备与所述目标对象之间的距离在目标距离与目标发光强度的对应关系的列表中所属的第一距离区间；Determine the first distance interval to which the distance between the intelligent driving device and the target object belongs in the list of correspondences between the target distance and the target luminous intensity;
根据所述列表中所述第一距离区间对应的目标发光强度，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the target luminous intensity corresponding to the first distance interval in the list.
在一种可能的实现方式中，所述调节模块42用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：In a possible implementation, the adjustment module 42 is configured to determine whether the smart driving device is connected to the target object according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. The target luminous intensity corresponding to the distance between the target objects includes:
根据所述智能驾驶设备与所述目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定所述智能驾驶设备与所述目标对象之间的距离所在的第二距离区间；所述第二距离区间为所述函数的一个距离区间；According to the distance between the intelligent driving device and the target object and a function that characterizes the correspondence between the target distance and the target luminous intensity, determine the second distance interval in which the distance between the intelligent driving device and the target object is located ; The second distance interval is a distance interval of the function;
根据所述函数中所述第二距离区间对应的目标距离与目标发光强度的计算方式，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function.
在一种可能的实现方式中，所述调节模块42还用于在根据所述图像，确定所述图像中不存在目标对象时，将所述智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持所述智能驾驶设备的照明灯的发光强度不变。In a possible implementation manner, the adjustment module 42 is further configured to adjust the luminous intensity of the illuminator of the intelligent driving device to a preset value when it is determined that there is no target object in the image according to the image. Or, keep the luminous intensity of the illuminating lamp of the intelligent driving device unchanged.
在一些实施例中，本公开实施例中的智能驾驶设备为具有自动驾驶功能的车辆，或者为具有辅助驾驶功能的车辆。In some embodiments, the intelligent driving device in the embodiments of the present disclosure is a vehicle with an automatic driving function, or a vehicle with a driving assistance function.
在一些实施例中，本公开实施例提供的装置具有的功能或包含的模块可以用于执行上文方法实施例描述的方法，其具体实现可以参照上文方法实施例的描述，为了简洁，这里不再赘述。In some embodiments, the functions or modules contained in the device provided in the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments. For specific implementation, refer to the description of the above method embodiments. For brevity, here No longer.
本公开实施例还提出一种计算机可读存储介质，其上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现上述方法。计算机可读存储介质可以是非易失性计算机可读存储介质或易失性计算机可读存储介质。The embodiments of the present disclosure also provide a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above-mentioned method when executed by a processor. The computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium.
本公开实施例还提出一种电子设备，包括：处理器；用于存储处理器可执行指令的存储器；其中，所述处理器被配置为上述方法。An embodiment of the present disclosure also provides an electronic device, including: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured as the above method.
本公开实施例还提出一种计算机程序，包括计算机可读代码，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现上述方法。The embodiment of the present disclosure also proposes a computer program, including computer readable code, when the computer readable code is executed in an electronic device, the processor in the electronic device executes to implement the above method.
可以理解，在不违背逻辑的情况下，本公开提供的不同实现方式之间可以相互结合。It can be understood that, without violating logic, the different implementation manners provided in the present disclosure can be combined with each other.
电子设备可以被提供为终端、服务器或其它形态的设备。The electronic device can be provided as a terminal, server or other form of device.
图5是根据一示例性实施例示出的一种电子设备800的框图。例如，电子设备800可以是移动电话，计算机，数字广播终端，消息收发设备，游戏控制台，平板设备，医疗设备，健身设备，个人数字助理等终端。Fig. 5 is a block diagram showing an electronic device 800 according to an exemplary embodiment. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcasting terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, and other terminals.
参照图5，电子设备800可以包括以下一个或多个组件：处理组件802，存储器804，电源组件806，多媒体组件808，音频组件810，输入/输出(I/O)的接口812，传感器组件814，以及通信组件816。5, the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, and a sensor component 814 , And communication component 816.
处理组件802通常控制电子设备800的整体操作，诸如与显示，电话呼叫，数据通信，相机操作和记录操作相关联的操作。处理组件802可以包括一个或多个处理器820来执行指令，以完成上述的方法的全部或部分步骤。此外，处理组件802可以包括一个或多个模块，便于处理组件802和其他组件之间的交互。例如，处理组件802可以包括多媒体模块，以方便多媒体组件808和处理组件802之间的交互。The processing component 802 generally controls the overall operations of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the foregoing method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.
