Method and device for testing color uniformity of face recognition camera

Abstract

The invention discloses a face recognition camera color uniformity test method and device. The test method comprises the steps that target demand test parameters of a to-be-tested camera are determined; determining a plurality of test cards with an arrangement sequence according to the target demand test parameters; determining first color deviation data of the to-be-tested camera under the first test card according to the arrangement sequence; determining whether the first color deviation data meets requirements or not according to the target demand test parameters; when the first color deviation data does not meet the requirement, the test of the camera to be tested is stopped, and the test result of the camera to be tested is an unqualified product; when the first color deviation data meets the requirement, repeating the above steps according to the arrangement sequence, and sequentially determining the color deviation data of the to-be-tested camera under each test card; and when the color deviation data meet the requirements, determining that the test result of the to-be-tested camera is a qualified product. According to the invention, whether the color uniformity of the camera is qualified can be automatically determined.

Description

Technical Field

[0001] The present invention relates to the technical field of computer vision image processing, and in particular to a method and device for testing color uniformity of a face recognition camera. Background Art

[0002] In the fields of high-end photography, scientific research, industrial inspection, etc., customers have extremely high requirements for the imaging quality of facial recognition cameras. Color uniformity testing is one of the key factors to ensure that the product meets these requirements. Poor color uniformity of the camera may lead to a series of problems such as color distortion, increased difficulty in image processing, and reduced image clarity.

[0003] The traditional color uniformity test of facial recognition cameras is to manually take a photo of a pure color uniformity card with the camera to be tested, then open the photo with Photoshop software and manually process the center and edge corners to obtain the corresponding color values, and then determine whether their color values ​​are equal to screen out unqualified facial recognition camera products.

[0004] However, the disadvantages of manual measurement and calculation are high production costs, measurement and calculation vary from person to person, and there may be non-standard verification results, which affects the overall production quality and reduces customer satisfaction with the product. At the same time, when facing a large order volume, a large amount of labor and time costs are required, the efficiency is very low, and the test accuracy is not high, which does not meet the needs of modern manufacturing for efficient and high-quality products. Summary of the invention

[0005] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a face recognition camera color uniformity test method, which can automatically perform color uniformity test on the face recognition camera, and solve the problems of high cost and low test efficiency caused by manual measurement and manual calculation.

[0006] In order to solve the above problems, the present invention is implemented according to the following scheme:

[0007] A method for testing color uniformity of a face recognition camera is provided, comprising:

[0008] Determine the target required test parameters of the camera to be tested;

[0009] Determining a plurality of test cards having an arrangement order according to the target required test parameters;

[0010] Determine the first color deviation data of the camera to be tested under the first test card according to the arrangement order;

[0011] Determining whether the first color deviation data meets the requirements according to the target requirement test parameters;

[0012] When the first color deviation data does not meet the requirements, the test of the camera to be tested is stopped, and the test result of the camera to be tested is an unqualified product;

[0013] When the first color deviation data meets the requirements, the above steps are repeated according to the arrangement order to determine the color deviation data of the camera to be tested under each test card in turn; when the color deviation data all meet the requirements, the test result of the camera to be tested is a qualified product.

[0014] Compared with the prior art, the beneficial effects of the color uniformity testing method for a face recognition camera of the present invention are as follows: by automatically generating multiple test cards and automatically reading color deviation data, it is automatically determined whether the color uniformity of the camera is qualified, ensuring that the camera products leaving the factory have high-quality production control, thereby improving customer satisfaction with the product, and reducing testing costs and improving testing efficiency.

[0015] Optionally, the target requirement test parameter includes a target adjustment factor;

[0016] Determine the target test parameters of the camera to be tested, including:

[0017] When the received adjustment factor is greater than or equal to a preset threshold, determining the received adjustment factor as the target adjustment factor;

[0018] When the received adjustment factor is less than the preset threshold, the adjustment factor is received again until the received adjustment factor is greater than or equal to the preset threshold, and the received adjustment factor is determined as the target adjustment factor.

[0019] Optionally, the target demand test parameter also includes a target adjustment interval;

[0020] Determine the target test parameters of the camera to be tested, including:

[0021] When the received adjustment interval meets the preset condition, determining the received adjustment interval as the target adjustment interval;

[0022] When the received adjustment interval does not meet the preset condition, the adjustment interval is received again until the received adjustment interval meets the preset condition, and the received adjustment interval is determined as the target adjustment interval.

[0023] Optionally, determining a plurality of test cards having an arrangement order according to the target requirement test parameter includes:

[0024] Determining the number of cards to be tested for representing the number of test cards according to the upper adjustment limit value and the lower adjustment limit value of the target adjustment interval;

[0025] Determine pure color uniformity cards with different color parameters according to the target adjustment range and the number of cards to be tested;

[0026] According to the color parameters corresponding to the pure color uniformity cards, the pure color uniformity cards are sorted from small to large to obtain a plurality of test cards with an arrangement order.

[0027] Optionally, determining the first color deviation data of the camera to be tested under the first test card according to the arrangement order includes:

[0028] Setting the parameters of the camera to be tested to optimal parameters;

[0029] The camera to be tested shoots the first test card with the optimal parameters to obtain a test image;

[0030] The first color deviation data is determined according to the test image and the color parameters corresponding to the first test card.

[0031] Optionally, determining the first color deviation data according to the test image and the color parameters corresponding to the first test card includes:

[0032] Reading color data of the test image;

[0033] The first color deviation data is determined according to the color data and the color parameter.

[0034] Optionally, the color data includes center color data and edge color data;

[0035] Reading the color data of the test image includes:

[0036] The color data of the center point and the edge corner points of the test image are read to obtain the center color data for representing the color data of the center point of the test image and the edge color data for representing the color data of each edge corner point of the test image.

[0037] Optionally, determining whether the first color deviation data meets the requirement according to the target requirement test parameter includes:

[0038] When the first color deviation data is greater than the target adjustment factor, the first color deviation data does not meet the requirement;

[0039] When the first color deviation data is less than or equal to the target adjustment factor, the first color deviation data meets the requirement.

[0040] Optionally, also include:

[0041] Determine the number of qualified products and the number of unqualified products according to the test results of the camera to be tested;

[0042] The sum of the number of qualified products and the number of unqualified products is determined as the number of test cameras;

[0043] A test report is generated based on the number of qualified products and the number of test cameras, and the test report is the product qualification rate.

[0044] A computer device is also provided, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor to implement the color uniformity test method. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Flow chart of the testing method of the present invention. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0047] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0048] See also Figure 1 As shown, the present invention provides a method for testing color uniformity of a face recognition camera, comprising:

[0049] S1: Determine target requirement test parameters of the camera to be tested, wherein the target requirement parameters include a target adjustment factor and a target adjustment interval. Determining the target requirement test parameters of the camera to be tested includes: determining the target adjustment factor and determining the target adjustment interval.

[0050] Determining the target regulatory factor includes the following steps:

[0051] Receive the adjustment factor sent by the tester, and automatically check whether the received adjustment factor meets the preset threshold; when the received adjustment factor is greater than or equal to the preset threshold, determine the received adjustment factor as the target adjustment factor; when the received adjustment factor is less than the preset threshold, report an error, notify the tester to resend the adjustment factor, and receive the adjustment factor resent by the tester until the received adjustment factor is greater than or equal to the preset threshold, then determine the received adjustment factor as the target adjustment factor.

[0052] The target adjustment factor is used to indicate the maximum color deviation allowed in the color uniformity test of the camera. The purpose of determining the target adjustment factor is to decouple the entire project. By adjusting the numerical value of the adjustment factor, the strictness of the color uniformity test can be adjusted to better meet the product needs of different customers. The smaller the adjustment factor, the stricter the color uniformity test of the camera, and the camera needs to meet higher requirements to be judged as a qualified product.

[0053] In order to ensure the validity and rationality of the adjustment factor and avoid invalid or erroneous input affecting the accuracy of the test results, the preset threshold of the present invention is 0; in the present invention, the smaller the value of the target adjustment factor, the higher the customer's requirements for the product; in the actual testing process, the size of the target adjustment factor can be adjusted according to the customer's requirements for the product. For example, the default adjustment factor is 0.0001. If the customer's requirements for the product result are twice as stringent, the tester only needs to set the target adjustment factor to half of the default adjustment factor on the basis of the default adjustment factor, that is, to set the target adjustment factor to 0.0001÷2=0.00005; if the customer's requirements for the product result are 10 times more stringent, the tester only needs to set the target adjustment factor to one tenth of the default adjustment factor on the basis of the default adjustment factor, that is, to set the target adjustment factor to 0.0001÷10=0.00001.

[0054] Determining the target adjustment range includes the following steps:

[0055] Receive the adjustment interval sent by the tester, and automatically check whether the received adjustment interval meets the preset conditions. When the received adjustment interval meets the preset conditions, the received adjustment interval is determined as the target adjustment interval; when the received adjustment interval does not meet the preset conditions, an error is reported, notifying the tester to resend the adjustment interval, and receiving the adjustment interval resent by the tester until the received adjustment interval meets the preset conditions, and the received adjustment interval is determined as the target adjustment interval.

[0056] Among them, the adjustment range includes an upper adjustment limit value and a lower adjustment limit value, and the color parameter is specifically an RGB value, and the value range of the RGB value is 0-255. Therefore, the preset condition is specifically that the upper adjustment limit value is greater than the lower adjustment limit value, and the upper adjustment limit value and the lower adjustment limit value are both integers in the range of 0-255.

[0057] S2: According to the target test parameters, determine multiple test cards with an arrangement order, including:

[0058] First, according to the upper and lower limits of the target adjustment interval, determine the number of cards to be tested that is used to represent the number of test cards. Specifically, the difference between the upper and lower limits is used as the number of cards to be tested. Assuming that the target adjustment interval is [start, end], the number of cards to be tested is (end-start+1), that is, (end-start+1) rounds of testing are required.

[0059] Next, according to the target adjustment range and the number of cards to be tested, determine the pure color uniformity cards with different color parameters, wherein the color parameters of the test card can be expressed as RGB (R, G, B), and the color parameters of the pure color uniformity card are the same as the three parameters R, G, and B, that is, the color parameters of the pure color uniformity card can be expressed as RGB (c, c, c), and the value range of c is an integer between 0 and 255.

[0060] Finally, according to the color parameters corresponding to the pure color uniformity cards, the pure color uniformity cards are sorted from small to large to obtain multiple test cards with an arrangement order. Assume that there are N test cards with color parameters of RGB 1 (c 1 , c 1 , c 1 ), RGB 2 (c 2 , c 2 , c 2 ),...,RGB N (c N , c N , c N ), and use color parameters to represent each test card. 1 <c 2 <...<c N , then these N test cards with arrangement order are RGB 1 (c 1 , c 1 , c 1 ), RGB 2 (c 2 , c 2 , c 2 ),...,RGB N (c N, c N , c N ).

[0061] S3: Determine the first color deviation data of the camera to be tested under the first test card according to the arrangement order, including:

[0062] First, the parameters of the camera to be tested are set to the optimal parameters; the camera to be tested shoots the first test card with the optimal parameters to obtain a test image; the parameters of the camera to be tested are set to the optimal parameters to ensure the accuracy and reliability of the target data, and then to ensure the accuracy and reliability of the color uniformity test results, specifically, the ISP parameters of the camera to be tested are debugged to the optimal, and the relevant parameters of the camera to be tested are set to normal mode.

[0063] Camera ISP (Image Signal Processor) refers to a chip or module that specializes in processing digital images. It is mainly used to convert analog signals output by digital camera image sensors into digital signals, and perform various enhancements and processing on them to improve image quality and enhance image clarity, color reproduction, dynamic range and depth perception. By debugging the ISP parameters of the camera to be tested to the optimal state, it can be ensured that the camera to be tested outputs high-quality test images during the test process, so that the test images have high clarity, accurate color reproduction, rich dynamic range and low noise, and reduce color errors caused by image quality problems, thereby ensuring the accuracy and reliability of the test.

[0064] Set the relevant parameters of the camera to be tested to normal mode, that is, do not turn on special functions such as night mode, HDR, face enhancement, etc. when shooting. These special functions may affect the acquired test image, thereby affecting the color deviation data of the test image, and the accuracy and reliability of the test results cannot be guaranteed; by setting the relevant parameters of the camera to be tested to normal mode, it can be ensured that the color uniformity test results of the camera to be tested are not affected by these special functions, thereby ensuring the accuracy and reliability of the color uniformity test.

[0065] Next, first color deviation data is determined according to the test image and the color parameters corresponding to the first test card, including: firstly reading the color data of the test image to determine the first color deviation data according to the color data and the color parameters.

[0066] Among them, the color data includes center color data and edge color data; reading the color data of the test image includes: reading the color data of the center point and edge corner points of the test image, obtaining the center color data used to represent the color data of the center point of the test image, and the edge color data used to represent the color data of each edge corner point of the test image.

[0067] Assume that the color parameters corresponding to the first test card are RGB (c, c, c), and the center color data corresponding to the test and image obtained by the camera to be tested when shooting the first test card is RGB c (cr, cg, cb), edge color data is RGB n1 (nr 1 ,ng 1 , nb 1 ), RGB n2 (nr 1 ,ng 1 , nb 1 ), RGB n3 (nr 3 ,ng 3 , nb 3 ), RGB n4 (nr 4 ,ng 4 , nb 4 ).

[0068] Then the calculation formula of the first color deviation data corresponding to the test image is as follows:

[0069] R=|c-cr| 2 +|c-cg| 2 +|c-cb| 2 +|nr 1 -cr| 2 +|ng 1 -cg| 2 +|nb 1 -cb| 2

[0070] +|nr 2 -cr| 2 +|ng 2 -cg| 2 +|nb 2 -cb| 2

[0071] +|nr 3 -cr| 2 +|ng 3 -cg| 2 +|nb 3 -cb| 2

[0072] +|nr 4 -cr| 2 +|ng 4 -cg| 2 +|nb 4 -cb| 2

[0073] Wherein, R is the first color deviation data.

[0074] S4: Determine whether the first color deviation data meets the requirements according to the target demand test parameters, including: when the first color deviation data is greater than the target adjustment factor, this means that when the camera to be tested shoots the test card, the color difference between the center point and the edge corner exceeds the allowed range. Too large color deviation may cause image distortion, color unevenness and other problems, affecting the imaging quality of the camera, so it is considered that the first color deviation data does not meet the requirements; when the first color deviation data is less than or equal to the target adjustment factor, this means that when the camera to be tested shoots the test card, the color difference between the center point and the edge corner is within the allowed range and meets the requirements of customer or product standards, so it is considered that the first color deviation data meets the requirements.

[0075] S5.1: When the first color deviation data does not meet the requirements, the test of the camera to be tested is stopped, and the test result of the camera to be tested is an unqualified product; the color uniformity test is to ensure the consistency of the camera's performance under different color conditions. If the color deviation data of the camera in a certain round of testing (test card under a certain color parameter) exceeds the target adjustment factor, it means that the image taken by the camera under this color condition does not meet the requirements.

[0076] Since color uniformity is an overall indicator, if the camera fails to meet the standards under a certain color condition (a test card under a certain color parameter), it usually means that the camera may have similar problems under other color conditions. Therefore, in order to save testing time and resources, once the camera is found to fail in a certain round of testing, it can be directly judged as a failed product without the need for subsequent testing.

[0077] S5.2: When the first color deviation data meets the requirements, repeat the above steps according to the arrangement order to determine the color deviation data of the camera to be tested under each test card in turn; when the color deviation data all meet the requirements, the test result of the camera to be tested is a qualified product; the color uniformity test is to ensure the consistency of the camera's performance under different color conditions. Each test card represents a specific color condition. Multiple rounds of testing can cover a wider range of colors to ensure that the camera can maintain consistent performance under various color conditions.

[0078] Only by passing the test of all test cards can it be proved that the color deviation data of the camera under all test color conditions meets the requirements, thereby ensuring that its color uniformity meets the requirements of customer or product standards. The cumulative effect of multiple rounds of testing can effectively avoid the randomness of a single test result and improve the reliability and comprehensiveness of the test results.

[0079] After determining the test results of each camera to be tested in this test, the number of qualified products and the number of unqualified products are determined according to the test results of each camera to be tested. The number of qualified products and the number of unqualified products are added together to obtain the number of test cameras for this test, so as to automatically calculate the product qualification rate of this test, and the product qualification rate is used as a test report and fed back to the tester and the customer. The calculation formula of the product qualification rate is as follows:

[0080] R=(p÷s)×100%.

[0081] Among them, R is the product qualification rate, p is the number of qualified products, and s is the number of test cameras.

[0082] Next, the color uniformity test method is described in detail with specific values:

[0083] Assuming that the target adjustment factor is 0.001 and the target adjustment interval is [127, 128], the number of cards to be tested is 128-127+1=2, that is, there are two test cards in total, where the color parameters of the first test card are RGB (127, 127, 127), and the color parameters of the second test card are RGB (128, 128, 128).

[0084] After setting the parameters of the camera to be tested to the optimal parameters, the camera to be tested shoots the first test card with the optimal parameters to obtain a test image of the first test card with shooting color parameters of RGB (127, 127, 127), that is, the test image of the first round of testing, and automatically determines the color data of the test image.

[0085] Assume that the color data of the test image in the first round of testing is: center color data RGB c (127.01, 127.00, 126.99), the edge color data of the four corresponding edge corners are RGB n1 (127.00, 127.00, 127.00), RGB n2 (127.02, 127.01, 127.01), RGB n3 (127.00, 127.00, 127.00), RGB n4 (126.98, 127.00, 127.00).

[0086] Then the color deviation data corresponding to the test image is:

[0087] R=|127-127.01|2+|127-127.00|2+|127-126.99|2

[0088] +|127.00-127.01|2+|127.00-127.00|2+|127.00-126.99|2

[0089] +|127.02-127.01|2+|127.01-127.00|2+|127.01-126.99|2

[0090] +|127.00-127.01|2+|127.00-127.00|2+|127.00-126.99|2

[0091] +|126.98-127.01|2+|127.00-127.00|2+|127.00-126.99|2

[0092] =|0.01|2+|0|2+|0.01|2

[0093] +|0.01|2+|0|2+|0.01|2

[0094] +|0.01|2+|0.01|2+|0.02|2

[0095] +|0.01|2+|0|2+|0.01|2

[0096] +|0.03|2+|0|2+|0.01|2=0.0014

[0097] The color deviation data R=0.0014>0.001, that is, the color deviation data is greater than the target adjustment factor, and the test result of the first round of testing is unqualified. At this time, there is no need to conduct a second round of testing, that is, the camera to be tested does not need to shoot the second test card with color parameters of RGB (128, 128, 128), and the camera to be tested can be directly determined as an unqualified product.

[0098] If the customer's requirements for the product results are relaxed by half, the target adjustment factor can be set to 0.001*2=0.002. When the target adjustment factor is 0.002, the color deviation data R=0.0014<0.002, that is, the color deviation data is less than the target adjustment factor. The test results of the first round of tests are qualified. At this time, a second round of tests is required, that is, the camera to be tested needs to shoot a second test card with color parameters of RGB (128, 128, 128), and repeat the first round of testing process to determine the second round of test results. When the second round of test results are also qualified, the camera to be tested is determined to be a qualified product; when the second round of test results are unqualified, the camera to be tested is an unqualified product.

[0099] The present invention significantly improves the test efficiency and accuracy by automatically performing a color uniformity test on the camera to be tested. As long as the color deviation data of the camera to be tested exceeds the target adjustment factor in any round of testing, it can be determined as an unqualified product without the need for subsequent testing, thereby saving test time and resources.

[0100] The camera to be tested must pass all the test cards before it can be judged as a qualified product, ensuring that it can maintain consistent performance under various color conditions. This test method can not only quickly screen out unqualified products, but also comprehensively evaluate the color uniformity of the camera through multiple rounds of tests to ensure the reliability and consistency of product quality. At the same time, the flexible setting of the target adjustment factor enables the test method to adapt to the needs of different customers, further enhancing the market competitiveness of the product; at the same time, through the automated testing and report generation functions, it can greatly reduce labor costs and time costs.

[0101] The present invention also provides a computer device, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor to implement the above-mentioned color uniformity testing method.

[0102] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0103] The memory can be used to store the computer program or module, and the processor implements various functions of the color uniformity test method by running or executing the computer program or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0104] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for testing color uniformity of a face recognition camera, characterized in that: include: Determine the target required test parameters of the camera to be tested; Determining a plurality of test cards having an arrangement order according to the target required test parameters; Determine the first color deviation data of the camera to be tested under the first test card according to the arrangement order; Determining whether the first color deviation data meets the requirements according to the target requirement test parameters; When the first color deviation data does not meet the requirements, the test of the camera to be tested is stopped, and the test result of the camera to be tested is an unqualified product; When the first color deviation data meets the requirements, the above steps are repeated according to the arrangement order to determine the color deviation data of the camera to be tested under each test card in turn; when the color deviation data all meet the requirements, the test result of the camera to be tested is a qualified product.

2. The method for testing color uniformity of a face recognition camera according to claim 1, characterized in that: The target demand test parameters include target adjustment factors; Determine the target test parameters of the camera to be tested, including: When the received adjustment factor is greater than or equal to a preset threshold, determining the received adjustment factor as the target adjustment factor; When the received adjustment factor is less than the preset threshold, the adjustment factor is received again until the received adjustment factor is greater than or equal to the preset threshold, and the received adjustment factor is determined as the target adjustment factor.

3. The method for testing color uniformity of a face recognition camera according to claim 2, characterized in that: The target demand test parameters also include a target adjustment interval; Determine the target test parameters of the camera to be tested, including: When the received adjustment interval meets the preset condition, determining the received adjustment interval as the target adjustment interval; When the received adjustment interval does not meet the preset condition, the adjustment interval is received again until the received adjustment interval meets the preset condition, and the received adjustment interval is determined as the target adjustment interval.

4. The method for testing color uniformity of a face recognition camera according to claim 3, characterized in that: According to the target required test parameters, a plurality of test cards having an arrangement order are determined, including: Determining the number of cards to be tested for representing the number of test cards according to the upper adjustment limit value and the lower adjustment limit value of the target adjustment interval; Determine pure color uniformity cards with different color parameters according to the target adjustment range and the number of cards to be tested; According to the color parameters corresponding to the pure color uniformity cards, the pure color uniformity cards are sorted from small to large to obtain a plurality of test cards with an arrangement order.

5. The method for testing color uniformity of a face recognition camera according to claim 4, characterized in that: Determining the first color deviation data of the camera to be tested under the first test card according to the arrangement order includes: Setting the parameters of the camera to be tested to optimal parameters; The camera to be tested shoots the first test card with the optimal parameters to obtain a test image; The first color deviation data is determined according to the test image and the color parameters corresponding to the first test card.

6. The method for testing color uniformity of a face recognition camera according to claim 5, characterized in that: Determining the first color deviation data according to the test image and the color parameters corresponding to the first test card includes: Reading color data of the test image; The first color deviation data is determined according to the color data and the color parameter.

7. A method for testing color uniformity of a face recognition camera according to claim 6, characterized in that: The color data includes center color data and edge color data; Reading the color data of the test image includes: The color data of the center point and the edge corner points of the test image are read to obtain the center color data for representing the color data of the center point of the test image and the edge color data for representing the color data of each edge corner point of the test image.

8. The method for testing color uniformity of a face recognition camera according to claim 7, characterized in that: Determining whether the first color deviation data meets the requirements according to the target requirement test parameters includes: When the first color deviation data is greater than the target adjustment factor, the first color deviation data does not meet the requirement; When the first color deviation data is less than or equal to the target adjustment factor, the first color deviation data meets the requirement.

9. The method for testing color uniformity of a face recognition camera according to claim 1, characterized in that: Also includes: Determine the number of qualified products and the number of unqualified products according to the test results of the camera to be tested; The sum of the number of qualified products and the number of unqualified products is determined as the number of test cameras; A test report is generated based on the number of qualified products and the number of test cameras, and the test report is the product qualification rate.

10. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor to implement the color uniformity testing method according to any one of claims 1 to 9.

Images