CN113642521B - Traffic light identification quality evaluation method and device and electronic equipment - Google Patents
Traffic light identification quality evaluation method and device and electronic equipment Download PDFInfo
- Publication number
- CN113642521B CN113642521B CN202111020101.1A CN202111020101A CN113642521B CN 113642521 B CN113642521 B CN 113642521B CN 202111020101 A CN202111020101 A CN 202111020101A CN 113642521 B CN113642521 B CN 113642521B
- Authority
- CN
- China
- Prior art keywords
- traffic light
- score
- identified
- color
- identification algorithm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000013441 quality evaluation Methods 0.000 title abstract description 12
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 101
- 230000015654 memory Effects 0.000 claims description 17
- 238000012360 testing method Methods 0.000 claims description 10
- 239000003086 colorant Substances 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000012549 training Methods 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
Abstract
The invention provides a traffic light identification quality evaluation method, a traffic light identification quality evaluation device and electronic equipment, which comprise the following steps: determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light; if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score; counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light; and determining the score of the traffic light recognition quality according to the first score and the second score. The method can quantitatively judge the traffic light recognition quality recognized by the traffic light recognition algorithm, further determine the effectiveness of the traffic light recognition algorithm, and solve the technical problem that the recognition quality of the traffic light cannot be judged in the prior art.
Description
Technical Field
The invention relates to the technical field of traffic light identification, in particular to a traffic light identification quality evaluation method, a traffic light identification quality evaluation device and electronic equipment.
Background
With the wider and wider application of intelligent technology, the automatic driving technology is generated, and during automatic driving, the identification of traffic lights has a very important influence on automatic driving of vehicles.
The advanced driving auxiliary system utilizes sensors, such as millimeter wave radar, laser radar, cameras and satellite navigation, which are arranged on the vehicle, to sense the surrounding environment in the running process of the vehicle, collect data, identify, detect and track static and dynamic objects, and combine with navigator map data to perform systematic operation and analysis, thereby leading a driver to predict possible danger in advance and effectively increasing the safety. Currently, vision-based urban traffic light identification is always one of the core contents of auxiliary driving research, and certain characteristics of traffic light images are generally detected through a traffic light identification algorithm, so that the traffic light state is identified. However, the identification quality of the traffic light cannot be judged in the prior art, and the validity of the traffic light identification algorithm cannot be determined.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, a device and an electronic device for evaluating the identification quality of a traffic light, so as to alleviate the technical problem that the identification quality of the traffic light cannot be evaluated in the prior art.
In a first aspect, an embodiment of the present invention provides a method for evaluating traffic light identification quality, including:
determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score;
counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light;
and determining the score of the traffic light identification quality according to the first score and the second score.
Further, the method further comprises:
and if the color identified by the traffic light identification algorithm is incorrect, determining the score of the traffic light identification quality as a preset score.
Further, determining whether the color identified by the traffic light identification algorithm is correct according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light comprises the following steps:
obtaining a test dataset, wherein the test dataset comprises: traffic light images and colors of marked traffic lights corresponding to the traffic light images;
carrying out traffic light identification on the traffic light image by adopting the traffic light identification algorithm to obtain the color of the traffic light corresponding to the traffic light image;
and determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light corresponding to the traffic light image and the color of the marked traffic light corresponding to the traffic light image.
Further, calculating the overlapping ratio of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light includes:
acquiring a surrounding frame of the traffic light, which is obtained by the traffic light identification algorithm for identifying the traffic light image;
calculating the intersection ratio of the identified surrounding frame of the traffic light and the corresponding marked surrounding frame of the traffic light;
and taking the cross ratio as the overlapping rate.
Further, calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light includes:
calculating a ratio between the number of pixels and the total number of pixels;
the ratio is taken as the second score.
Further, counting the number of pixels of the correct color identified by the traffic light identification algorithm, including:
acquiring a pixel position of a pixel to be identified, wherein the pixel position is determined according to the marked traffic light image;
determining a corresponding target pixel in the image to be detected according to the pixel position;
and counting the number of pixels of the color of the traffic light identified by the traffic light identification algorithm in the target pixel according to the HSV value of the target pixel.
Further, the method further comprises:
and if the score of the traffic light identification quality is smaller than a preset threshold value, carrying out optimization training on the traffic light identification algorithm.
