CN115631356A - Road facility missing identification method and device, storage medium and electronic device - Google Patents
Road facility missing identification method and device, storage medium and electronic device Download PDFInfo
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Abstract
The embodiment of the invention provides a method and a device for identifying missing road facilities, a storage medium and an electronic device, and relates to the technical field of road facility inspection technologies. The method comprises the following steps: acquiring initial image information of a target road; determining facility shadow information of a target area through a pre-trained object recognition model; under the condition that the facility shadow information meets a first position condition, performing first matching processing on the facility shadow information and preset facility reference information to obtain a first matching result; determining that the asset is missing if the first matching result does not satisfy a first matching condition. By the method and the device, the problem of low identification precision of the missing road facilities is solved, and the effect of improving the missing road facilities is achieved.
Description
Technical Field
The embodiment of the invention relates to the field of road facility inspection, in particular to a road facility missing identification method, a road facility missing identification device, a storage medium and an electronic device.
Background
In recent years, for the purpose of responding to garden city construction, city road construction in China gradually decorates city roads through flower boxes and the like so as to increase road greening and improve city aesthetic feeling.
Under the influence of severe weather such as typhoon, the flower box on the road is easy to lose and the like, or under the influence of traffic accidents, the flower box can be damaged and displaced, particularly, the displacement phenomenon can cause accidents such as road traffic jam, secondary impact, vehicle scratch and the like in severe cases.
In the prior art, only the conditions of pit bags and the like of roads are automatically detected, and no scheme for effectively detecting the road flower boxes exists, so that the inspection can be carried out only in a manual inspection mode, the mode consumes manpower, and the inspection efficiency is also reduced.
Disclosure of Invention
The embodiment of the invention provides a method and a device for identifying the missing of road facilities, a storage medium and an electronic device, which at least solve the problem of the missing of road flower boxes in the related technology.
According to an embodiment of the present invention, there is provided a road facility loss identification method including:
acquiring initial image information of a target road;
determining facility shadow information of a target area through a pre-trained object recognition model, wherein the target road comprises the target area, and the facility shadow information comprises shadow information of road facilities of the target road;
under the condition that the facility shadow information meets a first position condition, performing first matching processing on the facility shadow information and preset facility reference information to obtain a first matching result;
determining that the asset is missing if the first matching result does not satisfy a first matching condition.
In an exemplary embodiment, after determining the facility shadow information of the target area through the pre-trained object recognition model, the method further comprises:
under the condition that the facility shadow information meets a second position condition, performing second matching processing on the facility shadow information and the facility reference information to obtain a second matching result;
and determining that the road facility is missing if the second matching result meets a first matching condition.
In an exemplary embodiment, before the determining facility shadow information of the target area through the pre-trained object recognition model, the method further comprises:
acquiring weather information and/or time information of the target road to determine an illumination angle of a target time period;
determining the first location condition and/or the second location condition for a target time period based on the illumination angle.
In an exemplary embodiment, after the obtaining weather information and/or time information of the target road to determine the illumination angle of the target time period, the method further comprises:
acquiring road ponding information of the target road based on the initial image information under the condition that the weather information and/or the time information meet a first weather condition;
determining second facility shadow information of the target road based on the road ponding information;
performing third matching processing on the second facility shadow information and the facility shadow information to obtain a third matching result;
determining that the asset is missing if the third matching result does not satisfy the first matching condition.
In one exemplary embodiment, the method further comprises:
determining a road reference line of the target road and a facility reference line of the road facility through the object recognition model;
calculating a space included angle of the road reference line and the facility reference line to obtain a reference included angle;
and determining that the road facility has the dislocation under the condition that the reference included angle is larger than a first threshold value and smaller than a second threshold value.
According to another embodiment of the present invention, there is provided a road facility loss identifying apparatus including:
the image acquisition module is used for acquiring initial image information of a target road;
an information determination module, configured to determine facility shadow information of a target area through a pre-trained object recognition model, where the target road includes the target area, and the facility shadow information includes shadow information of road facilities of the target road;
the first matching module is used for performing first matching processing on the facility shadow information and preset facility reference information under the condition that the facility shadow information meets a first position condition so as to obtain a first matching result;
and the first result judging module is used for determining that the road facilities are missing under the condition that the first matching result does not meet the first matching condition.
