Material defect identification dynamic display method, device, electronic equipment and storage medium

Abstract

The embodiment of the present invention discloses a material defect identification dynamic display method, device, electronic device and storage medium. When the method determines that the collected picture is a dynamic picture target picture, the method collects a corresponding number of dynamic picture target pictures according to preset dynamic picture parameters, generates a material defect identification dynamic picture according to the corresponding number of dynamic picture target pictures, and displays it in a preset display area; when the method determines that the collected picture is not a dynamic picture target picture, the collected picture is stored in a static picture path and displayed in a static picture display area. The present invention solves the shortcomings of the existing material defect identification result display, displays the identification results of defective materials through dynamic pictures, and displays the identification results of normal materials through static pictures, occupies less computing resources, effectively solves the homogeneity of display methods, and enables re-inspection personnel to quickly and intuitively distinguish defective materials from normal materials, effectively improving the efficiency, comprehensiveness and accuracy of re-inspection.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of material defect detection, and in particular, to a material defect identification dynamic display method, device, electronic device and storage medium. Background Art

[0002] Double Vertical Continuity Plating (DVCP) is used for electroplating copper on circuit boards and is widely used in the production process of printed circuit boards. Before electroplating the copper-plated board material, the copper-plated board is placed on a rack, and the pre-treatment, electroplating and post-treatment processes are completed in sequence. The defects of the copper-plated board material on the double vertical copper plating line are identified and the identification results are displayed by an automatic visual inspection (AVI) machine, and manual re-inspection is performed based on the identification results of the AVI machine. However, the existing material defect identification and display scheme displays the identification results of defective materials and normal materials through a static picture. The re-inspector needs to first find the defective picture from the many identification results before re-inspecting the defective material. It is impossible to quickly and intuitively distinguish between defective materials and normal materials. Missed re-inspections often occur, which is time-consuming and labor-intensive, affecting the efficiency, comprehensiveness and accuracy of the re-inspection.

[0003] The above problems need to be solved urgently. Summary of the invention

[0004] In order to solve the related technical problems, the present invention provides a material defect identification dynamic display method, device, electronic device and storage medium to solve the problems mentioned in the above background technology part.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a material defect identification dynamic display method, the method comprising:

[0007] Determine whether the collected image is a dynamic image target image;

[0008] If the result of the judgment is yes, then according to the preset dynamic image parameters, a corresponding number of dynamic image target pictures are collected;

[0009] A material defect recognition dynamic graph is generated according to the corresponding number of dynamic graph target images and displayed in a preset display area.

[0010] As an optional implementation manner, the determining whether the captured image is a dynamic image target image includes:

[0011] The collected images are used to identify material defects. If the identification result shows that the material has defects, the collected images are determined to be dynamic image target images, and the dynamic image target images are stored in Redis.

[0012] As an optional implementation manner, the determining whether the captured image is a dynamic image target image further includes:

[0013] Determine whether the collected image is an image that has not been subjected to material defect identification;

[0014] If the judgment result is yes, the collected picture is determined to be a dynamic picture target picture, and the dynamic picture target picture is stored in Redis.

[0015] As an optional implementation, collecting a corresponding number of dynamic image target images according to preset dynamic image parameters includes:

[0016] The dynamic parameters include but are not limited to any one or a combination of dynamic image acquisition time or dynamic image key frame data volume; according to the preset dynamic image acquisition time or dynamic image key frame data volume, the dynamic image target image corresponding to the dynamic image key frame data volume is collected.

[0017] As an optional implementation manner, before determining whether the captured image is a dynamic image target image, the method further includes:

[0018] Obtain a picture of the copper-plated wire rack number to be processed, and perform OCR recognition on the picture of the copper-plated wire rack number to obtain the copper-plated wire rack number, thereby completing material positioning.

[0019] As an optional implementation, the collected image is subjected to material defect recognition, and if the recognition result is that the material has defects, the collected image is determined to be a dynamic image target image, including:

[0020] The collected images are used to identify material defects. If the identification result shows that the material has defects, the location of the defects is marked on the image, and the collected image is determined to be a dynamic image target image.

