CN111866402A - Parameter adjusting method and device, electronic equipment and storage medium - Google Patents
Parameter adjusting method and device, electronic equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/76—Circuitry for compensating brightness variation in the scene by influencing the image signals
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Abstract
The embodiment of the application provides a parameter adjusting method and device, an electronic device and a storage medium, and relates to the technical field of parameter adjustment. The parameter adjusting method is applied to electronic equipment, the electronic equipment is in communication connection with photographing equipment, and the parameter adjusting method comprises the following steps: firstly, obtaining a sample image shot by a shooting device; secondly, processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains; and then, adjusting parameters of the photographing equipment according to the illumination intensity of the sample image, the exposure value and the deviation value of the camera gain. By the method, the camera can be adjusted to multiple parameters quickly, and the appropriate parameters can be adjusted quickly, so that the parameter adjustment efficiency is improved.
Description
Technical Field
The present application relates to the field of parameter adjustment technologies, and in particular, to a parameter adjustment method and apparatus, an electronic device, and a storage medium.
Background
The inventor researches and discovers that in the prior art, the imaging quality of a camera is mainly adjusted according to a single-factor variable, illumination, camera gain or exposure is independently adjusted by utilizing an image gray level mean value, a histogram and the like, and the method is difficult to adjust to proper parameters in the adjustment process and slow in adjustment speed, so that the problem of low parameter adjustment efficiency exists.
Disclosure of Invention
In view of the above, an object of the present application is to provide a parameter adjusting method and apparatus, an electronic device, and a storage medium, so as to solve the problems in the prior art.
In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:
a parameter adjusting method is applied to electronic equipment, the electronic equipment is in communication connection with photographing equipment, and the parameter adjusting method comprises the following steps:
acquiring a sample image shot by the shooting equipment;
processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains;
and adjusting parameters of the photographing equipment according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image.
In a preferred option of the embodiment of the present application, the parameter adjusting method further includes a step of obtaining the first preset model, where the step includes:
acquiring a first training image, and training an initial model according to the first training image to obtain the first preset model, wherein the first training image comprises images with different illumination intensities, exposure values and camera gains, which are obtained by shooting by the shooting equipment.
In a preferred option of the embodiment of the present application, the step of training an initial model according to the first training image to obtain the first preset model includes:
screening the first training image to obtain a first reference image;
calibrating the first training image according to the first reference image to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the first training image;
and training the initial model according to the illumination intensity, the exposure value and the deviation value of the camera gain of the first training image to obtain the first preset model.
In a preferred option of the embodiment of the present application, the parameter adjusting method further includes:
processing the sample image according to a second preset model to obtain a deviation value of a pixel value of the sample image, wherein the second preset model is obtained by training according to second training images with different pixel values;
and adjusting the pixel value of the sample image according to the deviation value of the pixel value of the sample image to obtain an adjusted image corresponding to the sample image.
In a preferred option of the embodiment of the present application, the parameter adjusting method further includes a step of obtaining the second preset model, where the step includes:
and acquiring a second training image, and training the initial model according to the second training image to obtain the second preset model, wherein the second training image comprises images with different pixel values, which are obtained by shooting by the shooting equipment.
In a preferred option of the embodiment of the present application, the step of training the initial model according to the second training image to obtain the second preset model includes:
screening the second training image to obtain a second reference image;
calibrating the second training image according to the second reference image to obtain a deviation value of the pixel value of the second training image;
and training the initial model according to the deviation value of the pixel value of the second training image to obtain the second preset model.
The embodiment of the present application further provides a parameter adjusting device, which is applied to an electronic device, the electronic device is in communication connection with a photographing device, and the parameter adjusting device includes:
the image acquisition module is used for acquiring a sample image shot by the shooting equipment;
the image processing module is used for processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains;
and the parameter adjusting module is used for adjusting the parameters of the photographing equipment according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image.