In one exemplary embodiment, further comprising:
a second matching module, configured to, after determining facility shadow information of a target area through the pre-trained object recognition model, perform second matching processing on the facility shadow information and the facility reference information to obtain a second matching result when the facility shadow information satisfies a second position condition;
and the second result judging module is used for determining that the road facilities are missing under the condition that the second matching result meets the first matching condition.
In one exemplary embodiment, further comprising:
the weather information acquisition module is used for acquiring weather information and/or time information of the target road to determine an illumination angle of a target time period before determining facility shadow information of a target area through the pre-trained object recognition model;
a condition generating module for determining the first location condition and/or the second location condition of a target time period based on the illumination angle.
According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to, when executed, perform the steps of any of the method embodiments described above.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, as the facility shadow is compared with the facility reference, the automation of flower box identification is realized, the calculation requirement for identifying the attribute of the flower box is reduced, and the flower box identification efficiency is improved, so that the problem of low flower box identification precision can be solved, and the effect of improving the flower box identification precision and efficiency is achieved.
Drawings
Fig. 1 is a block diagram of a hardware structure of a mobile terminal of a road infrastructure loss identification method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for identifying missing roadway facilities in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating one embodiment of the present invention;
FIG. 4 is a schematic diagram of a second embodiment of the present invention;
fig. 5 is a block diagram of a road facility loss identification apparatus according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided in the embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the example of the operation on a mobile terminal, fig. 1 is a block diagram of a hardware structure of the mobile terminal of a road facility missing identification method according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, wherein the mobile terminal may further include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program and a module of application software, such as a computer program corresponding to a road facility loss identification method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In the present embodiment, a road facility loss identification method is provided, and fig. 2 is a flowchart of a road facility loss identification method according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps:
step S202, acquiring initial image information of a target road;
in this embodiment, the initial image information of the target road is acquired to identify facilities such as flower boxes of the target road by image recognition, so as to realize automation of facility identification.
The target road includes (but is not limited to) a road needing facility monitoring, and can be manually set according to administrative planning, or determined according to an information acquirable range determined by equipment parameters of information acquisition equipment, or obtained by performing space division through a GIS technology; the mode of obtaining the initial image information may be (but is not limited to) that images or information are acquired in a certain area through a visible light camera or a laser radar, or that images are acquired on a target road through a mode that an unmanned aerial vehicle carries an airborne camera, correspondingly, the initial image information further includes coordinate information of the target road, and the determination of the target road may be (but is not limited to) that the target road is identified through trained neural network models such as yolo3 and yolo 5.
Step S204, determining facility shadow information of a target area through a pre-trained object recognition model, wherein the target road comprises the target area, and the facility shadow information comprises shadow information of road facilities of the target road;
in the embodiment, the difficulty of identifying the shadow is smaller than that of identifying the specific object, and the required calculation force is smaller, so that the facility identification efficiency can be improved, and the equipment cost required by identification can be reduced.
The object recognition model may be, but is not limited to, a model for recognizing a specific object, such as CNN, RCNN, fast-RCNN, etc., and the training process of the object recognition model may include (but is not limited to) a process of calculating the intensity ratio of sunlight irradiating on three channels of RGB in the initial image information, and then performing segmentation calculation of a shadow region and a non-shadow region; the target area comprises (but is not limited to) areas 1-2m on two sides of a target road, a central axis area of the road and the like, the road facilities comprise (but is not limited to) road facilities such as a road flower box, a tree, a street lamp, a protective fence, a sound insulation screen and the like, in some special cases, special things such as vehicles, pedestrians, buildings, sprinklers and the like on the road can be identified, and correspondingly, the shadow information comprises (but is not limited to) coordinate information, area information and the like of shadows of the road facilities.
