Coverage detection method and device

Abstract

The invention provides a coverage detection method and device. The method comprises the following steps: acquiring an image containing a target product; preprocessing the image containing the target product to obtain a preprocessed image; performing image recognition on the preprocessed image to obtain a recognition result; and according to a preset detection standard and the identification result, performing coverage detection on the target area of the target product to obtain a coverage detection result. According to the invention, the obtained image containing the target product is preprocessed, then the image identification is carried out, and finally the coverage detection result is obtained by carrying out the coverage detection on the target area of the target product according to the preset detection standard and the identification result, so that a physical contact test does not need to be carried out manually by using a probe or a probe rod; displacement of the eye and face protection product is not caused, the testing precision is higher, and the advantages of saving labor cost and improving detection efficiency are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of coverage detection, and also to a coverage detection method and device. Background Art

[0002] Correct use of eye and face protection products is the key to reducing risks in the work environment and preventing accidents. Eye and face protection products are equipment used to protect the eyes and face from dangerous substances and other potential hazards. They are widely used in construction, chemical, medical, laboratory and other fields. In order to test whether the eye and face protection products can fully protect the wearer's eye and face areas that need to be protected, it is necessary to conduct an eye and face protection area coverage test.

[0003] The existing testing method is to wear the sample on the head model and put the sample in the correct wearing position, then hold a probe with a diameter of 2mm, perpendicular to the surface of the eye and face protection product, and probe along the edge of the sample. If the steel rod does not touch the protection area covered by the sample, the product is judged to be qualified. This method of manual testing often causes displacement of the eye and face protection product that has been worn during the test, and the product wearing position needs to be readjusted before continuing the test. The process is complicated, inefficient, and lacks precision. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a coverage detection method and device to reduce labor costs and improve detection efficiency.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A first aspect of the present invention provides a coverage detection method, comprising:

[0007] Acquire an image containing a target product;

[0008] Preprocessing the image containing the target product to obtain a preprocessed image;

[0009] Performing image recognition on the preprocessed image to obtain a recognition result;

[0010] A coverage detection is performed on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain a coverage detection result.

[0011] Optionally, obtain an image containing the target product, including:

[0012] Obtain basic information of target products;

[0013] Determine light source conditions according to the basic information of the target product;

[0014] The target product is imaged according to the light source conditions to obtain an image containing the target product.

[0015] Optionally, preprocessing the image containing the target product to obtain a preprocessed image includes:

[0016] Cropping the image containing the target product to obtain a cropped image;

[0017] Performing a geometric transformation on the cropped image to obtain a geometrically transformed image;

[0018] The geometrically transformed image is enhanced to obtain an enhanced image.

[0019] Optionally, performing image recognition on the preprocessed image to obtain a recognition result includes:

[0020] Converting the preprocessed image to obtain a grayscale image;

[0021] Dividing the grayscale image according to a preset threshold to obtain a divided image;

[0022] Extracting the divided image to obtain a bright area and a dark area;

[0023] Image recognition is performed on the preprocessed image according to the bright area and the dark area to obtain a recognition result.

[0024] Optionally, performing coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result includes:

[0025] Obtain preset test standards;

[0026] Comparing the recognition result with the preset detection standard to obtain a comparison result;

[0027] According to the comparison result, coverage detection is performed on the target area of ​​the target product to obtain a coverage detection result.

[0028] Optionally, obtain preset test standards, including:

[0029] Obtain basic information of target products;

[0030] Determine target coverage based on basic information of the target product;

[0031] According to the target coverage, a preset detection standard is determined.

[0032] Optionally, the method further includes:

[0033] Determine an improvement plan based on the coverage test result;

[0034] An evaluation report for the target product is generated based on the coverage test results, the improvement plan and the preset test standards.

[0035] A second aspect of the present invention provides a coverage detection device, comprising:

[0036] An acquisition module, used for acquiring an image containing a target product;

[0037] A processing module, used for preprocessing the image containing the target product to obtain a preprocessed image;

[0038] A recognition module, used to perform image recognition on the preprocessed image to obtain a recognition result;

[0039] The detection module is used to perform coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result.

[0040] According to a third aspect of the present invention, a computing device is provided, comprising: a processor and a memory storing a computer program, wherein when the computer program is executed by the processor, the method according to the first aspect is executed.

[0041] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, causes the computer to execute the method described in the first aspect.

[0042] The above solution of the present invention includes at least the following beneficial effects:

[0043] The above scheme of the present invention preprocesses the acquired image containing the target product, then performs image recognition, and finally performs coverage detection on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain the coverage detection result. There is no need to manually use a probe or a probe to carry out a physical contact test, and it will not cause the displacement of the eye and face protection product. The test accuracy is higher, and it has the advantages of saving labor costs and improving detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a coverage detection method in an embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of acquiring an image in an embodiment of the present invention;

[0046] Figure 3 It is a schematic diagram of the structure of the coverage detection device in an embodiment of the present invention.

[0047] Description of reference numerals: 1-head model, 2-target product, 3-light source, 4-image acquisition device. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0049] like Figure 1 As shown, an embodiment of the present invention provides a coverage detection method, comprising the following steps:

[0050] Step 101, obtaining an image containing a target product;

[0051] Step 102, preprocessing the image containing the target product to obtain a preprocessed image;

[0052] Step 103, performing image recognition on the preprocessed image to obtain a recognition result;

[0053] Step 104 , performing coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result.

[0054] The coverage detection method proposed in the embodiment of the present invention preprocesses the acquired image containing the target product, then performs image recognition, and finally performs coverage detection on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain the coverage detection result. There is no need to manually use a probe or a probe to conduct a physical contact test, and it will not cause displacement of the eye and face protection product. The test accuracy is higher, and it has the advantages of saving labor costs and improving detection efficiency.

[0055] Here, the target products are eye and face protection products, including but not limited to laser safety glasses, welding safety glasses, protective glasses, protective eye masks, protective face shields, full-face masks for respirators, medical protective (eye) masks, sunglasses, surface swimming glasses, ski goggles and other protective products for protecting the eyes, face or the entire head.

[0056] In an optional embodiment of the present invention, step 101 includes:

[0057] Step 1011, obtaining basic information of the target product;

[0058] Specifically, different eye and face protection products have different functions and effects. Different light source conditions need to be determined according to different eye and face protection products to improve the subsequent detection accuracy. Therefore, it is necessary to first obtain the basic information of the target product. This basic information may include the name, protection function, size (such as length, width, area, etc.), shape, etc. For example, for a pair of sunglasses A, whose function is to filter ultraviolet light, ultraviolet light needs to be excluded as a light source condition when determining the light source condition to ensure that light can pass through the sunglasses A to obtain a better detection effect.

[0059] Step 1012, determining light source conditions according to the basic information of the target product;

[0060] Specifically, based on the basic information such as the name, protection function, size (such as length, width, area, etc.), and shape of the target product, the appropriate light source intensity and light source type (such as ultraviolet light, infrared light, etc.) can be selected according to the protection function, and the light source installation position can be determined according to the size (such as length, width, area, etc.) and shape. Generally, the light source will be installed in the middle of the target product to ensure that the light emitted by the light source is evenly transmitted from the target product, which is convenient for subsequent coverage detection.

[0061] Step 1013: Capture an image of the target product according to the light source conditions to obtain an image containing the target product.

[0062] Specifically, the target product is worn on a head model, and the eyes or face of the head model is a hollow structure. If the target product is an eye protection product, the eyes of the head model are a hollow structure; if the target product is a face protection product, the face of the head model is a hollow structure; the specific structure of the head model is selected according to the type of eye and face protection product. According to the light source installation position, light source intensity, light source type, etc. in the light source conditions, the corresponding light source is installed inside the head model, and the corresponding intensity is set, and the image of the target product is captured using an image acquisition device, such as a camera. Here, the image acquisition device is located directly in front of the head model, so that the image acquisition device can capture the complete head model. The image acquisition device and the light source inside the head model are located on the same horizontal plane, ensuring that the image acquisition device is facing the light source, so that the light emitted by the light source is evenly distributed in the captured image, which is convenient for subsequent image recognition. In addition, it is necessary to capture images of the target product at multiple angles, such as rotating the head model 360 degrees, and capturing images at each angle (or multiple preset angles) to improve the accuracy of coverage detection.

[0063] In an optional embodiment of the present invention, step 102 includes:

[0064] Step 1021, cropping the image containing the target product to obtain a cropped image;

[0065] Specifically, the image containing the target product is cropped according to preset size requirements such as preset length and preset width, so that the cropped image meets the preset size requirements such as preset length and preset width, thereby reducing the impact of irrelevant information in the image on subsequent detection and improving work efficiency.

[0066] Step 1022, performing geometric transformation on the cropped image to obtain a geometrically transformed image;

[0067] Specifically, the cropped image is processed through geometric transformations such as translation, transposition, mirroring, rotation, and scaling to correct the errors of the image acquisition device and the random errors of the image acquisition device position (imaging angle, perspective relationship, and even the lens itself). The appropriate geometric transformation method can be selected according to the actual situation.

[0068] Step 1023, performing enhancement processing on the geometrically transformed image to obtain an enhanced image.

[0069] Specifically, in order to enhance the useful information in the geometrically transformed image, improve the visual effect of the image, purposefully emphasize the overall or local characteristics of the image, make the originally unclear image clear or emphasize certain interesting features, expand the difference between the features of different objects in the image, suppress uninteresting features, improve image quality, enrich the amount of information, enhance image recognition effects, and meet detection needs. According to actual conditions, you can choose a suitable image enhancement algorithm, such as the spatial domain method and the frequency domain method.

[0070] Here, the spatial domain method operates on the pixels in the image, and the formula is:

[0071] g(x,y)=f(x,y)×h(x,y)

[0072] Among them, f(x,y) is the image after geometric transformation, h(x,y) is the spatial transformation function, and g(x,y) represents the enhanced image.

[0073] The frequency domain method uses a low-pass filter or a high-pass filter to enhance the image after geometric transformation. Among them, the low-pass filter is to remove noise in the image; the high-pass filter is to enhance high-frequency signals such as edges to make blurred images clear. Specifically, the low-frequency filter can be selected from one of the ideal low-pass filter, Butterworth low-pass filter, Gaussian low-pass filter, exponential filter, etc. The high-pass filter can be selected from one of the ideal high-pass filter, Butterworth high-pass filter, Gaussian high-pass filter, exponential filter, etc. Different enhancement processing methods can be selected according to actual needs.

[0074] In an optional embodiment of the present invention, step 103 includes:

[0075] Step 1031, converting the preprocessed image to obtain a grayscale image;

[0076] Specifically, the preprocessed image is generally a color image, and the grayscale image only contains brightness information but not color information. Converting the preprocessed image into a grayscale image can simplify the image processing process and facilitate subsequent processing.

[0077] Step 1032, dividing the grayscale image according to a preset threshold to obtain a divided image;

[0078] Here, the role of the preset threshold is to divide the pixels of the image into two parts, the bright part and the dark part. For the obtained grayscale image, a suitable preset threshold is selected, and all pixels above the preset threshold are divided into the bright part, and the pixels below the preset threshold are divided into the dark part. The bright part and the dark part constitute the divided image.

[0079] Step 1033, extracting the divided image to obtain a bright area and a dark area;

[0080] Specifically, the divided image can be eroded to reduce the number of bright pixels, and the highlight area will shrink inward to remove small particle noise or refine the boundary of the foreground object; the dilation operation can increase the number of bright pixels, and the highlight area will expand outward to fill the small holes or cracks inside the object; the opening operation can be eroded first and then expanded to remove small objects and smooth the boundaries of larger objects without significantly changing their areas; the closing operation can be expanded first and then eroded to fill the small holes in the object and connect adjacent objects without significantly changing their areas. According to the actual situation, one or more of the above operations can be selected to repair the divided image, and then the bright area can be determined according to the distribution of bright pixels, and the dark area can be determined according to the distribution of dark pixels.

[0081] Step 1034: performing image recognition on the preprocessed image according to the bright area and the dark area to obtain a recognition result.

[0082] Specifically, the bright area and the dark area are obtained according to the bright area and the dark area, and the bright area is used as the outline of the target product in the preprocessed image, that is, the bright area is the protection area of ​​the target product in the preprocessed image, and the dark area is the non-protection area. Then, the size of the bright area, such as length, width, shape, area and other information, is calculated as the recognition result.

[0083] In an optional embodiment of the present invention, step 104 includes:

[0084] Step 1041, obtaining a preset detection standard;

[0085] In an optional embodiment of the present invention, step 1041 includes:

[0086] Step 10411, obtaining basic information of the target product;

[0087] Here, different eye and face protection products have different functions and effects, and different preset testing standards need to be determined according to different eye and face protection products for comparison in subsequent testing. Therefore, it is necessary to first obtain the basic information of the target product, which may include name, protection function, size (such as length, width, area, etc.), shape, etc. For example, for a pair of sunglasses A, its function is to filter ultraviolet light from the eyes.

[0088] Step 10412, determining target coverage according to the basic information of the target product;

[0089] Specifically, the protection area can be determined as the eye or face according to the name of the target product; the area of ​​the target product can be calculated according to its size, shape and other information. The target coverage is determined according to the protection area and area. For example, the target coverage for a pair of women's sunglasses is: the coverage area of ​​a single eye is 20 square centimeters. Here, as needed, the target coverage can also include shape, length and width, such as the target coverage of a single lens is: length 5 centimeters, width 4 centimeters, rectangular shape, etc.

[0090] Step 10413, determine the preset detection standard based on the target coverage.

[0091] Specifically, the preset testing standard includes the name of the target product and the corresponding target coverage content. For example, the preset testing standard for a pair of women's sunglasses is: women's sunglasses, rectangular in shape, 5 cm in length, 4 cm in width, and a single eye coverage area of ​​20 square centimeters.

[0092] Step 1042, comparing the recognition result with the preset detection standard to obtain a comparison result;

[0093] Specifically, the length, width, shape, area and other information in the recognition result are matched one by one with the length, width, shape and area and other information in the preset detection standard, and the comparison is performed, and the comparison result and content are used as the comparison result. For example, the comparison result may include: the length of 5 cm in the recognition result is the same as the length of 5 cm in the preset detection standard, the width of 4 cm in the recognition result is the same as the width of 4 cm in the preset detection standard, the area of ​​20 square centimeters in the recognition result is the same as the area of ​​20 square centimeters in the preset detection standard, the shape of the recognition result is a rectangle is the same as the shape of the preset detection standard, etc. The comparison here can compare the outline of the bright area in the recognition result with the outline of the target product in the preset detection standard to compare whether the relevant data of the two are completely consistent. The comparison result can also include the outline data of the bright area and the dark area.

[0094] Step 1043: Perform coverage detection on the target area of ​​the target product according to the comparison result to obtain a coverage detection result.

[0095] Specifically, the target area of ​​the target product is the eye and face area that the target product protects, such as the eye area for sunglasses. Here, the ratio of the bright area to the dark area in the collected image, the area of ​​the target product in the image, and other data can be obtained based on the data in the comparison result. Based on these data, the coverage of the target product in the image to its protection area can be calculated.

[0096] In an optional embodiment of the present invention, the coverage detection method further includes the following steps:

[0097] Step 105, determining an improvement plan according to the coverage detection result;

[0098] Specifically, if the expected coverage is 100% (i.e., the target product completely covers its target protection area), and the coverage of the target product in the image is 90%, then the target product still needs to be improved, and the corresponding solution in the solution library can be retrieved as an improvement solution.

[0099] Step 106, generating an evaluation report of the target product according to the coverage test result, the improvement plan and the preset test standard.

[0100] Specifically, the evaluation report of the target product includes coverage test results, improvement plans and preset test standards, so that users can intuitively see the test content of the target product. For defective products, improvement plans are provided to users to improve user satisfaction.

[0101] A specific embodiment of the coverage detection method proposed in the embodiment of the present invention is:

[0102] Step 111, acquiring an image. Figure 2 As shown, the head model 1 is placed on a rotatable platform, and the platform rotation angle is not less than 180 degrees. Among them, when the target product 2 is an eye protection product, its protection area is the eye, and the eye protection area of ​​the head model 1 is a hollow design; when the target product is a face protection product, its protection area is the face, and the face protection area of ​​the head model 1 is a hollow design. Light can be emitted through the hollow structure. A light source 3 is installed inside the head model, and the position of the light source 3 corresponds to that of the image acquisition device 4. After turning on the power supply 3, images of the head model 1 at multiple angles are collected by the image acquisition device 4. In this embodiment, the target product 2 is an eye protection product as an example for explanation.

[0103] Step 112, preprocessing. The acquired image is cropped, transformed, enhanced, etc., so that the image meets the preset size, useless information is cut off, the error of the image acquisition device due to itself and the position is improved, and the clarity of the image and the efficiency of subsequent detection are improved.

[0104] Step 113, image recognition. The purpose of image recognition is to use the relevant information of the bright and dark areas in the image to identify whether there is light coming through the edge of the target product and to identify the outline of the target product in the image, thereby obtaining the size information of the target product in the image, such as length, width, area, position, etc.

[0105] Step 114, coverage detection. According to the image recognition result, the area and other information of the target product in the image are calculated, and compared with the area and other information of the target product in the preset detection standard to detect whether the coverage of the target product in the image meets the expected requirements.

[0106] Step 115, generating an evaluation report. If the coverage of the target product in the image does not meet the expected requirements, the corresponding improvement plan is retrieved from the pre-stored solution library, and the test results, improvement plan and preset test standards are sent to the user as an evaluation report of the target product to help the user improve the product and improve user satisfaction.

[0107] The embodiment of the present invention proposes a coverage detection method. The test can be carried out by simply wearing the eye and face protection product on a head model. No other tools or steps are required, and the operation is simple. No probe or probe is required to carry out physical contact testing, which will not cause displacement of the eye and face protection product and has higher test accuracy. By recognizing the image, it is determined whether the light at the boundary of the eye or face protection area overflows from the edge of the eye and face protection product to determine whether the product is qualified. The determination speed is fast, which greatly improves the test efficiency.

[0108] like Figure 3 As shown, an embodiment of the present invention provides a coverage detection device 200, comprising:

[0109] An acquisition module 201 is used to acquire an image containing a target product;

[0110] A processing module 202 is used to preprocess the image containing the target product to obtain a preprocessed image;

[0111] The recognition module 203 is used to perform image recognition on the preprocessed image to obtain a recognition result;

[0112] The detection module 204 is used to perform coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result.

[0113] Optionally, obtain an image containing the target product, including:

[0114] Obtain basic information of target products;

[0115] Determine light source conditions according to the basic information of the target product;

[0116] The target product is imaged according to the light source conditions to obtain an image containing the target product.

[0117] Optionally, preprocessing the image containing the target product to obtain a preprocessed image includes:

[0118] Cropping the image containing the target product to obtain a cropped image;

[0119] Performing a geometric transformation on the cropped image to obtain a geometrically transformed image;

[0120] The geometrically transformed image is enhanced to obtain an enhanced image.

[0121] Optionally, performing image recognition on the preprocessed image to obtain a recognition result includes:

[0122] Converting the preprocessed image to obtain a grayscale image;

[0123] Dividing the grayscale image according to a preset threshold to obtain a divided image;

[0124] Extracting the divided image to obtain a bright area and a dark area;

[0125] Image recognition is performed on the preprocessed image according to the bright area and the dark area to obtain a recognition result.

[0126] Optionally, performing coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result includes:

[0127] Obtain preset test standards;

[0128] Comparing the recognition result with the preset detection standard to obtain a comparison result;

[0129] According to the comparison result, coverage detection is performed on the target area of ​​the target product to obtain a coverage detection result.

[0130] Optionally, obtain preset test standards, including:

[0131] Obtain basic information of target products;

[0132] Determine target coverage based on basic information of the target product;

[0133] According to the target coverage, a preset detection standard is determined.