存储器804被配置为存储各种类型的数据以支持在电子设备800的操作。这些数据的示例包括用于在电子设备800上操作的任何应用程序或方法的指令，联系人数据，电话簿数据，消息，图片，视频等。存储器804可以由任何类型的易失性或非易失性存储设备或者它们的组合实现，如静态随机存取存储器(SRAM)，电可擦除可编程只读存储器(EEPROM)，可擦除可编程只读存储器(EPROM)，可编程只读存储器(PROM)，只读存储器(ROM)，磁存储器，快闪存储器，磁盘或光盘。The memory 804 is configured to store various types of data to support operations in the electronic device 800. Examples of these data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable and Programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.
电源组件806为电子设备800的各种组件提供电力。电源组件806可以包括电源管理***，一个或多个电源，及其他与为电子设备800生成、管理和分配电力相关联的组件。The power supply component 806 provides power for various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
多媒体组件808包括在所述电子设备800和用户之间的提供一个输出接口的屏幕。在一些实施例中，屏幕可以包括液晶显示器(LCD)和触摸面板(TP)。如果屏幕包括触摸面板，屏幕可以被实现为触摸屏，以接收来自用户的输入信号。触摸面板包括一个或多个触摸传感器以感测触摸、滑动和触摸面板上的手势。所述触摸传感器可以不仅感测触摸或滑动动作的边界，而且还检测与所述触摸或滑动操作相关的持续时间和压力。在一些实施例中，多媒体组件808包括一个前置摄像头和/或后置摄像头。当电子设备800处于操作模式，如拍摄模式或视频模式时，前置摄像头和/或后置摄像头可以接收外部的多媒体数据。每个前置摄像头和后置摄像头可以是一个固定的光学透镜***或具有焦距和光学变焦能力。The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, sliding, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure related to the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.
音频组件810被配置为输出和/或输入音频信号。例如，音频组件810包括一个麦克风(MIC)，当电子设备800处于操作模式，如呼叫模式、记录模式和语音识别模式时，麦克风被配置为接收外部音频信号。所接收的音频信号可以被进一步存储在存储器804或经由通信组件816发送。在一些实施例中，音频组件810还包括一个扬声器，用于输出音频信号。The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.
I/O接口812为处理组件802和***接口模块之间提供接口，上述***接口模块可以是键盘，点击轮，按钮等。这些按钮可包括但不限于：主页按钮、音量按钮、启动按钮和 锁定按钮。The I/O interface 812 provides an interface between the processing component 802 and a peripheral interface module. The peripheral interface module may be a keyboard, a click wheel, a button, and the like. These buttons may include, but are not limited to: home button, volume button, start button, and lock button.
传感器组件814包括一个或多个传感器，用于为电子设备800提供各个方面的状态评估。例如，传感器组件814可以检测到电子设备800的打开/关闭状态，组件的相对光强调节，例如所述组件为电子设备800的显示器和小键盘，传感器组件814还可以检测电子设备800或电子设备800一个组件的位置改变，用户与电子设备800接触的存在或不存在，电子设备800方位或加速/减速和电子设备800的温度变化。传感器组件814可以包括接近传感器，被配置用来在没有任何的物理接触时检测附近物体的存在。传感器组件814还可以包括光传感器，如互补金属氧化物半导体(CMOS)或电荷耦合装置(CCD)图像传感器，用于在成像应用中使用。在一些实施例中，该传感器组件814还可以包括加速度传感器，陀螺仪传感器，磁传感器，压力传感器或温度传感器。The sensor component 814 includes one or more sensors for providing the electronic device 800 with various aspects of state evaluation. For example, the sensor component 814 can detect the on/off state of the electronic device 800 and adjust the relative light intensity of the component. For example, the component is the display and the keypad of the electronic device 800, and the sensor component 814 can also detect the electronic device 800 or the electronic device. The position of a component 800 changes, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration/deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor component 814 may include a proximity sensor configured to detect the presence of nearby objects when there is no physical contact. The sensor component 814 may also include a light sensor, such as a complementary metal oxide semiconductor (CMOS) or charge coupled device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor component 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
通信组件816被配置为便于电子设备800和其他设备之间有线或无线方式的通信。电子设备800可以接入基于通信标准的无线网络，如无线网络(WiFi)，第二代移动通信技术(2G)或第三代移动通信技术(3G)，或它们的组合。在一个示例性实施例中，通信组件816经由广播信道接收来自外部广播管理***的广播信号或广播相关信息。在一个示例性实施例中，所述通信组件816还包括近场通信(NFC)模块，以促进短程通信。例如，在NFC模块可基于射频识别(RFID)技术，红外数据协会(IrDA)技术，超宽带(UWB)技术，蓝牙(BT)技术和其他技术来实现。The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as a wireless network (WiFi), a second-generation mobile communication technology (2G) or a third-generation mobile communication technology (3G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.