Step S206, under the condition that the facility shadow information meets a first position condition, carrying out first matching processing on the facility shadow information and preset facility reference information to obtain a first matching result;
in the present embodiment, as shown in fig. 3, in the case where the road facility location is normal and the shadow can be captured (i.e., the capturing device is directed to the light), the road facility and the shadow on the road should be in one-to-one correspondence, so if the shadow is lost, it can be considered that the road facility is lost.
Wherein the first location condition may be (but is not limited to) a location where the facility shadow and the asset may be collected at the same time, for example, as shown in fig. 3, shadow information of the asset and the asset may be collected at the same time, when the facility shadow information satisfies the first location condition; the facility reference information includes, but is not limited to, coordinates, size, color, type, etc. of the road facility.
The first matching process may (but is not limited to) calculate the illumination position of the coordinates of the road facility in the facility reference information and match the calculation result with the shadow coordinates included in the shadow information, or may directly match the coordinates of the road facility in the facility reference information with the shadow coordinates and determine whether the shadow coordinates are within the coordinate variation range of the road facility.
And step S208, determining that the road facilities are missing when the first matching result does not meet the first matching condition.
In this embodiment, the first matching condition may (but is not limited to) be that the coordinates of the road facility and the shadow information are in one-to-one correspondence, that is, the illumination position calculation may be matched to the corresponding shadow coordinates, or the coordinates of the road facility may be matched to the corresponding shadow coordinates, and when the coordinates of the road facility do not match to the corresponding shadow information, it is indicated that the corresponding road facility is missing.
Through the steps, the calculation force required by the shadow identification and change calculation is small compared with the identification of the facility, the model training is simpler, and meanwhile, the identification error caused by the facility approximation is avoided, so that the equipment arrangement cost and the facility inspection cost can be reduced, the problems of high identification cost and low identification precision of road facilities (such as road flower boxes) are solved, the identification efficiency and precision of the road facilities are improved, and the inspection cost is reduced.
The main body of executing the above steps may be a base station, a terminal, and the like, but is not limited thereto.
In an optional embodiment, after determining the facility shadow information of the target area through the pre-trained object recognition model, the method further comprises:
step S2010, performing second matching processing on the facility shadow information and the facility reference information to obtain a second matching result when the facility shadow information satisfies a second position condition;
step S2012, determining that the road facility is missing if the second matching result satisfies the first matching condition.
In the present embodiment, in the case where the road facility can be collected but the shadow cannot be collected (i.e., the collecting device is backlighted), the shadow is usually blocked by the road facility, and at this time, if the shadow information can be collected, it indicates that the road facility is missing.
In this embodiment, the second location condition may (but is not limited to) be a location where a facility shadow and an asset cannot be collected simultaneously, and correspondingly, the second matching condition is that coordinates of the asset cannot be matched with corresponding road shadow information, and if the coordinates of the asset cannot be matched with the corresponding road shadow information, the shadow is not blocked, so that it is indicated that the road equipment is missing.
In an optional embodiment, before the determining facility shadow information of the target area through the pre-trained object recognition model, the method further comprises:
step S20402, acquiring weather information and/or time information of the target road to determine an illumination angle of a target time period;
step S20404, based on the illumination angle, determines the first position condition and/or the second position condition of the target time period.
In this embodiment, since the shadow may change with the change of the sun illumination angle, or may be limited by the illumination of the surrounding street lamps at night, the judgment of the weather information or the time information of the target road can determine the shadow change range of the road facility.
The target time period includes (but is not limited to) the time period of acquiring the initial image information, the weather information includes (but is not limited to) information such as weather conditions (sunny days, rainy days, snowy days and the like), temperature and humidity, wind speed, wind direction and the like, and the acquisition of the weather information can be (but is not limited to) acquired by an internet crawler through published information of a relevant meteorological department or directly obtained by networking with a relevant system of the meteorological department, and can also be acquired through other modes; the time information can be obtained by acquiring standard time in real time or by a timing module.