[0021] As an optional implementation, if the result of the judgment is no, the collected picture is stored in the static picture path and displayed in the static picture display area.

[0022] In a second aspect, an embodiment of the present invention provides a material defect identification dynamic display device, which adopts the material defect identification dynamic display method described in any one of the embodiments of the first aspect above, including:

[0023] A dynamic image target picture judgment module is used to judge whether the collected picture is a dynamic image target picture;

[0024] A dynamic image target picture acquisition module is used to acquire a corresponding number of dynamic image target pictures according to preset dynamic image parameters when the dynamic image target picture determination module determines that the acquired picture is a dynamic image target picture;

[0025] The material defect identification dynamic image generation module is used to generate a material defect identification dynamic image according to the corresponding number of dynamic image target images, and display it in a preset display area.

[0026] As an optional implementation, the material defect identification dynamic display device further includes:

[0027] The static image processing module is used to store the collected image into the static image path and display it in the static image display area when the dynamic image target image judgment module determines that the collected image is not the dynamic image target image.

[0028] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory connected to the processor, wherein program data is stored in the memory, and the processor calls the program data stored in the memory to execute the material defect identification dynamic display method as described in any one of the embodiments of the first aspect above.

[0029] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement the material defect identification dynamic display method as described in any one of the embodiments of the first aspect above.

[0030] The technical solution proposed in the embodiment of the present invention solves the shortcomings of the existing material defect identification result display. When it is determined that the collected picture is a dynamic picture target picture, a corresponding number of dynamic picture target pictures are collected according to preset dynamic picture parameters, and a material defect identification dynamic picture is generated according to the corresponding number of dynamic picture target pictures, and displayed in a preset display area; when it is determined that the collected picture is not a dynamic picture target picture, the collected picture is stored in a static picture path and displayed in a static picture display area. The technical solution proposed in the embodiment of the present invention displays the identification results of defective materials through dynamic pictures, and displays the identification results of normal materials through static pictures, occupies less computing resources, effectively solves the homogeneity of display methods, and enables re-inspection personnel to quickly and intuitively distinguish defective materials from normal materials, effectively improving the efficiency, comprehensiveness and accuracy of re-inspection, and is suitable for popularization and application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate and understand the technical solutions in the embodiments of the present invention, the following briefly introduces the background technology of the present invention and the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the contents of the embodiments of the present invention and these drawings without paying creative work.

[0032] Figure 1 A schematic diagram of a process flow of a material defect identification dynamic display method provided in Embodiment 1 of the present invention;

[0033] Figure 2 This is a schematic diagram of the structure of a dynamic display device for identifying material defects provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0034] In order to make the technical problems solved by the present invention, the technical solutions adopted and the technical effects achieved clearer, the technical solutions of the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0035] Embodiment 1

[0036] Please refer to Figure 1 As stated, Figure 1 This is a schematic diagram of a material defect identification dynamic display method flow chart provided in Embodiment 1 of the present invention. As shown in the figure, the material defect identification dynamic display method 100 in this embodiment includes the following steps:

[0037] S101. Determine whether the collected image is a dynamic image target image;

[0038] S102. If the result of the judgment is yes, then according to the preset dynamic image parameters, a corresponding number of dynamic image target images are collected;

[0039] S103. Generate a material defect recognition dynamic graph based on the corresponding number of dynamic graph target images, and display it in a preset display area.

[0040] The material defect identification dynamic display method 100 proposed in this embodiment collects a corresponding number of dynamic image target images according to preset dynamic image parameters when determining that the collected image is a dynamic image target image, generates a material defect identification dynamic image based on the corresponding number of dynamic image target images, and displays it in a preset display area, so that re-inspection personnel can quickly and intuitively find defective materials and re-inspect, effectively improving the efficiency, comprehensiveness and accuracy of re-inspection, and the dynamic image occupies less computing resources and has low cost, which is suitable for promotion and application.