[0134] Optionally, the device further comprises:

[0135] A determination module 205 is used to determine an improvement plan according to the coverage detection result;

[0136] The generation module 206 is used to generate an evaluation report of the target product according to the coverage detection result, the improvement plan and the preset detection standard.

[0137] The coverage detection device proposed in the embodiment of the present invention preprocesses the acquired image containing the target product, then performs image recognition, and finally performs coverage detection on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain the coverage detection result. There is no need to manually use a probe or a probe to conduct a physical contact test, and it will not cause displacement of the eye and face protection product. The test accuracy is higher, and it has the advantages of saving labor costs and improving detection efficiency.

[0138] It should be noted that the device is a device corresponding to the above method, and all implementations in the above method embodiment are applicable to the embodiment of the device and can achieve the same technical effect, which will not be described in detail in this embodiment.

[0139] The embodiment of the present invention further provides a computing device, comprising: a processor, and a memory storing a computer program, wherein when the computer program is executed by the processor, the method described in any one of the above embodiments is executed. All implementations in the above method embodiments are applicable to the embodiments of the device, and can achieve the same technical effects. They will not be described in detail in this embodiment.

[0140] The embodiment of the present invention further provides a computer-readable storage medium on which instructions are stored. When the instructions are executed on a computer, the computer executes the method as described in any one of the above embodiments. All implementations in the above method embodiments are applicable to the embodiments of the device and can achieve the same technical effects. They will not be described in detail in this embodiment.

[0141] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A coverage detection method, It is characterized in that include: Acquire an image containing a target product; Preprocessing the image containing the target product to obtain a preprocessed image; Performing image recognition on the preprocessed image to obtain a recognition result; A coverage detection is performed on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain a coverage detection result.

2. The coverage detection method according to claim 1, It is characterized in that Acquire an image containing the target product, including: Obtain basic information of target products; Determine light source conditions according to the basic information of the target product; The target product is imaged according to the light source conditions to obtain an image containing the target product.

3. The coverage detection method according to claim 1, It is characterized in that Preprocessing the image containing the target product to obtain a preprocessed image includes: Cropping the image containing the target product to obtain a cropped image; Performing a geometric transformation on the cropped image to obtain a geometrically transformed image; The geometrically transformed image is enhanced to obtain an enhanced image.

4. The coverage detection method according to claim 1, It is characterized in that Performing image recognition on the preprocessed image to obtain a recognition result includes: Converting the preprocessed image to obtain a grayscale image; Dividing the grayscale image according to a preset threshold to obtain a divided image; Extracting the divided image to obtain a bright area and a dark area; Image recognition is performed on the preprocessed image according to the bright area and the dark area to obtain a recognition result.

5. The coverage detection method according to claim 1, It is characterized in that Performing coverage detection on the target area of ​​the target product according to the preset detection standard and the recognition result to obtain a coverage detection result, including: Obtain preset test standards; Comparing the recognition result with the preset detection standard to obtain a comparison result; According to the comparison result, coverage detection is performed on the target area of ​​the target product to obtain a coverage detection result.

6. The coverage detection method according to claim 5, It is characterized in that Access preset test standards, including: Obtain basic information of target products; Determine target coverage based on basic information of the target product; According to the target coverage, a preset detection standard is determined.

7. The coverage detection method according to claim 1, It is characterized in that Also includes: Determine an improvement plan based on the coverage test result; An evaluation report for the target product is generated based on the coverage test results, the improvement plan and the preset test standards.

8. A coverage detection device, It is characterized in that include: An acquisition module, used for acquiring an image containing a target product; A processing module, used for preprocessing the image containing the target product to obtain a preprocessed image; A recognition module, used to perform image recognition on the preprocessed image to obtain a recognition result; The detection module is used to perform coverage detection on the target area of ​​the target product according to a preset detection standard and the recognition result to obtain a coverage detection result.

9. A computing device, It is characterized in that include: A processor and a memory storing a computer program, wherein when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is performed.

10. A computer-readable storage medium, It is characterized in that Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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