In an optional embodiment, after the obtaining weather information and/or time information of the target road to determine the illumination angle of the target time period, the method further includes:
step S204022, under the condition that the weather information and/or the time information meet a first weather condition, acquiring road ponding information of the target road based on the initial image information;
step S204042, determining second facility shadow information of the target road based on the road ponding information;
step S204026, performing a third matching process on the second facility shadow information and the facility shadow information to obtain a third matching result;
step S204028, in a case where the third matching result does not satisfy the first matching condition, determines that the asset is missing.
In the embodiment, as shown in fig. 4, in the case of rainy days, the light cannot form obvious shadows, and at this time, the absence of facilities can be identified by collecting road ponding and shadows of road facilities generated by the ponding.
The first weather condition can be (but is not limited to) weather which may generate road ponding, such as rainy days and the like, the road ponding information comprises information such as coordinates and areas of the road ponding, and the acquisition of the road ponding information can also be obtained by identifying the initial image information through an object identification model; the third matching process may be (but is not limited to) jointly matching the coordinates of the water of road, the coordinates of the shade information, and the coordinates of the road facilities, or may be matching in another form, and when the coordinates of the water of road, the coordinates of the shade information, and the coordinates of the road facilities cannot be matched, it is determined that the corresponding road facilities are missing.
In an optional embodiment, the method further comprises:
step S2002, determining a road reference line of the target road and a facility reference line of the road facility through the object recognition model;
step S2004, calculating a space included angle between the road reference line and the facility reference line to obtain a reference included angle;
step S2006, determining that the road facility has an abnormal position when the reference included angle is greater than a first threshold and smaller than a second threshold.
In this embodiment, the road facility is generally in a standard shape, and is set according to a certain rule, for example, the street lamp is in a column shape, and the sound insulation board is in a rectangular shape and is set along the extending direction of the road, so that the facility reference line can be determined by determining the central axis of the road facility, and then determining whether the included angle between the central axis of the road facility and the reference line of the road meets a preset condition can determine whether the corresponding road facility is abnormal, for example, the included angle between the street lamp and the road is generally 90 °, and if the included angle is less than 85 °, the road facility may topple.
The determination of the road reference line may (but is not limited to) determine a central axis of the road after determining the boundary of the road, and use the central axis as the road reference line, or use a boundary line of the road as the road reference line, or use a solid line or a dotted line drawn in the target road as the road reference line, and the road reference line.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method according to the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, a device for identifying missing road facilities is further provided, and the device is used to implement the above embodiments and preferred embodiments, which have already been described and will not be described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware or a combination of software and hardware is also possible and contemplated.
Fig. 5 is a block diagram of a road facility loss identification apparatus according to an embodiment of the present invention, as shown in fig. 5, the apparatus including:
the image acquisition module 52 is used for acquiring initial image information of the target road;
an information determining module 54, configured to determine facility shadow information of a target area through a pre-trained object recognition model, where the target road includes the target area, and the facility shadow information includes shadow information of road facilities of the target road;
a first matching module 56, configured to, when the facility shadow information meets a first position condition, perform a first matching process on the facility shadow information and preset facility reference information to obtain a first matching result;
and a first result judging module 58, configured to determine that the asset is missing if the first matching result does not satisfy the first matching condition.
In an optional embodiment, further comprising:
a second matching module 510, configured to, after determining facility shadow information of a target area through the pre-trained object recognition model, perform second matching processing on the facility shadow information and the facility reference information when the facility shadow information satisfies a second position condition, so as to obtain a second matching result;
a second result judging module 512, configured to determine that the road facility is missing if the second matching result satisfies the first matching condition.
In an optional embodiment, further comprising:
a weather information acquisition module 5402, configured to acquire weather information and/or time information of the target road before determining facility shadow information of a target area through the pre-trained object recognition model, so as to determine an illumination angle of a target time period;
a condition generating module 5404 configured to determine the first location condition and/or the second location condition of a target time period based on the illumination angle.
In an optional embodiment, further comprising:
a water accumulation determining module 54022, configured to, after the weather information and/or the time information of the target road are obtained to determine an illumination angle of a target time period, obtain road water accumulation information of the target road based on the initial image information when the weather information and/or the time information satisfy a first weather condition;
the second shadow acquisition module 54044 is configured to determine second facility shadow information of the target road based on the road ponding information;
a third matching module 54046, configured to perform third matching processing on the second facility shadow information and the facility shadow information to obtain a third matching result;
a third determining module 54048, configured to determine that the road facility is missing if the third matching result does not satisfy the first matching condition.