[0041] Embodiment 2

[0042] This embodiment provides a material defect identification dynamic display method, which includes the following steps:

[0043] S201. Determine whether the collected image is a dynamic image target image;

[0044] S202. If the result of the judgment is yes, then according to the preset dynamic image parameters, a corresponding number of dynamic image target images are collected;

[0045] S203. Generate a material defect recognition dynamic graph based on the corresponding number of dynamic graph target images, and display it in a preset display area.

[0046] Exemplarily, the determining whether the captured image is a dynamic image target image includes:

[0047] The collected images are subjected to material defect identification. If the identification result shows that the material has defects, the collected images are determined to be dynamic image target images, and the dynamic image target images are stored in Redis. In this embodiment, the dynamic image target images are stored in Redis, so that the data is stored and read in memory, and the access speed is extremely fast, which meets the needs of real-time display and real-time update of material defect identification results.

[0048] Exemplarily, the determining whether the captured image is a dynamic image target image further includes:

[0049] Determine whether the collected image is an image that has not been subjected to material defect identification;

[0050] If the judgment result is yes, the collected picture is determined to be a dynamic picture target picture, and the dynamic picture target picture is stored in Redis.

[0051] Due to insufficient computing power of the AVI inspection machine and other reasons, sometimes the captured images are not identified for defects. Such images should also be included in the re-inspection category. In this embodiment, such images are also judged and used as dynamic image target images, which can effectively help re-inspection personnel quickly identify such problem images and conduct re-inspections.

[0052] Exemplarily, the collecting a corresponding number of dynamic image target images according to preset dynamic image parameters includes:

[0053] The dynamic parameters include but are not limited to any one or a combination of dynamic image acquisition time or dynamic image key frame data volume; according to the preset dynamic image acquisition time or dynamic image key frame data volume, the dynamic image target image corresponding to the dynamic image key frame data volume is collected.

[0054] In this embodiment, the user can set only the dynamic image acquisition time according to their own usage scenario, set it to store the first dynamic image target image in Redis, and then continue to collect dynamic image target images for t seconds. You can choose to store all dynamic image target images collected within t seconds in Redis for generating material defect recognition dynamic images, or you can choose to filter the dynamic image target images collected within t seconds. In this embodiment, the screening method includes but is not limited to: calculating the defect confidence of all dynamic image target images, and setting a defect confidence threshold, judging whether the defect confidence of the dynamic image target image is higher than the defect confidence threshold, if higher, then storing it in Redis as the key frame data of the material defect recognition dynamic image, otherwise the dynamic image target image cannot be used as the key frame data of the material defect recognition dynamic image.

[0055] In this embodiment, the user can control the display duration of the material defect recognition dynamic graph by setting the amount of dynamic graph key frame data; after setting the first dynamic graph target image to be stored in Redis, after collecting dynamic graph target images with the set amount of dynamic graph key frame data, stop collecting dynamic graph target images required for the material defect recognition dynamic graph. It is worth mentioning that when collecting dynamic graph target images with the set amount of dynamic graph key frame data, the collected dynamic graph target images need to be screened. Set a defect confidence threshold to determine whether the defect confidence of the dynamic graph target image is higher than the defect confidence threshold. If higher, store it in Redis as key frame data for the material defect recognition dynamic graph.

[0056] In this embodiment, in order to improve the material defect recognition dynamic graph to reduce the display of invalid information and improve the comprehensiveness of information display, before the dynamic graph target image is included in the key frame data of the material defect recognition dynamic graph, the dynamic graph target image is preprocessed to remove noise, and the key features of the dynamic graph target image such as defect feature size, corner points, edges, etc. are extracted to determine the direct similarity of the key features. When it is determined that the similarity meets the preset similarity threshold, the dynamic graph target image is included in the key frame data of the material defect recognition dynamic graph, otherwise it is eliminated.

[0057] In a specific application, a material defect recognition dynamic graph is generally set to include but not limited to 15 frames of key frame data, and the acquisition time of 15 frames of key frame data does not exceed 5 seconds.