In a second aspect, an embodiment of the present invention further provides an apparatus for evaluating traffic light identification quality, including:
the first determining unit is used for determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
the calculating unit is used for calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light if the traffic light identification algorithm is correct, and taking the overlapping rate as a first score;
the statistics and calculation unit is used for counting the number of pixels of the pixels with the correct colors identified by the traffic light identification algorithm and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic lights;
and the second determining unit is used for determining the score of the traffic light identification quality according to the first score and the second score.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of the method according to any one of the first aspects when the processor executes the computer program.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing machine-executable instructions which, when invoked and executed by a processor, cause the processor to perform the method of any one of the first aspects.
In an embodiment of the present invention, a method for evaluating traffic light recognition quality is provided, including: determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light; if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score; meanwhile, counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light; and finally, determining the score of the traffic light recognition quality according to the first score and the second score. According to the method for evaluating the traffic light recognition quality, disclosed by the invention, the traffic light recognition quality recognized by the traffic light recognition algorithm can be quantitatively evaluated, so that the effectiveness of the traffic light recognition algorithm is determined, and the technical problem that the recognition quality of the traffic light cannot be evaluated in the prior art is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for evaluating traffic light recognition quality according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for determining whether a color identified by a traffic light identification algorithm is correct according to a color of a traffic light identified by the traffic light identification algorithm and a color of a marked traffic light according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for calculating the overlapping rate of a surrounding frame of a traffic light identified by a traffic light identification algorithm and a surrounding frame of a marked traffic light according to an embodiment of the present invention;
fig. 4 is a schematic diagram of an evaluation device for traffic light recognition quality according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the identification quality of the traffic light cannot be judged, and the validity of the traffic light identification algorithm cannot be determined.
Based on the above, the embodiment provides a method for evaluating the traffic light identification quality, which can quantitatively judge the traffic light identification quality identified by the traffic light identification algorithm, so as to determine the validity of the traffic light identification algorithm.
Embodiments of the present invention are further described below with reference to the accompanying drawings.
Embodiment one:
according to an embodiment of the present invention, there is provided an embodiment of a method for evaluating traffic light recognition quality, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that shown or described herein.
Fig. 1 is a flowchart of a method for evaluating traffic light recognition quality according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
in the embodiment of the invention, the traffic light recognition algorithm is a traffic light recognition algorithm after training.
Step S104, if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score;
step S106, counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light;
and S108, determining the score of the traffic light identification quality according to the first score and the second score.
In an embodiment of the present invention, a method for evaluating traffic light recognition quality is provided, including: determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light; if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score; meanwhile, counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light; and finally, determining the score of the traffic light recognition quality according to the first score and the second score. According to the method for evaluating the traffic light recognition quality, disclosed by the invention, the traffic light recognition quality recognized by the traffic light recognition algorithm can be quantitatively evaluated, so that the effectiveness of the traffic light recognition algorithm is determined, and the technical problem that the recognition quality of the traffic light cannot be evaluated in the prior art is solved.
The above-mentioned content briefly describes the method for evaluating the identification quality of the traffic light of the present invention, and the detailed description will be given below on the specific content related thereto.
In an alternative embodiment of the invention, the method further comprises: if the color identified by the traffic light identification algorithm is incorrect, determining the score of the traffic light identification quality as a preset score.
The preset score is a preset low score, and the preset score is not particularly limited in the embodiment of the present invention.
In an alternative embodiment of the present invention, referring to fig. 2, determining whether the color identified by the traffic light identification algorithm is correct according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light specifically includes the following steps:
step S201, acquiring a test data set, where the test data set includes: traffic light images and colors of marked traffic lights corresponding to the traffic light images;
step S202, traffic light identification is carried out on traffic light images by adopting a traffic light identification algorithm, and the colors of traffic lights corresponding to the traffic light images are obtained;
step S203, whether the color identified by the traffic light identification algorithm is correct or not is determined according to the color of the traffic light corresponding to the traffic light image and the color of the marked traffic light corresponding to the traffic light image.