In an optional embodiment, the method further comprises:
a reference determining module 5002 for determining a road reference line of the target road and a facility reference line of the road facility through the object recognition model;
an included angle determining module 5004, configured to perform spatial included angle calculation on the road reference line and the facility reference line to obtain a reference included angle;
an ectopic determining module 5006 is configured to determine that the road facility has an ectopic position when the reference included angle is greater than the first threshold and smaller than the second threshold.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.
In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention further provide an electronic device, comprising a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details of this embodiment are not repeated herein.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for identifying a missing road facility, comprising:
acquiring initial image information of a target road;
determining facility shadow information of a target area through a pre-trained object recognition model, wherein the target road comprises the target area, and the facility shadow information comprises shadow information of road facilities of the target road;
under the condition that the facility shadow information meets a first position condition, performing first matching processing on the facility shadow information and preset facility reference information to obtain a first matching result;
determining that the road facility is missing if the first matching result does not satisfy a first matching condition.
2. The method of claim 1, wherein after determining facility shadow information for a target area by a pre-trained object recognition model, the method further comprises:
under the condition that the facility shadow information meets a second position condition, performing second matching processing on the facility shadow information and the facility reference information to obtain a second matching result;
and determining that the road facilities are missing if the second matching result meets a first matching condition.
3. The method of claim 2, wherein prior to determining facility shadow information for a target region by a pre-trained object recognition model, the method further comprises:
acquiring weather information and/or time information of the target road to determine an illumination angle of a target time period;
determining the first location condition and/or the second location condition for a target time period based on the illumination angle.
4. The method of claim 3, wherein after the obtaining weather information and/or time information of the target road to determine the illumination angle of the target time period, the method further comprises:
acquiring road ponding information of the target road based on the initial image information under the condition that the weather information and/or the time information meet a first weather condition;
determining second facility shadow information of the target road based on the road ponding information;
performing third matching processing on the second facility shadow information and the facility shadow information to obtain a third matching result;
determining that the asset is missing if the third matching result does not satisfy the first matching condition.
5. The method of claim 1, further comprising:
determining a road reference line of the target road and a facility reference line of the road facility through the object recognition model;
calculating a space included angle of the road reference line and the facility reference line to obtain a reference included angle;
and determining that the road facility has the dislocation under the condition that the reference included angle is larger than a first threshold value and smaller than a second threshold value.
6. A road facility loss identification device, comprising:
the image acquisition module is used for acquiring initial image information of a target road;
an information determination module, configured to determine facility shadow information of a target area through a pre-trained object recognition model, where the target road includes the target area, and the facility shadow information includes shadow information of road facilities of the target road;
the first matching module is used for performing first matching processing on the facility shadow information and preset facility reference information under the condition that the facility shadow information meets a first position condition so as to obtain a first matching result;
and the first result judging module is used for determining that the road facilities are missing under the condition that the first matching result does not meet a first matching condition.
7. The apparatus of claim 6, further comprising:
a second matching module, configured to, after determining facility shadow information of a target area through the pre-trained object recognition model, perform second matching processing on the facility shadow information and the facility reference information when the facility shadow information satisfies a second position condition, so as to obtain a second matching result;
and the second result judging module is used for determining that the road facilities are missing under the condition that the second matching result meets the first matching condition.
8. The apparatus of claim 7, further comprising:
the weather information acquisition module is used for acquiring weather information and/or time information of the target road to determine an illumination angle of a target time period before determining facility shadow information of a target area through the pre-trained object recognition model;
a condition generating module for determining the first position condition and/or the second position condition of a target time period based on the illumination angle.
9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 5 when executed.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211496211.XA CN115631356B (en) | 2022-11-28 | 2022-11-28 | Method and device for identifying missing of road facility, storage medium and electronic device |
Applications Claiming Priority (1)
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