[0058] For example, during copper plating, the copper-plated plate of the material is a bare plate, and the copper-plated plate of the material needs to be positioned and identified by the copper-plated wire rack number; therefore, in this embodiment, before judging whether the captured image is a dynamic image target image, it also includes: obtaining the copper-plated wire rack number image to be processed, and performing optical character recognition (OCR) on the copper-plated wire rack number image to obtain the copper-plated wire rack number to complete material positioning. After the OCR recognition is successful, the judgment of whether the captured image is a dynamic image target image is performed.

[0059] Exemplarily, the collected image is subjected to material defect recognition, and if the recognition result is that the material has defects, the collected image is determined to be a dynamic image target image, including:

[0060] The collected images are used to identify material defects. If the identification result shows that the material has defects, the location of the defects is marked on the image, and the collected image is determined to be a dynamic image target image.

[0061] In this embodiment, the method of marking the location of the defect on the image can adopt different shapes and line colors for different defect types. The re-inspection personnel can intuitively understand the location and type of material defects, so as to quickly complete the defect re-inspection.

[0062] Exemplarily, if it is determined that the captured image is not a dynamic image target image, the captured image is stored in a static image path and displayed in a static image display area.

[0063] In this embodiment, when the material defect identification is dynamically displayed, the material defect identification dynamic image is displayed in the preset display area, and the dynamic image target image with the highest defect confidence is selected from the material defect identification dynamic image and displayed in the static display area. The static display area is set at, but not limited to, below the material defect identification dynamic image.

[0064] The material defect identification dynamic display method proposed in this embodiment, when determining that the collected image is a dynamic image target image, collects a corresponding number of dynamic image target images according to preset dynamic image parameters, generates a material defect identification dynamic image according to the corresponding number of dynamic image target images, and displays it in a preset display area; when determining that the collected image is not a dynamic image target image, the collected image is stored in a static image path and displayed in a static image display area. The material defect identification dynamic display method proposed in this embodiment displays the identification results of defective materials through dynamic images and the identification results of normal materials through static images, occupies less computing resources, effectively solves the homogeneity of display methods, and enables re-inspection personnel to quickly and intuitively distinguish between defective materials and normal materials, effectively improving the efficiency, comprehensiveness and accuracy of re-inspection, and is suitable for promotion and application.

[0065] Embodiment 3

[0066] This embodiment provides a material defect identification dynamic display device 200, which adopts the material defect identification dynamic display method described in any one of the above-mentioned embodiments 1 and 2, and includes:

[0067] A dynamic image target picture determination module 201 is used to determine whether the collected picture is a dynamic image target picture;

[0068] The dynamic image target picture acquisition module 202 is used to acquire a corresponding number of dynamic image target pictures according to preset dynamic image parameters when the dynamic image target picture determination module 201 determines that the acquired picture is a dynamic image target picture;

[0069] The material defect identification dynamic image generation module 203 is used to generate a material defect identification dynamic image according to the corresponding number of dynamic image target images, and display it in a preset display area.

[0070] Exemplarily, the material defect identification dynamic display device 200 also includes: a static image processing module 204; the static image processing module 204 is used to store the collected image into a static image path and display it in a static image display area when the dynamic image target image judgment module 201 determines that the collected image is not a dynamic image target image.

[0071] In this embodiment, the dynamic image target picture determination module 201 is specifically used for:

[0072] The collected images are subjected to material defect identification. If the identification result shows that the material has defects, the collected images are determined to be dynamic image target images, and the dynamic image target images are stored in Redis. In this embodiment, the dynamic image target images are stored in Redis, so that the data is stored and read in memory, and the access speed is extremely fast, which meets the needs of real-time display and real-time update of material defect identification results.

[0073] In this embodiment, the dynamic graph target image judgment module 201 is also used to: judge whether the collected image is an image that has not been subjected to material defect identification; if the judgment result is yes, determine that the collected image is a dynamic graph target image, and store the dynamic graph target image in Redis.

[0074] Due to insufficient computing power of the AVI inspection machine and other reasons, sometimes the captured images are not identified for defects. Such images should also be included in the re-inspection category. In this embodiment, such images are also judged and used as dynamic image target images, which can effectively help re-inspection personnel quickly identify such problem images and conduct re-inspections.