In an alternative embodiment of the present invention, referring to fig. 3, the overlapping ratio of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light is calculated, and specifically includes the following steps:
step S301, acquiring a surrounding frame of a traffic light, which is obtained by identifying a traffic light image by a traffic light identification algorithm;
step S302, calculating the intersection ratio of the identified surrounding frame of the traffic light and the surrounding frame of the corresponding marked traffic light;
step S303, the overlap ratio is used as the overlap ratio.
In an alternative embodiment of the present invention, counting the number of pixels of the correct color identified by the traffic light identification algorithm specifically includes the following steps:
(1) Acquiring a pixel position of a pixel to be identified, wherein the pixel position is determined according to the marked traffic light image;
for example, if the marked traffic light image is a traffic light image marked with a red light, determining the pixel position of each pixel in the red light region, that is, the pixel position of the pixel to be identified, where the marked traffic light image may be the marked traffic light image in the test data set.
(2) Determining a corresponding target pixel in the image to be detected according to the pixel position;
the image to be detected is an image to be detected corresponding to the marked traffic light image, namely, the traffic light image before marking the marked traffic light image (the non-marked traffic light image can be an image in the test data set), and the corresponding target pixel is a target pixel corresponding to the pixel position.
(3) And counting the number of pixels of the color of the traffic light identified by the traffic light identification algorithm in the target pixel according to the HSV value of the target pixel.
For example, if the traffic light identified by the traffic light identification algorithm is red, the number of pixels in the target pixel, which are red pixels, is counted according to the HSV value of the target pixel, that is, the number of pixels in the correct color identified by the traffic light identification algorithm.
In an alternative embodiment of the present invention, the second score is calculated according to the number of pixels and the total number of pixels of the corresponding traffic light, and specifically comprises the following steps:
A. calculating a ratio between the number of pixels and the total number of pixels;
B. the ratio was taken as the second score.
In an alternative embodiment of the present invention, after scoring the traffic light identification quality, the method further comprises:
and if the score of the traffic light identification quality is smaller than a preset threshold value, carrying out optimization training on the traffic light identification algorithm.
The traffic light identification quality evaluation method can quantitatively judge the traffic light identification quality identified by the traffic light identification algorithm, so that the effectiveness of the traffic light identification algorithm is determined, and the method is simple, efficient, convenient and quick.
Embodiment two:
the embodiment of the invention also provides a traffic light identification quality evaluation device which is mainly used for executing the traffic light identification quality evaluation method provided in the first embodiment of the invention, and the traffic light identification quality evaluation device provided in the embodiment of the invention is specifically introduced below.
Fig. 4 is a schematic diagram of an evaluation device for traffic light recognition quality according to an embodiment of the present invention, as shown in fig. 4, the device mainly includes: a first determination unit 10, a calculation unit 20, a statistics and calculation unit 30, and a second determination unit 40, wherein:
the first determining unit is used for determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
the calculating unit is used for calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light if the traffic light identification algorithm is correct, and taking the overlapping rate as a first score;
the statistics and calculation unit is used for counting the number of pixels of the correct color identified by the traffic light identification algorithm and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light;
and the second determining unit is used for determining the score of the traffic light identification quality according to the first score and the second score.
In an embodiment of the present invention, an evaluation device for traffic light identification quality is provided, including: determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light; if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score; meanwhile, counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light; and finally, determining the score of the traffic light recognition quality according to the first score and the second score. According to the description, the traffic light identification quality evaluation device disclosed by the invention can quantitatively judge the traffic light identification quality identified by the traffic light identification algorithm, so that the validity of the traffic light identification algorithm is determined, and the technical problem that the identification quality of the traffic light cannot be judged in the prior art is solved.
Optionally, the device is further configured to: if the color identified by the traffic light identification algorithm is incorrect, determining the score of the traffic light identification quality as a preset score.
Optionally, the first determining unit is further configured to: obtaining a test data set, wherein the test data set comprises: traffic light images and colors of marked traffic lights corresponding to the traffic light images; carrying out traffic light identification on the traffic light image by adopting a traffic light identification algorithm to obtain the color of the traffic light corresponding to the traffic light image; and determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light corresponding to the traffic light image and the color of the marked traffic light corresponding to the traffic light image.