在示例性实施例中，电子设备800可以被一个或多个应用专用集成电路(ASIC)、数字信号处理器(DSP)、数字信号处理设备(DSPD)、可编程逻辑器件(PLD)、现场可编程门阵列(FPGA)、控制器、微控制器、微处理器或其他电子元件实现，用于执行上述方法。In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field-available A programmable gate array (FPGA), controller, microcontroller, microprocessor, or other electronic components are implemented to implement the above methods.
在示例性实施例中，还提供了一种非易失性计算机可读存储介质或易失性计算机可读存储介质，例如包括计算机程序指令的存储器804，上述计算机程序指令可由电子设备800的处理器820执行以完成上述方法。In an exemplary embodiment, a non-volatile computer-readable storage medium or a volatile computer-readable storage medium is also provided, such as the memory 804 including computer program instructions, which can be processed by the electronic device 800. The device 820 executes to complete the above-mentioned method.
图6是根据一示例性实施例示出的一种电子设备1900的框图。例如，电子设备1900可以被提供为一服务器。参照图6，电子设备1900包括处理组件1922，其进一步包括一个或多个处理器，以及由存储器1932所代表的存储器资源，用于存储可由处理组件1922的执行的指令，例如应用程序。存储器1932中存储的应用程序可以包括一个或一个以上的每一个对应于一组指令的模块。此外，处理组件1922被配置为执行指令，以执行上述方法。Fig. 6 is a block diagram showing an electronic device 1900 according to an exemplary embodiment. For example, the electronic device 1900 may be provided as a server. 6, the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by the memory 1932, for storing instructions executable by the processing component 1922, such as application programs. The application program stored in the memory 1932 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above-described methods.
电子设备1900还可以包括一个电源组件1926被配置为执行电子设备1900的电源管理，一个有线或无线网络接口1950被配置为将电子设备1900连接到网络，和一个输入输出(I/O)接口1958。电子设备1900可以操作基于存储在存储器1932的操作***，例如微软服务器操作***(Windows Server TM)，苹果公司推出的基于图形用户界面操作***(Mac OS X TM)，多用户多进程的计算机操作***(Unix TM)，自由和开放原代码的类Unix操作***(Linux TM)，开放原代码的类Unix操作***(FreeBSD TM)或类似。 The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input output (I/O) interface 1958 . The electronic device 1900 can operate based on an operating system stored in the memory 1932, such as a Microsoft server operating system (Windows Server TM ), a graphical user interface operating system (Mac OS X TM ) launched by Apple, and a multi-user and multi-process computer operating system (Unix TM ), free and open source Unix-like operating system (Linux TM ), open source Unix-like operating system (FreeBSD TM ) or similar.
在示例性实施例中，还提供了一种非易失性计算机可读存储介质或易失性计算机可读存储介质，例如包括计算机程序指令的存储器1932，上述计算机程序指令可由电子设 备1900的处理组件1922执行以完成上述方法。In an exemplary embodiment, a non-volatile computer-readable storage medium or a volatile computer-readable storage medium is also provided, such as the memory 1932 including computer program instructions, which can be processed by the electronic device 1900. The component 1922 executes to complete the above method.
本公开可以是***、方法和/或计算机程序产品。计算机程序产品可以包括计算机可读存储介质，其上载有用于使处理器实现本公开的各个方面的计算机可读程序指令。The present disclosure may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium loaded with computer-readable program instructions for enabling a processor to implement various aspects of the present disclosure.