[0075] Exemplarily, the collecting of a corresponding number of dynamic graphic target images according to preset dynamic graphic parameters includes: the dynamic parameters include but are not limited to any one or a combination of the dynamic graphic collection time or the dynamic graphic key frame data volume; collecting the dynamic graphic target images corresponding to the dynamic graphic key frame data volume according to the preset dynamic graphic collection time or the dynamic graphic key frame data volume.

[0076] In this embodiment, the user can set only the dynamic image acquisition time according to their own usage scenario, set it to store the first dynamic image target image in Redis, and then continue to collect dynamic image target images for t seconds. You can choose to store all dynamic image target images collected within t seconds in Redis for generating material defect recognition dynamic images, or you can choose to filter the dynamic image target images collected within t seconds. In this embodiment, the screening method includes but is not limited to: calculating the defect confidence of all dynamic image target images, and setting a defect confidence threshold, judging whether the defect confidence of the dynamic image target image is higher than the defect confidence threshold, if higher, then storing it in Redis as the key frame data of the material defect recognition dynamic image, otherwise the dynamic image target image cannot be used as the key frame data of the material defect recognition dynamic image.

[0077] In this embodiment, the user can control the display duration of the material defect recognition dynamic graph by setting the amount of dynamic graph key frame data; after setting the first dynamic graph target image to be stored in Redis, after collecting dynamic graph target images with the set amount of dynamic graph key frame data, stop collecting dynamic graph target images required for the material defect recognition dynamic graph. It is worth mentioning that when collecting dynamic graph target images with the set amount of dynamic graph key frame data, the collected dynamic graph target images need to be screened. Set a defect confidence threshold to determine whether the defect confidence of the dynamic graph target image is higher than the defect confidence threshold. If higher, store it in Redis as key frame data for the material defect recognition dynamic graph.

[0078] In this embodiment, in order to improve the material defect recognition dynamic graph to reduce the display of invalid information and improve the comprehensiveness of information display, before the dynamic graph target image is included in the key frame data of the material defect recognition dynamic graph, the dynamic graph target image is preprocessed to remove noise, and the key features of the dynamic graph target image such as defect feature size, corner points, edges, etc. are extracted to determine the direct similarity of the key features. When it is determined that the similarity meets the preset similarity threshold, the dynamic graph target image is included in the key frame data of the material defect recognition dynamic graph, otherwise it is eliminated.

[0079] For example, during copper plating, the copper-plated board of the material is a bare board, and the copper-plated board of the material needs to be positioned and identified by the copper-plated wire rack number; therefore, in this embodiment, before judging whether the collected image is a dynamic image target image, it also includes: obtaining the copper-plated wire rack number image to be processed, and performing optical character recognition on the copper-plated wire rack number image to obtain the copper-plated wire rack number, so as to complete material positioning.

[0080] In this embodiment, the dynamic image target picture judgment module 201 is specifically used to: identify material defects in the collected pictures. If the recognition result is that the material has defects, the location of the defects is marked on the picture, and the collected picture is determined to be a dynamic image target picture.

[0081] In this embodiment, the method of marking the location of the defect on the image can adopt different shapes and line colors for different defect types. The re-inspection personnel can intuitively understand the location and type of material defects, so as to quickly complete the defect re-inspection.

[0082] In this embodiment, if it is determined that the captured image is not a dynamic image target image, the captured image is stored in a static image path and displayed in a static image display area.

[0083] When the material defect identification is dynamically displayed, the material defect identification dynamic image is displayed in the preset display area, and the dynamic image target image with the highest defect confidence is selected from the material defect identification dynamic image and displayed in the static display area. The static display area is set at but not limited to below the material defect identification dynamic image.