Optionally, the computing unit is further configured to: acquiring a surrounding frame of a traffic light, which is obtained by identifying the traffic light image by a traffic light identification algorithm; calculating the intersection ratio of the identified surrounding frame of the traffic light and the surrounding frame of the corresponding marked traffic light; the overlap ratio is taken as the overlap ratio.
Optionally, the statistics and computation unit is further configured to: calculating a ratio between the number of pixels and the total number of pixels; the ratio was taken as the second score.
Optionally, the statistics and computation unit is further configured to: acquiring a pixel position of a pixel to be identified, wherein the pixel position is determined according to the marked traffic light image; determining a corresponding target pixel in the image to be detected according to the pixel position; and counting the number of pixels of the color of the traffic light identified by the traffic light identification algorithm in the target pixel according to the HSV value of the target pixel.
Optionally, the device is further configured to: and if the score of the traffic light identification quality is smaller than a preset threshold value, carrying out optimization training on the traffic light identification algorithm.
The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
As shown in fig. 5, an electronic device 600 provided in an embodiment of the present application includes: the system comprises a processor 601, a memory 602 and a bus, wherein the memory 602 stores machine-readable instructions executable by the processor 601, when the electronic device is running, the processor 601 and the memory 602 communicate through the bus, and the processor 601 executes the machine-readable instructions to execute the steps of the method for evaluating the identification quality of the traffic lights.
Specifically, the memory 602 and the processor 601 can be general-purpose memories and processors, and are not particularly limited herein, and the above-described traffic light recognition quality evaluation method can be executed when the processor 601 runs a computer program stored in the memory 602.
The processor 601 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 601 or instructions in the form of software. The processor 601 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 602, and the processor 601 reads information in the memory 602 and performs the steps of the above method in combination with its hardware.
Corresponding to the above method for evaluating traffic light identification quality, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores machine executable instructions, and the computer executable instructions, when being called and run by a processor, cause the processor to run the steps of the above method for evaluating traffic light identification quality.
The evaluation device for the traffic light identification quality provided by the embodiment of the application can be specific hardware on equipment or software or firmware installed on the equipment, and the like. The device provided in the embodiments of the present application has the same implementation principle and technical effects as those of the foregoing method embodiments, and for a brief description, reference may be made to corresponding matters in the foregoing method embodiments where the device embodiment section is not mentioned. It will be clear to those skilled in the art that, for convenience and brevity, the specific operation of the system, apparatus and unit described above may refer to the corresponding process in the above method embodiment, which is not described in detail herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
As another 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 various 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.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments provided in the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units 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 may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing an electronic device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the vehicle marking 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 (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that: like reference numerals and letters in the following figures denote like items, and thus once an item is defined in one figure, no further definition or explanation of it is required in the following figures, and furthermore, the terms "first," "second," "third," etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present application, and are not intended to limit the scope of the present application, but the present application is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, the present application is not limited thereto. Any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or make equivalent substitutions for some of the technical features within the technical scope of the disclosure of the present application; such modifications, changes or substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application. Are intended to be encompassed within the scope of this application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The method for evaluating the traffic light identification quality is characterized by comprising the following steps of:
determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
if the traffic light is correct, calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light, and taking the overlapping rate as a first score;
counting the number of pixels of the correct color identified by the traffic light identification algorithm, and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic light;
and determining the score of the traffic light identification quality according to the first score and the second score.
2. The method according to claim 1, wherein the method further comprises:
and if the color identified by the traffic light identification algorithm is incorrect, determining the score of the traffic light identification quality as a preset score.
3. The method of claim 1, wherein determining whether the traffic light identification algorithm identifies a correct color based on the traffic light identification algorithm identified color and the annotated traffic light color comprises:
obtaining a test dataset, wherein the test dataset comprises: traffic light images and colors of marked traffic lights corresponding to the traffic light images;
carrying out traffic light identification on the traffic light image by adopting the traffic light identification algorithm to obtain the color of the traffic light corresponding to the traffic light image;
and determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light corresponding to the traffic light image and the color of the marked traffic light corresponding to the traffic light image.
4. A method according to claim 3, wherein calculating the overlap ratio of the bounding box of the traffic light identified by the traffic light identification algorithm and the bounding box of the marked traffic light comprises:
acquiring a surrounding frame of the traffic light, which is obtained by the traffic light identification algorithm for identifying the traffic light image;
calculating the intersection ratio of the identified surrounding frame of the traffic light and the corresponding marked surrounding frame of the traffic light;
and taking the cross ratio as the overlapping rate.