In a preferred option of the embodiment of the present application, the parameter adjusting apparatus further includes:
and the model training module is used for acquiring a first training image, training an initial model according to the first training image to obtain the first preset model, wherein the first training image comprises images with different illumination intensities, exposure values and camera gains, which are obtained by shooting by the shooting equipment.
An embodiment of the present application further provides an electronic device, which includes a memory and a processor, where the processor is configured to execute an executable computer program stored in the memory, so as to implement the parameter adjustment method described above.
The embodiment of the present application further provides a storage medium, on which a computer program is stored, and when the program is executed, the steps of the parameter adjusting method are implemented.
According to the parameter adjusting method and device, the electronic equipment and the storage medium, the sample image is processed according to the first preset model, the deviation value of the illumination intensity, the exposure value and the camera gain of the sample image is obtained, and the parameter of the photographing equipment is adjusted according to the deviation value of the illumination intensity, the exposure value and the camera gain of the sample image, so that the multi-parameter adjustment of the camera is realized, the proper parameter is quickly adjusted, the problem that in the prior art, the camera imaging quality is adjusted aiming at a single-factor variable, the proper parameter is difficult to adjust, the adjusting speed is low, and the parameter adjusting efficiency is low is solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a block diagram of a parameter adjustment system according to an embodiment of the present disclosure.
Fig. 2 is a block diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 3 is a schematic flow chart of a parameter adjustment method according to an embodiment of the present application.
Fig. 4 is another schematic flow chart of a parameter adjustment method according to an embodiment of the present disclosure.
Fig. 5 is another schematic flow chart of a parameter adjustment method according to an embodiment of the present disclosure.
Fig. 6 is another schematic flow chart of a parameter adjustment method according to an embodiment of the present disclosure.
Fig. 7 is another schematic flow chart of a parameter adjustment method according to an embodiment of the present application.
Fig. 8 is another schematic flow chart of a parameter adjustment method according to an embodiment of the present application.
Icon: 10-a parameter adjustment system; 100-an electronic device; 110-a network port; 120-a first processor; 130-a communication bus; 140-a first storage medium; 150-interface; 200-photographing equipment.
Detailed Description
For purposes of making the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In order to enable a person skilled in the art to make use of the present disclosure, the following embodiments are given. It will be apparent to those skilled in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Applications of the system or method of the present application may include web pages, plug-ins for browsers, client terminals, customization systems, internal analysis systems, or artificial intelligence robots, among others, or any combination thereof.
It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
FIG. 1 is a schematic diagram of exemplary hardware and software components of a parameter adjustment system 10 that may implement the concepts of the present application, according to some embodiments of the present application. The parameter adjustment system may include an electronic device 100 and a photographing device 200.
The electronic device 100 is in communication connection with the photographing device 200 to obtain an image captured by the photographing device 200, and the electronic device 100 may adjust parameters of the photographing device 200 according to the obtained image.
It should be noted that the electronic device 100 and the photographing device 200 may be two independent devices, or may be different modules of the same device, so as to implement different functions.
Fig. 2 illustrates a schematic diagram of exemplary hardware and software components of an electronic device 100 that may implement the concepts of the present application, according to some embodiments of the present application. The electronic device 100 may include a network port 110 connected to a network, one or more first processors 120 for executing program instructions, a communication bus 130, and a first storage medium 140 of a different form, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the electronic device 100 may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof, according to which the methods of the present application may be implemented. The electronic device 100 may also include an Input/Output (I/O) interface 150 with other Input/Output devices (e.g., keyboard, display screen).
In some embodiments, the first processor 120 may process information and/or data related to parameter adjustments to perform one or more of the functions described herein. In some embodiments, the first processor 120 may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, the first Processor 120 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a reduced Instruction Set computer (reduced Computing Set Computing, RISC), a microprocessor, or the like, or any combination thereof.
The first processor 120 in the electronic device 100 may be a general purpose computer or a set purpose computer, both of which may be used to implement the parameter adjustment method of the present application. Although only a single computer is shown, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.
For ease of illustration, only one processor is depicted in electronic device 100. However, it should be noted that the electronic device 100 in the present application may also comprise a plurality of processors, and thus the steps performed by one processor described in the present application may also be performed by a plurality of processors in combination or individually. For example, if the processor of the electronic device 100 executes steps a and B, it should be understood that steps a and B may also be executed by two different processors together or separately in one processor. For example, a first processor performs step A and a second processor performs step B, or both a first processor and a second processor perform steps A and B.
The network may be used for the exchange of information and/or data. In some embodiments, one or more components in electronic device 100 may send information and/or data to other components. For example, the electronic device 100 may acquire the signal via a network. Merely by way of example, the Network may include a Wireless Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a bluetooth Network, a ZigBee Network, or a Near Field Communication (NFC) Network, among others, or any combination thereof.
In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of electronic device 100 may connect to the network to exchange data and/or information.
With reference to fig. 3, an embodiment of the present application further provides a parameter adjusting method, which may be applied to the electronic device 100 shown in fig. 2, where the parameter adjusting method may include:
in step S310, a sample image captured by the photographing apparatus 200 is acquired.
It should be noted that, under different illumination intensities, parameters such as an exposure value and a camera gain of the photographing apparatus 200 are different, and sample images with different pixel values can be obtained, that is, the sample images include parameters such as the illumination intensity, the exposure value, the camera gain, and the pixel value.
After step S310, when the parameters of the photographing apparatus 200 need to be adjusted to obtain an image satisfying the requirements, step S320 and step S330 are performed.
Step S320, processing the sample image according to the first preset model to obtain the illumination intensity, the exposure value, and the deviation value of the camera gain of the sample image.
The first preset model is obtained by training according to first training images with different illumination intensities, exposure values and camera gains.
And step S330, adjusting parameters of the photographing equipment according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image.
It should be noted that the illumination intensity of the image captured by the photographing apparatus 200 may be adjusted by adjusting the ambient illumination intensity, or may be adjusted by adjusting the flash illumination intensity of the photographing apparatus 200. The exposure value of the image obtained by the photographing device 200 can be adjusted by adjusting the aperture and shutter speed of the photographing device 200, the aperture controls the entering size of the light, the larger the aperture is, the more the light is collected in unit time, the larger the exposure value is, the smaller the aperture is, the less the light is collected in unit time, and the larger the exposure value is; the shutter speed is the time for pressing the shutter, and the longer the time is, the more the collected light is, and the larger the exposure value is. The camera gain of the image captured by the photographing apparatus 200 may be obtained by adjusting the sensitivity (ISO) of the photographing apparatus 200, where ISO may represent the light sensing speed of the light sensing element of the photographing apparatus 200, and a higher ISO value indicates a stronger light sensing capability of the light sensing element and a larger camera gain.
By the method, the sample image is processed according to the first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, and the parameters of the photographing equipment are adjusted according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, so that the multi-parameter adjustment of the camera is realized, the proper parameters are quickly adjusted, and the problems that in the prior art, the imaging quality of the camera is adjusted according to single-factor variables, the proper parameters are difficult to adjust, the adjusting speed is low, and the parameter adjusting efficiency is low are solved.
Before step S310, it should be noted that the embodiment of the present application may further include a step of obtaining a first preset model. Therefore, on the basis of fig. 3, fig. 4 is a schematic flow chart of another parameter adjusting method provided in the embodiment of the present application, and referring to fig. 4, the parameter adjusting method may further include:
step S340, acquiring a first training image, and training the initial model according to the first training image to obtain a first preset model.
The first training image comprises images with different illumination intensities, exposure values and camera gains, wherein the images are obtained by shooting of the shooting equipment.
In detail, the illumination intensity of the environment can be measured by using the illumination meter, a plurality of groups of images with different illumination intensities, different exposure values and different camera gains in the same scene are collected, the range of the illumination intensity and the range of the exposure value in the collection process all need to cover the range in the real environment, and the specific range can be set according to actual requirements. For example, in an alternative example, the exposure time corresponding to the shutter speed may range from 1000ms to 6000ms, and the acquisition interval may be set to 1000ms or may be set to 500 ms.
For step S340, it should be noted that the step of training the model is not limited, and may be set according to the actual application requirement. For example, in an alternative example, step S340 may include the step of screening the first training image. Therefore, on the basis of fig. 4, fig. 5 is a schematic flow chart of another parameter adjusting method provided in the embodiment of the present application, and referring to fig. 5, step S340 may include:
step S341, a first reference image is obtained by performing a screening process on the first training image.
It should be noted that, in the embodiment of the present application, the first training image may be screened in a manner of manually screening a clear image, so as to obtain a first reference image; the average pixel value of all pixel points of each first training image can be calculated, all the first training images are ranked, and the first training image with the highest average pixel value is selected as the first reference image.
Step S342, calibrating the first training image according to the first reference image to obtain a deviation value of the illumination intensity, the exposure value and the camera gain of the first training image.
It should be noted that the number of the first reference images may be plural, and for example, for different luminances, the first reference images with different luminances (dark, bright, and normal luminance) may be manually set. For each first training image, the closest first reference image can be selected as a standard to perform calibration processing on the first training image, and the illumination intensity, the exposure value and the camera gain of the first training image are calibrated to be low or high, namely, the deviation value of the illumination intensity, the exposure value and the camera gain of the first training image is obtained.
Step S343, training the initial model according to the illumination intensity of the first training image, the exposure value and the deviation value of the camera gain to obtain a first preset model.
It should be noted that the specific type of the initial model is not limited, and may be set according to the actual application requirements. For example, in one alternative example, the initial model may be a convolutional network model.
For the step S330, it should be noted that after obtaining the deviation values of the illumination intensity, the exposure value and the camera gain of the sample image, the parameters of the photographing apparatus 200 may be adjusted so that the image obtained by the photographing apparatus 200 meets the requirements. For example, the camera gain of the sample image is 1000, the camera gain of the sample image is lower according to the deviation value of the camera gain, the adjustment step size may be set to 500, the camera gain of the photographing apparatus 200 is adjusted to 1500 according to the adjustment step size, and the adjusted image photographed by the photographing apparatus 200 is obtained. If the gain of the camera of the image shot by the adjusted photographing device 200 is low, the adjustment step length may also be set to 500, and the photographing device 200 is adjusted again according to the adjustment step length.
It should be noted that, after step S310, the sample image may not be processed by using the first preset model, and the sample image may be directly compared with the first reference image to obtain a deviation value of the illumination intensity, the exposure value and the camera gain of the sample image, and the parameters of the photographing apparatus 200 are adjusted according to the deviation value of the illumination intensity, the exposure value and the camera gain of the sample image.
Further, the embodiment of the present application may further include a step of adjusting the sample image itself. Therefore, after step S310, fig. 6 is a schematic flow chart of another parameter adjusting method provided in the embodiment of the present application, and referring to fig. 6, the parameter adjusting method may further include:
and step S350, processing the sample image according to the second preset model to obtain a deviation value of the pixel value of the sample image.
And the second preset model is obtained by training according to second training images with different pixel values.
And step S360, adjusting the pixel value of the sample image according to the deviation value of the pixel value of the sample image to obtain an adjusted image corresponding to the sample image.
Before step S310, it should be noted that, this embodiment of the application may further include a step of obtaining a second preset model. Therefore, on the basis of fig. 6, fig. 7 is a schematic flow chart of another parameter adjusting method provided in the embodiment of the present application, and referring to fig. 7, the parameter adjusting method may further include:
step S370, a second training image is obtained, and the initial model is trained according to the second training image, so as to obtain a second preset model.
The second training image comprises images with different pixel values, which are obtained by shooting of the shooting equipment.
For step S370, it should be noted that the step of training the model is not limited, and may be set according to the actual application requirement. For example, in an alternative example, step S370 may include the step of screening the second training image. Therefore, on the basis of fig. 7, fig. 8 is a schematic flowchart of another parameter adjustment method provided in the embodiment of the present application, and referring to fig. 8, step S370 may include:
step S371 is to perform a screening process on the second training image to obtain a second reference image.
It should be noted that, in the embodiment of the present application, the second training image may be screened in a manner of manually screening a clear image, so as to obtain a second reference image; the average pixel value of all pixel points of each second training image can be calculated, all the second training images are ranked, and the second training image with the highest average pixel value is selected as the first reference image.
And step 372, calibrating the second training image according to the second reference image to obtain a deviation value of the pixel value of the second training image.
It should be noted that the number of the second reference images may be plural, and for example, for different luminances, the second reference images with different luminances (dark, bright, and normal luminance) may be manually set. For each second training image, the closest second reference image may be selected as a standard to perform calibration processing on the second training image, and whether the pixel value of the second training image is low or high is calibrated, that is, a deviation value of the pixel value of the second training image is obtained.
Step S373, training the initial model according to the deviation value of the pixel value of the second training image to obtain a second preset model.
In step S360, it should be noted that after the deviation value of the pixel value of the sample image is obtained, the pixel value of the sample image may be adjusted to obtain an adjusted image corresponding to the sample image, and the deviation value of the pixel value of the adjusted image is 0, so that the adjusted image meets the requirement.
It should be noted that, after step S310, the sample image may not be processed by using the second preset model, the sample image may be directly compared with the second reference image to obtain a deviation value of the pixel value of the sample image, and the pixel value of the sample image is adjusted according to the deviation value of the pixel value of the sample image to obtain an adjusted image corresponding to the sample image.
Further, an embodiment of the present application further provides a parameter adjusting apparatus, where functions implemented by the parameter adjusting apparatus correspond to steps executed by the foregoing method. The parameter adjusting apparatus may be understood as a processor of the electronic device 100, or may be understood as a component that is independent from the electronic device 100 or the processor and implements the functions of the present application under the control of the electronic device 100. The parameter adjusting device may include an image obtaining module, an image processing module, and a parameter adjusting module.
And the image acquisition module is used for acquiring a sample image shot by the shooting equipment. In the embodiment of the present application, the image acquiring module may be configured to perform step S310 shown in fig. 3, and reference may be made to the foregoing detailed description of step S310 for relevant content of the image acquiring module.
And the image processing module is used for processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains. In the embodiment of the present application, the image processing module may be configured to perform step S320 shown in fig. 3, and reference may be made to the foregoing detailed description of step S320 for relevant contents of the image processing module.
And the parameter adjusting module is used for adjusting the parameters of the photographing equipment according to the illumination intensity of the sample image, the exposure value and the deviation value of the camera gain. In the embodiment of the present application, the parameter adjustment module may be configured to perform step S330 shown in fig. 3, and reference may be made to the foregoing detailed description of step S330 for relevant contents of the parameter adjustment module.
Further, the parameter adjustment device provided in this application embodiment may further include a model training module, configured to obtain a first training image, train the initial model according to the first training image, and obtain a first preset model, where the first training image includes images with different illumination intensities, exposure values, and camera gains, which are obtained by shooting with a shooting device. In the embodiment of the present application, the model training module may be configured to perform step S340 shown in fig. 4, and reference may be made to the foregoing detailed description of step S340 for relevant contents of the model training module.
In addition, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the parameter adjustment method.
The computer program product of the parameter adjustment method provided in the embodiment of the present application includes a computer-readable storage medium storing a program code, where instructions included in the program code may be used to execute the step of parameter adjustment in the above method embodiment, which may be referred to specifically in the above method embodiment, and details are not described here again.
To sum up, according to the parameter adjustment method and apparatus, the electronic device, and the storage medium provided in the embodiments of the present application, the sample image is processed according to the first preset model, so as to obtain the deviation value of the illumination intensity, the exposure value, and the camera gain of the sample image, and the parameter of the photographing device is adjusted according to the deviation value of the illumination intensity, the exposure value, and the camera gain of the sample image, thereby achieving multi-parameter adjustment of the camera and quickly adjusting to a suitable parameter, and avoiding the problems that in the prior art, the camera imaging quality is adjusted for a single-factor variable, and is often difficult to adjust to a suitable parameter, the adjustment speed is slow, and the resulting parameter adjustment efficiency is low.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. The parameter adjusting method is applied to electronic equipment, wherein the electronic equipment is in communication connection with photographing equipment, and the parameter adjusting method comprises the following steps:
acquiring a sample image shot by the shooting equipment;
processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains;
and adjusting parameters of the photographing equipment according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image.
2. The parameter adjustment method according to claim 1, further comprising a step of obtaining the first preset model, the step comprising:
acquiring a first training image, and training an initial model according to the first training image to obtain the first preset model, wherein the first training image comprises images with different illumination intensities, exposure values and camera gains, which are obtained by shooting by the shooting equipment.
3. The parameter adjustment method according to claim 2, wherein the step of training an initial model according to the first training image to obtain the first preset model comprises:
screening the first training image to obtain a first reference image;
calibrating the first training image according to the first reference image to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the first training image;
and training the initial model according to the illumination intensity, the exposure value and the deviation value of the camera gain of the first training image to obtain the first preset model.
4. The parameter adjustment method of claim 1, further comprising:
processing the sample image according to a second preset model to obtain a deviation value of a pixel value of the sample image, wherein the second preset model is obtained by training according to second training images with different pixel values;
and adjusting the pixel value of the sample image according to the deviation value of the pixel value of the sample image to obtain an adjusted image corresponding to the sample image.
5. The parameter adjustment method according to claim 4, further comprising a step of obtaining the second preset model, the step comprising:
and acquiring a second training image, and training the initial model according to the second training image to obtain the second preset model, wherein the second training image comprises images with different pixel values, which are obtained by shooting by the shooting equipment.
6. The parameter adjustment method according to claim 5, wherein the step of training the initial model according to the second training image to obtain the second preset model comprises:
screening the second training image to obtain a second reference image;
calibrating the second training image according to the second reference image to obtain a deviation value of the pixel value of the second training image;
and training the initial model according to the deviation value of the pixel value of the second training image to obtain the second preset model.
7. The parameter adjusting device is applied to an electronic device, wherein the electronic device is in communication connection with a photographing device, and the parameter adjusting device comprises:
the image acquisition module is used for acquiring a sample image shot by the shooting equipment;
the image processing module is used for processing the sample image according to a first preset model to obtain the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image, wherein the first preset model is obtained by training according to first training images with different illumination intensities, different exposure values and different camera gains;
and the parameter adjusting module is used for adjusting the parameters of the photographing equipment according to the illumination intensity, the exposure value and the deviation value of the camera gain of the sample image.
8. The parameter adjustment apparatus of claim 7, wherein the parameter adjustment apparatus further comprises:
and the model training module is used for acquiring a first training image, training an initial model according to the first training image to obtain the first preset model, wherein the first training image comprises images with different illumination intensities, exposure values and camera gains, which are obtained by shooting by the shooting equipment.
9. An electronic device comprising a memory and a processor, the processor being configured to execute an executable computer program stored in the memory to implement the parameter adjustment method of any one of claims 1-6.
10. A storage medium, having stored thereon a computer program which, when executed, carries out the steps of the parameter adjustment method of any one of claims 1 to 6.
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