[0084] The material defect identification dynamic display device 200 proposed in this embodiment, when determining that the collected image is a dynamic image target image, collects a corresponding number of dynamic image target images according to preset dynamic image parameters, generates a material defect identification dynamic image according to the corresponding number of dynamic image target images, and displays it in a preset display area; when determining that the collected image is not a dynamic image target image, the collected image is stored in a static image path and displayed in a static image display area. The material defect identification dynamic display device 200 proposed in this embodiment displays the identification results of defective materials through dynamic images and displays the identification results of normal materials through static images, occupies less computing resources, effectively solves the homogeneity of display methods, and enables re-inspection personnel to quickly and intuitively distinguish defective materials from normal materials, effectively improving the efficiency, comprehensiveness and accuracy of re-inspection.

[0085] Embodiment 4

[0086] This embodiment provides an electronic device, which includes a processor and a memory connected to the processor, wherein program data is stored in the memory, and the processor calls the program data stored in the memory to execute the material defect identification dynamic display method as described in any one of the above-mentioned embodiments 1 and 2.

[0087] Embodiment 5

[0088] This embodiment provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the material defect identification dynamic display method as described in any one of the above-mentioned embodiments 1 and 2.

[0089] It should be noted that the above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0090] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A material defect identification dynamic display method, characterized in that: include: Determine whether the collected image is a dynamic image target image; If the result of the judgment is yes, then according to the preset dynamic image parameters, a corresponding number of dynamic image target pictures are collected; A material defect recognition dynamic graph is generated according to the corresponding number of dynamic graph target images and displayed in a preset display area.

2. The material defect identification dynamic display method according to claim 1 is characterized in that: The step of determining whether the captured image is a dynamic image target image includes: The collected images are used to identify material defects. If the identification result shows that the material has defects, the collected images are determined to be dynamic image target images, and the dynamic image target images are stored in Redis.

3. The material defect identification dynamic display method according to claim 2 is characterized in that: The step of determining whether the captured image is a dynamic image target image further includes: Determine whether the collected image is an image that has not been subjected to material defect identification; If the judgment result is yes, the collected picture is determined to be a dynamic picture target picture, and the dynamic picture target picture is stored in Redis.

4. The material defect identification dynamic display method according to claim 1 is characterized in that: The step of collecting a corresponding number of dynamic image target images according to preset dynamic image parameters includes: The dynamic parameters include but are not limited to any one or a combination of dynamic image acquisition time or dynamic image key frame data volume; according to the preset dynamic image acquisition time or dynamic image key frame data volume, the dynamic image target image corresponding to the dynamic image key frame data volume is collected.

5. The material defect identification dynamic display method according to claim 4 is characterized in that: Before determining whether the captured image is a dynamic image target image, the method further includes: Obtain a picture of the copper-plated wire rack number to be processed, and perform OCR recognition on the picture of the copper-plated wire rack number to obtain the copper-plated wire rack number, thereby completing material positioning.

6. The material defect identification dynamic display method according to claim 2 is characterized in that: The collected images are subjected to material defect recognition. If the recognition result shows that the material has defects, the collected images are determined to be dynamic image target images, including: The collected images are used to identify material defects. If the identification result shows that the material has defects, the location of the defects is marked on the image, and the collected image is determined to be a dynamic image target image.

7. The material defect identification dynamic display method according to any one of claims 1 to 6, characterized in that: If the result of the judgment is no, the collected picture is stored in the static picture path and displayed in the static picture display area.

8. A material defect identification dynamic display device, characterized in that: The device adopts the material defect identification dynamic display method described in claim 1, comprising: A dynamic image target picture judgment module is used to judge whether the collected picture is a dynamic image target picture; A dynamic image target picture acquisition module is used to acquire a corresponding number of dynamic image target pictures according to preset dynamic image parameters when the dynamic image target picture determination module determines that the acquired picture is a dynamic image target picture; The material defect identification dynamic image generation module is used to generate a material defect identification dynamic image according to the corresponding number of dynamic image target images, and display it in a preset display area.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory connected to the processor, wherein program data is stored in the memory, and the processor calls the program data stored in the memory to execute the material defect identification dynamic display method as described in any one of the above-mentioned first aspect embodiments.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the material defect identification dynamic display method as described in claim 1 above.

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