5. The method of claim 1, wherein calculating a second score from the number of pixels and the total number of pixels of the corresponding traffic light comprises:
calculating a ratio between the number of pixels and the total number of pixels;
the ratio is taken as the second score.
6. The method of claim 1, wherein counting the number of pixels of the correct color identified by the traffic light identification algorithm comprises:
acquiring a pixel position of a pixel to be identified, wherein the pixel position is determined according to the marked traffic light image;
determining a corresponding target pixel in the image to be detected according to the pixel position;
and counting the number of pixels of the color of the traffic light identified by the traffic light identification algorithm in the target pixel according to the HSV value of the target pixel.
7. The method according to claim 1, wherein the method further comprises:
and if the score of the traffic light identification quality is smaller than a preset threshold value, carrying out optimization training on the traffic light identification algorithm.
8. An evaluation device for traffic light recognition quality is characterized by comprising:
the first determining unit is used for determining whether the color identified by the traffic light identification algorithm is correct or not according to the color of the traffic light identified by the traffic light identification algorithm and the color of the marked traffic light;
the calculating unit is used for calculating the overlapping rate of the surrounding frame of the traffic light identified by the traffic light identification algorithm and the surrounding frame of the marked traffic light if the traffic light identification algorithm is correct, and taking the overlapping rate as a first score;
the statistics and calculation unit is used for counting the number of pixels of the pixels with the correct colors identified by the traffic light identification algorithm and calculating a second score according to the number of pixels and the total number of pixels of the corresponding traffic lights;
and the second determining unit is used for determining the score of the traffic light identification quality according to the first score and the second score.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of the preceding claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium storing machine executable instructions which, when invoked and executed by a processor, cause the processor to perform the method of any one of the preceding claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111020101.1A CN113642521B (en) | 2021-09-01 | 2021-09-01 | Traffic light identification quality evaluation method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111020101.1A CN113642521B (en) | 2021-09-01 | 2021-09-01 | Traffic light identification quality evaluation method and device and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113642521A CN113642521A (en) | 2021-11-12 |
| CN113642521B true CN113642521B (en) | 2024-02-09 |
Family
ID=78424753
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111020101.1A Active CN113642521B (en) | 2021-09-01 | 2021-09-01 | Traffic light identification quality evaluation method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113642521B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115311885B (en) * | 2022-07-29 | 2024-04-12 | 上海商汤临港智能科技有限公司 | Evaluation method, system, electronic equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109741406A (en) * | 2019-01-03 | 2019-05-10 | 广州广电银通金融电子科技有限公司 | A kind of body color recognition methods under monitoring scene |
| KR20190123858A (en) * | 2018-04-25 | 2019-11-04 | 모루시스템 주식회사 | Smart traffic signal control center algorithm evaluation method and device thereof |
| CN110738132A (en) * | 2019-09-23 | 2020-01-31 | 中国海洋大学 | target detection quality blind evaluation method with discriminant perception capability |
| CN111402610A (en) * | 2020-03-23 | 2020-07-10 | 东软睿驰汽车技术（沈阳）有限公司 | Method, device, equipment and storage medium for identifying lighting state of traffic light |
| CN111582216A (en) * | 2020-05-15 | 2020-08-25 | 安徽师范大学 | Unmanned vehicle-mounted traffic signal lamp identification system and method |
| CN111797993A (en) * | 2020-06-16 | 2020-10-20 | 东软睿驰汽车技术（沈阳）有限公司 | Evaluation method and device for deep learning model, electronic equipment and storage medium |
| CN111882549A (en) * | 2020-07-31 | 2020-11-03 | 陕西长岭软件开发有限公司 | Automatic detection and identification method and system for grayish green small foreign fibers |