计算机可读存储介质可以是可以保持和存储由指令执行设备使用的指令的有形设备。计算机可读存储介质例如可以是――但不限于――电存储设备、磁存储设备、光存储设备、电磁存储设备、半导体存储设备或者上述的任意合适的组合。计算机可读存储介质的更具体的例子(非穷举的列表)包括：便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、静态随机存取存储器(SRAM)、便携式压缩盘只读存储器(CD-ROM)、数字多功能盘(DVD)、记忆棒、软盘、机械编码设备、例如其上存储有指令的打孔卡或凹槽内凸起结构、以及上述的任意合适的组合。这里所使用的计算机可读存储介质不被解释为瞬时信号本身，诸如无线电波或者其他自由传播的电磁波、通过波导或其他传输媒介传播的电磁波(例如，通过光纤电缆的光脉冲)、或者通过电线传输的电信号。The computer-readable storage medium may be a tangible device that can hold and store instructions used by the instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) Or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as a printer with instructions stored thereon The protruding structure in the hole card or the groove, and any suitable combination of the above. The computer-readable storage medium used here is not interpreted as the instantaneous signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (for example, light pulses through fiber optic cables), or through wires Transmission of electrical signals.
这里所描述的计算机可读程序指令可以从计算机可读存储介质下载到各个计算/处理设备，或者通过网络、例如因特网、局域网、广域网和/或无线网下载到外部计算机或外部存储设备。网络可以包括铜传输电缆、光纤传输、无线传输、路由器、防火墙、交换机、网关计算机和/或边缘服务器。每个计算/处理设备中的网络适配卡或者网络接口从网络接收计算机可读程序指令，并转发该计算机可读程序指令，以供存储在各个计算/处理设备中的计算机可读存储介质中。The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to various computing/processing devices, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network, and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing/processing device .
用于执行本公开操作的计算机程序指令可以是汇编指令、指令集架构(ISA)指令、机器指令、机器相关指令、微代码、固件指令、状态设置数据、或者以一种或多种编程语言的任意组合编写的源代码或目标代码，所述编程语言包括面向对象的编程语言—诸如Smalltalk、C++等，以及常规的过程式编程语言—诸如“C”语言或类似的编程语言。计算机可读程序指令可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络—包括局域网(LAN)或广域网(WAN)—连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。在一些实施例中，通过利用计算机可读程序指令的状态信息来个性化定制电子电路，例如可编程逻辑电路、现场可编程门阵列(FPGA)或可编程逻辑阵列(PLA)，该电子电路可以执行计算机可读程序指令，从而实现本公开的各个方面。The computer program instructions used to perform the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or in one or more programming languages. Source code or object code written in any combination, the programming language includes object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as "C" language or similar programming languages. Computer-readable program instructions can be executed entirely on the user's computer, partly on the user's computer, executed as a stand-alone software package, partly on the user's computer and partly executed on a remote computer, or entirely on the remote computer or server carried out. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network-including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect to the user's computer) connection). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), can be customized by using the status information of the computer-readable program instructions. The computer-readable program instructions are executed to realize various aspects of the present disclosure.
这里参照根据本公开实施例的方法、装置(***)和计算机程序产品的流程图和/或框图描述了本公开的各个方面。应当理解，流程图和/或框图的每个方框以及流程图和/或框图中各方框的组合，都可以由计算机可读程序指令实现。Various aspects of the present disclosure are described herein with reference to flowcharts and/or block diagrams of methods, apparatuses (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each block of the flowcharts and/or block diagrams, and combinations of blocks in the flowcharts and/or block diagrams, can be implemented by computer-readable program instructions.
这些计算机可读程序指令可以提供给通用计算机、专用计算机或其它可编程数据处理装置的处理器，从而生产出一种机器，使得这些指令在通过计算机或其它可编程数据处理装置的处理器执行时，产生了实现流程图和/或框图中的一个或多个方框中规定的功 能/动作的装置。也可以把这些计算机可读程序指令存储在计算机可读存储介质中，这些指令使得计算机、可编程数据处理装置和/或其他设备以特定方式工作，从而，存储有指令的计算机可读介质则包括一个制造品，其包括实现流程图和/或框图中的一个或多个方框中规定的功能/动作的各个方面的指令。These computer-readable program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine that makes these instructions when executed by the processor of the computer or other programmable data processing device , A device that implements the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams is produced. It is also possible to store these computer-readable program instructions in a computer-readable storage medium. These instructions make computers, programmable data processing apparatuses, and/or other devices work in a specific manner. Thus, the computer-readable medium storing the instructions includes An article of manufacture, which includes instructions for implementing various aspects of the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.
也可以把计算机可读程序指令加载到计算机、其它可编程数据处理装置、或其它设备上，使得在计算机、其它可编程数据处理装置或其它设备上执行一系列操作步骤，以产生计算机实现的过程，从而使得在计算机、其它可编程数据处理装置、或其它设备上执行的指令实现流程图和/或框图中的一个或多个方框中规定的功能/动作。It is also possible to load computer-readable program instructions on a computer, other programmable data processing device, or other equipment, so that a series of operation steps are executed on the computer, other programmable data processing device, or other equipment to produce a computer-implemented process , So that the instructions executed on the computer, other programmable data processing apparatus, or other equipment realize the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.
附图中的流程图和框图显示了根据本公开的多个实施例的***、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或指令的一部分，所述模块、程序段或指令的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的***来实现，或者可以用专用硬件与计算机指令的组合来实现。The flowcharts and block diagrams in the accompanying drawings show the possible implementation architecture, functions, and operations of the system, method, and computer program product according to multiple embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, program segment, or part of an instruction, and the module, program segment, or part of an instruction contains one or more components for realizing the specified logical function. Executable instructions. In some alternative implementations, the functions marked in the block may also occur in a different order than the order marked in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions Or it can be realized by a combination of dedicated hardware and computer instructions.
该计算机程序产品可以具体通过硬件、软件或其结合的方式实现。在一个可选实施例中，所述计算机程序产品具体体现为计算机存储介质，在另一个可选实施例中，计算机程序产品具体体现为软件产品，例如软件开发包(Software Development Kit，SDK)等等。The computer program product can be specifically implemented by hardware, software, or a combination thereof. In an optional embodiment, the computer program product is specifically embodied as a computer storage medium. In another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc. Wait.
以上已经描述了本公开的各实施例，上述说明是示例性的，并非穷尽性的，并且也不限于所披露的各实施例。在不偏离所说明的各实施例的范围和精神的情况下，对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。本文中所用术语的选择，旨在最好地解释各实施例的原理、实际应用或对市场中技术的技术改进，或者使本技术领域的其它普通技术人员能理解本文披露的各实施例。The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Without departing from the scope and spirit of the described embodiments, many modifications and changes are obvious to those of ordinary skill in the art. The choice of terms used herein is intended to best explain the principles, practical applications, or technical improvements of the technologies in the market, or to enable those of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (26)

  1. 一种光强调节方法，其特征在于，所述方法包括：A method for adjusting light intensity, characterized in that the method includes:
    根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离；Determine the distance between the target object and the smart driving device according to the images collected by the smart driving device;
    根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。According to the distance between the intelligent driving device and the target object, the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
  2. 根据权利要求1所述的方法，其特征在于，根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离，包括：The method according to claim 1, wherein the determining the distance between the target object and the smart driving device according to the image collected by the smart driving device comprises:
    根据所述图像，确定所述目标对象的位置；Determine the position of the target object according to the image;
    根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离。According to the position of the target object, the distance between the target object and the intelligent driving device is determined.
  3. 根据权利要求2所述的方法，其特征在于，根据所述图像，确定所述目标对象的位置，包括：The method according to claim 2, wherein determining the position of the target object according to the image comprises:
    根据所述图像，确定所述目标对象在所述图像中的图像坐标；Determine the image coordinates of the target object in the image according to the image;
    基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置。Based on the image coordinates of the target object in the image, the position of the target object is determined.
  4. 根据权利要求3所述的方法，其特征在于，基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置，包括：The method according to claim 3, wherein determining the position of the target object based on the image coordinates of the target object in the image comprises:
    根据坐标变换关系，将所述目标对象的图像坐标转换为世界坐标系下的世界坐标；According to the coordinate transformation relationship, converting the image coordinates of the target object into world coordinates in the world coordinate system;
    所述根据所述目标对象的位置，确定所述智能驾驶设备与所述目标对象之间的距离，包括：The determining the distance between the intelligent driving device and the target object according to the position of the target object includes:
    根据所述目标对象的世界坐标以及所述智能驾驶设备的世界坐标，确定所述目标对象与所述智能驾驶设备之间的距离。According to the world coordinates of the target object and the world coordinates of the intelligent driving device, the distance between the target object and the intelligent driving device is determined.
  5. 根据权利要求4所述的方法，其特征在于，采用以下步骤确定所述坐标变换关系：The method according to claim 4, wherein the following steps are adopted to determine the coordinate transformation relationship:
    获取标注图像；Obtain annotated images;
    确定标注点在所述标注图像的图像坐标；Determining the image coordinates of the annotation point on the annotation image;
    根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。According to the image coordinates of the marked points and the pre-marked world coordinates, the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
  6. 根据权利要求1所述的方法，其特征在于，根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离，包括：The method according to claim 1, wherein the determining the distance between the target object and the smart driving device according to the image collected by the smart driving device comprises:
    根据所述图像，确定所述目标对象与所述智能驾驶设备之间的参考对象的数量；其中，相邻的两个参考对象之间的间距是已知的；According to the image, determine the number of reference objects between the target object and the intelligent driving device; wherein the distance between two adjacent reference objects is known;
    根据所述目标对象与所述智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定所述智能驾驶设备与所述目标对象之间的距离。The distance between the intelligent driving device and the target object is determined according to the number of reference objects between the target object and the intelligent driving device and the distance between adjacent reference objects.
  7. 根据权利要求1至6中任意一项所述的方法，其特征在于，所述目标对象为多个，根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度，包括：The method according to any one of claims 1 to 6, wherein there are multiple target objects, and the smart driving device is adjusted according to the distance between the smart driving device and the target object. The luminous intensity of the lamp includes:
    根据多个目标对象与所述智能驾驶设备之间的最小距离，调节所述智能驾驶设备的照明灯的发光强度。According to the minimum distance between the multiple target objects and the intelligent driving device, the luminous intensity of the lighting lamp of the intelligent driving device is adjusted.
  8. 根据权利要求1至7中任意一项所述的方法，其特征在于，根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度，包括：The method according to any one of claims 1 to 7, wherein adjusting the luminous intensity of the illuminator of the smart driving device according to the distance between the smart driving device and the target object comprises:
    根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度；Determine the target luminous intensity corresponding to the distance between the smart driving device and the target object according to the correspondence between the target distance and the target luminous intensity and the distance between the smart driving device and the target object;
    将所述智能驾驶设备的照明灯的发光强度调节至所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。The luminous intensity of the illuminator of the smart driving device is adjusted to a target luminous intensity corresponding to the distance between the smart driving device and the target object.
  9. 根据权利要求8所述的方法，其特征在于，所述根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度，包括：The method according to claim 8, wherein the determination of the relationship between the smart driving device and the target object is based on the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. The target luminous intensity corresponding to the distance between target objects includes:
    确定所述智能驾驶设备与所述目标对象之间的距离在目标距离与目标发光强度的对应关系的列表中所属的第一距离区间；Determine the first distance interval to which the distance between the intelligent driving device and the target object belongs in the list of correspondences between the target distance and the target luminous intensity;
    根据所述列表中所述第一距离区间对应的目标发光强度，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the target luminous intensity corresponding to the first distance interval in the list.
  10. 根据权利要求8所述的方法，其特征在于，所述根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度，包括：The method according to claim 8, wherein the determination of the relationship between the smart driving device and the target object is based on the corresponding relationship between the target distance and the target luminous intensity and the distance between the smart driving device and the target object. The target luminous intensity corresponding to the distance between target objects includes:
    根据所述智能驾驶设备与所述目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定所述智能驾驶设备与所述目标对象之间的距离所在的第二距离区间；所述第二距离区间为所述函数的一个距离区间；According to the distance between the intelligent driving device and the target object and a function that characterizes the correspondence between the target distance and the target luminous intensity, determine the second distance interval in which the distance between the intelligent driving device and the target object is located ; The second distance interval is a distance interval of the function;
    根据所述函数中所述第二距离区间对应的目标距离与目标发光强度的计算方式，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function.
  11. 根据权利要求1至10中任意一项所述的方法，其特征在于，所述方法还包括：The method according to any one of claims 1 to 10, wherein the method further comprises:
    在根据所述图像，确定所述图像中不存在目标对象时，将所述智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持所述智能驾驶设备的照明灯的发光强度不变。When it is determined according to the image that there is no target object in the image, the luminous intensity of the illuminating lamp of the intelligent driving device is adjusted to a preset luminous intensity, or the luminous intensity of the illuminating lamp of the intelligent driving device is maintained The intensity is unchanged.
  12. 根据权利要求1至11中任意一项所述的方法，其特征在于，所述智能驾驶设备为具有自动驾驶功能的车辆，或者为具有辅助驾驶功能的车辆。The method according to any one of claims 1 to 11, wherein the intelligent driving device is a vehicle with an automatic driving function or a vehicle with a driving assistance function.
  13. 一种光强调节装置，其特征在于，所述装置包括：A light intensity adjusting device, characterized in that the device comprises:
    确定模块，用于根据智能驾驶设备采集到的图像，确定目标对象与所述智能驾驶设备之间的距离；The determining module is used to determine the distance between the target object and the smart driving device according to the image collected by the smart driving device;
    调节模块，用于根据所述智能驾驶设备与所述目标对象之间的距离，调节所述智能驾驶设备的照明灯的发光强度。The adjustment module is used to adjust the luminous intensity of the illuminator of the intelligent driving device according to the distance between the intelligent driving device and the target object.
  14. 根据权利要求13所述的装置，其特征在于，所述确定模块，用于根据所述图像，确定所述目标对象的位置；根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离。The device according to claim 13, wherein the determining module is configured to determine the position of the target object according to the image; determine the target object and the smart object according to the position of the target object The distance between driving equipment.
  15. 根据权利要求14所述的装置，其特征在于，所述确定模块用于在根据所述图像确定所述目标对象的位置时，包括：The device according to claim 14, wherein the determining module is configured to determine the position of the target object according to the image, comprising:
    根据所述图像，确定所述目标对象在所述图像中的图像坐标；基于所述目标对象在所述图像中的图像坐标，确定所述目标对象的位置。According to the image, the image coordinates of the target object in the image are determined; and the position of the target object is determined based on the image coordinates of the target object in the image.
  16. 根据权利要求15所述的装置，其特征在于，所述确定模块用于在基于所述目标对象在所述图像中的图像坐标确定所述目标对象的位置时，包括：The device according to claim 15, wherein the determining module is configured to determine the position of the target object based on the image coordinates of the target object in the image, comprising:
    根据坐标变换关系，将所述目标对象的图像坐标转换为世界坐标系下的世界坐标；According to the coordinate transformation relationship, converting the image coordinates of the target object into world coordinates in the world coordinate system;
    所述确定模块用于在根据所述目标对象的位置，确定所述目标对象和所述智能驾驶设备之间的距离时，包括：根据所述目标对象的世界坐标以及所述智能驾驶设备的世界坐标，确定所述目标对象与所述智能驾驶设备之间的距离。The determining module is configured to determine the distance between the target object and the intelligent driving device according to the position of the target object, including: according to the world coordinates of the target object and the world of the intelligent driving device The coordinates determine the distance between the target object and the intelligent driving device.
  17. 根据权利要求16所述的装置，其特征在于，所述确定模块还用于采用以下步骤确定所述坐标变换关系：The device according to claim 16, wherein the determining module is further configured to determine the coordinate transformation relationship by adopting the following steps:
    获取标注图像；Obtain annotated images;
    确定标注点在所述标注图像的图像坐标；Determining the image coordinates of the annotation point on the annotation image;
    根据标注点的图像坐标以及预先标注的世界坐标，确定图像坐标与世界坐标的坐标变换关系。According to the image coordinates of the marked points and the pre-marked world coordinates, the coordinate transformation relationship between the image coordinates and the world coordinates is determined.
  18. 根据权利要求13所述的装置，其特征在于，所述确定模块，用于根据所述图像，确定所述目标对象与所述智能驾驶设备之间的参考对象的数量；根据所述目标对象与所述智能驾驶设备之间的参考对象的数量以及相邻的参考对象之间的间距，确定所述智能驾驶设备与所述目标对象之间的距离；其中，相邻的两个参考对象之间的间距是已知的。The apparatus according to claim 13, wherein the determining module is configured to determine the number of reference objects between the target object and the intelligent driving device according to the image; according to the target object and the intelligent driving device The number of reference objects between the intelligent driving devices and the distance between adjacent reference objects determine the distance between the intelligent driving device and the target object; wherein, between two adjacent reference objects The spacing is known.
  19. 根据权利要求13至18中任意一项所述的装置，其特征在于，所述目标对象为多个，所述调节模块，用于根据多个目标对象与所述智能驾驶设备之间的最小距离，调节所述智能驾驶设备的照明灯的发光强度。The apparatus according to any one of claims 13 to 18, wherein there are multiple target objects, and the adjustment module is configured to determine the minimum distance between the multiple target objects and the intelligent driving device. , Adjust the luminous intensity of the illuminating lamp of the intelligent driving device.
  20. 根据权利要求13至19中任意一项所述的装置，其特征在于，所述调节模块，用于根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度；将所述智能驾驶设备的照明灯的发光强度调节至所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。The apparatus according to any one of claims 13 to 19, wherein the adjustment module is used to adjust the distance between the target distance and the target luminous intensity according to the corresponding relationship between the intelligent driving device and the target object. Distance, determine the target luminous intensity corresponding to the distance between the smart driving device and the target object; adjust the luminous intensity of the illuminator of the smart driving device to be between the smart driving device and the target object The target luminous intensity corresponding to the distance.
  21. 根据权利要求20所述的装置，其特征在于，所述调节模块用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：The device according to claim 20, wherein the adjustment module is configured to determine the intelligent driving device according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object. The target luminous intensity corresponding to the distance between the driving device and the target object includes:
    确定所述智能驾驶设备与所述目标对象之间的距离在目标距离与目标发光强度的对应关系的列表中所属的第一距离区间；Determine the first distance interval to which the distance between the intelligent driving device and the target object belongs in the list of correspondences between the target distance and the target luminous intensity;
    根据所述列表中所述第一距离区间对应的目标发光强度，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the target luminous intensity corresponding to the first distance interval in the list.
  22. 根据权利要求20所述的装置，其特征在于，所述调节模块用于在根据目标距离与目标发光强度的对应关系以及所述智能驾驶设备与所述目标对象之间的距离，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度时，包括：The device according to claim 20, wherein the adjustment module is configured to determine the intelligent driving device according to the corresponding relationship between the target distance and the target luminous intensity and the distance between the intelligent driving device and the target object. The target luminous intensity corresponding to the distance between the driving device and the target object includes:
    根据所述智能驾驶设备与所述目标对象之间的距离和表征目标距离与目标发光强度的对应关系的函数，确定所述智能驾驶设备与所述目标对象之间的距离所在的第二距离区间；所述第二距离区间为所述函数的一个距离区间；According to the distance between the intelligent driving device and the target object and a function that characterizes the correspondence between the target distance and the target luminous intensity, determine the second distance interval in which the distance between the intelligent driving device and the target object is located ; The second distance interval is a distance interval of the function;
    根据所述函数中所述第二距离区间对应的目标距离与目标发光强度的计算方式，确定所述智能驾驶设备与所述目标对象之间的距离对应的目标发光强度。Determine the target luminous intensity corresponding to the distance between the intelligent driving device and the target object according to the calculation method of the target distance and the target luminous intensity corresponding to the second distance interval in the function.
  23. 根据权利要求13至22中任意一项所述的装置，其特征在于，所述调节模块还用于在根据所述图像，确定所述图像中不存在目标对象时，将所述智能驾驶设备的照明灯的发光强度调节至预设的发光强度，或者，保持所述智能驾驶设备的照明灯的发光强度不变。The apparatus according to any one of claims 13 to 22, wherein the adjustment module is further configured to: when it is determined that there is no target object in the image according to the image, change the value of the intelligent driving device The luminous intensity of the illuminating lamp is adjusted to a preset luminous intensity, or the luminous intensity of the illuminating lamp of the intelligent driving device is kept unchanged.
  24. 一种电子设备，其特征在于，包括：An electronic device, characterized in that it comprises:
    处理器；processor;
    用于存储处理器可执行指令的存储器；A memory for storing processor executable instructions;
    其中，所述处理器被配置为调用所述存储器存储的指令，以执行权利要求1至12中任意一项所述的方法。Wherein, the processor is configured to call instructions stored in the memory to execute the method according to any one of claims 1-12.
  25. 一种计算机可读存储介质，其上存储有计算机程序指令，其特征在于，所述计算机程序指令被处理器执行时实现权利要求1至12中任意一项所述的方法。A computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions implement the method according to any one of claims 1 to 12 when the computer program instructions are executed by a processor.
  26. 一种计算机程序，包括计算机可读代码，其特征在于，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现权利要求1至12中任意一项所述的方法。A computer program, comprising computer readable code, characterized in that, when the computer readable code runs in an electronic device, the processor in the electronic device is executed to implement any one of claims 1 to 12 The method described.
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