| CN112560737A (en) * | 2020-12-22 | 2021-03-26 | 清华大学苏州汽车研究院（吴江） | Signal lamp identification method and device, storage medium and electronic equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10586447B2 (en) * | 2017-07-25 | 2020-03-10 | International Business Machines Corporation | Smart traffic signal methods and systems |
-
2021
- 2021-09-01 CN CN202111020101.1A patent/CN113642521B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20190123858A (en) * | 2018-04-25 | 2019-11-04 | 모루시스템 주식회사 | Smart traffic signal control center algorithm evaluation method and device thereof |
| CN109741406A (en) * | 2019-01-03 | 2019-05-10 | 广州广电银通金融电子科技有限公司 | A kind of body color recognition methods under monitoring scene |
| CN110738132A (en) * | 2019-09-23 | 2020-01-31 | 中国海洋大学 | target detection quality blind evaluation method with discriminant perception capability |
| CN111402610A (en) * | 2020-03-23 | 2020-07-10 | 东软睿驰汽车技术（沈阳）有限公司 | Method, device, equipment and storage medium for identifying lighting state of traffic light |
| CN111582216A (en) * | 2020-05-15 | 2020-08-25 | 安徽师范大学 | Unmanned vehicle-mounted traffic signal lamp identification system and method |
| CN111797993A (en) * | 2020-06-16 | 2020-10-20 | 东软睿驰汽车技术（沈阳）有限公司 | Evaluation method and device for deep learning model, electronic equipment and storage medium |
| CN111882549A (en) * | 2020-07-31 | 2020-11-03 | 陕西长岭软件开发有限公司 | Automatic detection and identification method and system for grayish green small foreign fibers |
| CN112560737A (en) * | 2020-12-22 | 2021-03-26 | 清华大学苏州汽车研究院（吴江） | Signal lamp identification method and device, storage medium and electronic equipment |
Non-Patent Citations (4)
| Title |
|---|
| Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition;Gomez-Moreno 等;《IEEE Transactions on Intelligent Transportation Systems》;第11卷(第04期);917-930 * |
| Machine Vision Based Traffic Sign Detection Methods: Review, Analyses and Perspectives;Liu Chunsheng 等;《IEEE Access》;第07卷;86578-86596 * |
| 基于YOLO的交通标志检测算法;雷蕾 等;《现代计算机》;第27卷(第24期);93-99 * |
| 基于车载视觉的红绿灯自动识别技术研究;乔允浩;《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》(第02期);C035-305 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113642521A (en) | 2021-11-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109740469B (en) | Lane line detection method, lane line detection device, computer device, and storage medium | |
| CN109766793B (en) | Data processing method and device | |
| CN111814746A (en) | Method, device, equipment and storage medium for identifying lane line | |
| CN113642521B (en) | Traffic light identification quality evaluation method and device and electronic equipment | |
| CN112461257A (en) | Method and device for determining lane line information | |
| CN113762406A (en) | Data mining method and device and electronic equipment | |
| CN112434657A (en) | Drift carrier detection method, device, program, and computer-readable medium | |
| Alpar et al. | Intelligent collision warning using license plate segmentation | |
| CN108734161B (en) | Method, device and equipment for identifying prefix number area and storage medium | |
| CN114721376A (en) | Road condition identification method, device, equipment and medium for unmanned mine car | |
| CN114705121A (en) | Vehicle pose measuring method and device, electronic equipment and storage medium | |
| CN113591543B (en) | Traffic sign recognition method, device, electronic equipment and computer storage medium | |
| CN114842322A (en) | Method and device for detecting remnant, electronic device and computer-readable storage medium | |
| CN116503695B (en) | Training method of target detection model, target detection method and device | |
| CN110765816B (en) | Vehicle line-pressing violation detection method and device and electronic equipment | |
| CN114627651B (en) | Pedestrian protection early warning method and device, electronic equipment and readable storage medium | |
| CN115631477B (en) | Target identification method and terminal | |
| CN111860512A (en) | Vehicle identification method and device, electronic equipment and computer readable storage medium | |
| CN113642533B (en) | Lane level positioning method and electronic equipment | |
| CN111038496B (en) | Vehicle early warning method and device, terminal device and computer readable storage medium | |
| CN112101139B (en) | Human shape detection method, device, equipment and storage medium | |
| CN111597959B (en) | Behavior detection method and device and electronic equipment | |
| CN116664658B (en) | Obstacle detection method and device and terminal equipment | |
| CN115690028A (en) | Road pit detection method and device, electronic equipment and storage medium | |
| CN115620257A (en) | Method and device for detecting influence of road snow, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |