A target plate modeling and intelligent scoring method, system and storage medium based on image processing technology

Abstract

The present application discloses a target board modeling and intelligent scoring method, system and storage medium based on image processing technology, including: obtaining the curve ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data; when a shooting event is detected, a score mask is generated based on the curve ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data, and the score mask is cached; the coordinate data transmitted by the shooting device is received, and the shooting position is mapped with each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache; according to the mapping result, the score of the shooting is calculated and fed back to the training personnel in real time. The present application realizes the modeling, scoring and dynamic adjustment of the target board in shooting training through an intelligent method, and can calculate the shooting score efficiently and accurately.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a target plate modeling and intelligent scoring method, system and storage medium based on image processing technology. Background Art

[0002] In recent years, image processing technology has been widely used, especially in smart shooting ranges and intelligent shooting training. The combination of image processing technology has greatly improved the efficiency and accuracy of training. Image processing technology can intelligently analyze the target board image in the shooting range, thereby providing a more accurate shooting performance evaluation.

[0003] In existing smart shooting range training, trainers usually use shooting training equipment to shoot, and use shock wave drones to detect and calculate the hits. However, the shock wave drone has large functional limitations. It can usually only obtain the relative position coordinates (such as x, y coordinates) after the bullet hits the target, but cannot directly obtain the image information of the target plate. This requires the user to manually calculate the shooting score based on the feedback from the shock wave drone and the set target plate. This process is cumbersome and prone to errors, and manual intervention is still required for different target plate shapes and scoring rules.

[0004] However, most of the shooting training systems on the market do not have modeling and intelligent settings for the target board, and lack the function of directly linking the target board image with the shooting score. Traditional shooting scoring systems usually use a static scoring algorithm to compare the shooting hit point with the target board to calculate the score, but this method often has errors and efficiency problems, and is not flexible and difficult to adapt to complex and changing training needs. Summary of the invention

[0005] The purpose of this application is to provide a target plate modeling and intelligent scoring method, system and storage medium based on image processing technology to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0006] This application adopts the following technical solutions to achieve the above invention objectives:

[0007] The present application provides a target plate modeling and intelligent scoring method based on image processing technology, including:

[0008] Acquire the curved circular ring shape data of the target plate, the black and white area image data related to the target plate, and the circular ring score setting data or the area score setting data;

[0009] When a shooting event is detected, a score mask is generated based on the curved ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data, and the score mask is cached;

[0010] Receive the coordinate data transmitted by the shooting device, and map the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache;

[0011] Based on the mapping results, the score of the shooting is calculated and fed back to the training staff in real time.

[0012] Further, when a shooting event is detected, a method for generating a score mask based on the curve data, the area setting data and the score configuration data of the target board includes:

[0013] Initialize a two-dimensional short integer array of the same size as the target plate as the initial fractional mask. The height of the array is equal to the height of the target plate, and the width is equal to the width of the target plate. Each array element corresponds to a pixel on the target plate, and the initial value is 0.

[0014] For regional target plates, the processing is performed based on the black and white images of the region. The black and white images of the region represent different target areas, and the pixel values ​​in the corresponding regions will be assigned according to the set scores. In this process, the black and white images of the region are sorted, and the scores are assigned in sequence from the low layer area to the high layer area of ​​the target plate, so that the score of each area is gradually covered from the low layer to the high layer;

[0015] For the playground target, cover the playground rings according to their scores, sort the playground rings in ascending order of scores, and cover the pixels of each ring according to the scores, so that the scores of the inner rings cover the scores of the outer rings;

[0016] According to the saved black and white image of the valid area, some score values ​​of the corresponding area in the score mask are set to 0.

[0017] Further, when a shooting event is detected, the method for generating a score mask based on the curved ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data also includes:

[0018] When the black and white image of the target is not the same size as the target, it is scaled using the nearest neighbor difference:

[0019] Assume that the width and height of the target plate are W target , H target , the size of the regional black and white image is W origin , H origin , then a pixel point (x origin ,y origin ), the corresponding pixel position in the fractional mask (x target ,y target ) The calculation is shown as follows:

[0020]

[0021] Furthermore, the method for caching the score mask includes:

[0022] The score mask of each target board is saved through the Map data structure. The key of the Map is the target board ID, and the value is the score mask corresponding to the target board. When the score mask of the target board is generated, the mask is cached together with the corresponding target board ID.

[0023] Set intervals to automatically clear unused fractional masks, or intelligently determine cache data that should be deleted or updated based on cache usage.

[0024] Furthermore, the method of receiving the coordinate data transmitted by the shooting device and mapping the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache includes:

[0025] According to the image size and coordinate system of the target board, the coordinates of the shooting point are converted into the corresponding position on the target board image using the coordinate mapping algorithm;

[0026] If the coordinate system of the shooting device is inconsistent with the coordinate system of the target image, coordinate normalization is performed so that the shooting point is accurately mapped to the corresponding position on the target image;

[0027] After the mapping is completed, the target board area where the shooting point is located is identified according to its location. By comparing the coordinates of the shooting point with the corresponding area of ​​the target board score mask, it is determined in which scoring area the point is located and the correct score is assigned to it.

[0028] Furthermore, the method of calculating the score of the shooting according to the mapping result and providing real-time feedback to the training personnel includes:

[0029] After receiving the shooting point coordinates and completing the mapping, the score information of the corresponding area in the score mask is searched. If the shooting point is located in multiple overlapping areas, the most appropriate score will be selected for calculation according to the preset rules;

[0030] If the score mask required for the shot already exists in the cache, the score mask in the cache will be used directly for calculation;

[0031] After the calculation is completed, the final score of the shooting is fed back instantly, and the shooting position and scoring area are displayed through the interface, providing instant feedback and analysis for the trainers.

[0032] Furthermore, the curved circular ring shape data of the target plate, the black and white area image data related to the target plate, and the circular ring score setting data or the area score setting data are generated based on a visualization drawing board of scalable vector graphics technology.

[0033] The present application provides a target plate modeling and intelligent scoring system based on image processing technology, including:

[0034] An acquisition unit, used for acquiring curve ring shape data of the target plate, black and white area image data related to the target plate, and ring score setting data or area score setting data;

[0035] A cache generation unit is used to generate a score mask based on the curved ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data when a shooting event is detected, and cache the score mask;

[0036] A mapping unit, for receiving coordinate data transmitted by the shooting device, and mapping the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache;

[0037] The calculation unit is used to calculate the score of the shooting according to the mapping result and provide real-time feedback to the training personnel.

[0038] The present application provides a target plate modeling and intelligent scoring system based on image processing technology, including a memory and a processor;

[0039] The memory is used to store instructions;

[0040] The processor is used to operate according to the instructions to execute the steps according to the above method.

[0041] The present application provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the above method are implemented.

[0042] The beneficial effects of this application are as follows:

[0043] This application uses an intelligent method to achieve the modeling, scoring and dynamic adjustment of the target board in shooting training, and can calculate the shooting score efficiently and accurately;

[0044] Converting the original target board image into a dynamic score mask and calculating the score based on the actual position of each shot can not only improve the accuracy of scoring, but also greatly reduce the interference of human factors, thereby improving training effectiveness and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is an overall flow chart of a target plate modeling and intelligent scoring method based on image processing technology provided according to an embodiment of the present application;

[0046] Figure 2 A diagram of area settings in a target plate modeling and intelligent scoring method based on image processing technology provided according to an embodiment of the present application;

[0047] Figure 3 A playground target curve fitting diagram in a target board modeling and intelligent scoring method based on image processing technology provided in an embodiment of the present application;

[0048] Figure 4 A score mask generation diagram for a target plate modeling and intelligent scoring method based on image processing technology provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] like Figure 1 As shown, the present application provides a target board modeling and intelligent scoring method based on image processing technology, which realizes the modeling, scoring and dynamic adjustment of the target board in shooting training through intelligent methods, and can efficiently and accurately calculate the shooting score. The present application can directly associate the shooting results with the actual target board shape by processing the target board image, thereby solving the shortcomings of traditional shooting training that relies on shock wave target machine, manual scoring and static scoring methods. The specific steps are as follows:

[0050] S100, acquiring the curved circular ring shape data of the target plate, the black and white area image data related to the target plate, and the circular ring score setting data or the area score setting data, specifically including:

[0051] The web front end provides a visual drawing board based on SVG (Scalable Vector Graphics) technology, allowing users to directly set the target board area on the web end. Users can freely draw and edit the fitting curve of the target board through a mouse or touch device, and flexibly adjust the shape of the target board. Figure 2 As shown in the figure, when setting the regional target, similar to the layer concept in image processing software such as Photoshop, users are allowed to upload black and white images (such as scanned target board images) and automatically identify the areas therein. The high-layer area will cover the low-layer area when calculating the score. Users can manually mark these areas and specify the score for each area. The flexibility of area setting enables users to set complex target board structures and scoring rules according to different training needs. For example, the bull's eye area can be set to a high score and the ring area to a low score. The backend accepts and saves the playground target curve and the black and white area map. Users can assign corresponding scores to each custom area according to their needs. By providing a score input box, users are supported to set scores for different areas. Users can set multiple different types of scoring areas, such as circular target areas, rectangular areas, etc. according to the needs of the training scenario.

[0052] When setting up a playground target, you can also use Figure 3The method shown in the figure requires that each playground ring of the playground target needs to be set with a radius r and an offset, where r represents the radius of the two semicircles in the playground target. Offset represents the number of millimeters that the upper and lower semicircles in the playground ring are offset from the upper and lower semicircles of the first playground ring on the y-axis. Assume that the coordinates of the upper and lower semicircles of the first playground ring are (x 1 ,y 1 ),(x 1 ,y 2 ), then a playground ring with r as radius and offset as offset is composed of coordinates (x 1 ,y 1 -offset),(x 1 ,y 2 +offset), the upper and lower semicircles with radius r and the width between them is 2*r, and the height is y 1 -y 2 +2*offset rectangle.

[0053] S200, when a shooting event is detected, generating a target based on the curved ring shape data of the target, the black and white area image data related to the target, and the ring score setting data or the area score setting data. Figure 4 The fractional mask shown is cached, specifically including:

[0054] S201, data extraction: Get relevant information of the target board from the back-end database to support the subsequent scoring calculation process. When the user selects a specific target board, detailed information of the target board will be extracted from the database. This information includes the curved ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data. By querying the target board ID, all data corresponding to the target board are obtained and converted into a standard format that can be processed (such as JSON or a two-dimensional array).

[0055] The extracted data will be checked to ensure the validity of the target plate shape, area settings and score rules. If there are any inconsistencies or errors in the data, an error message will be automatically triggered and the user will be required to reset or correct the data.

[0056] To ensure efficient subsequent processing, the extracted data will be formatted. The target plate area information and score settings will be converted into a two-dimensional matrix or array that is easy to calculate, and the black and white image will be converted into a pixel format that meets the algorithm requirements for subsequent operations.

[0057] S202, initializing the fractional mask: First, a two-dimensional short integer array of the same size as the target plate is initialized as the initial fractional mask. The height of the array is equal to the height of the target plate, the width is equal to the width of the target plate, each array element corresponds to a pixel on the target plate, and the initial value is 0.

[0058] S203, regional target plate score coverage: For regional target plates, they will be processed according to the black and white images of the regions. The black and white images of the regions represent different target areas, and the pixel values ​​in the corresponding regions will be assigned according to the scores set by the user. In this process, the black and white images of the regions are sorted, and the scores are assigned in sequence from the low layer area to the high layer area of ​​the target plate, so that the scores of each region are gradually covered from the low layer to the high layer.

[0059] S204, since the black and white image of the target plate is not necessarily the same size as the target plate, the nearest adjacent difference is used to scale it.

[0060] Assume that the width and height of the target plate are W target , H target , the size of the regional black and white image is W origin , H origin , then a pixel point (x origin ,y origin ), the corresponding pixel position in the score mask (x target ,y target ) The calculation is shown as follows:

[0061]

[0062] S205, playground target score coverage: For the playground target, coverage will be performed according to the scores of each playground ring. First, the playground rings will be sorted in order from small to large scores, and then the pixels of each ring will be covered according to the score. In this way, the score of the inner ring will cover the score of the outer ring, ensuring the accuracy of the score calculation.

[0063] S206, valid area processing: Finally, according to the saved black and white image of the valid area, the score values ​​of the corresponding areas in the score mask are set to 0. The black and white image of the valid area describes which areas are valid scoring areas and which areas should be excluded. According to the image, the scores of some areas that are not in the valid area will be cleared to ensure the accuracy of the scoring.

[0064] S207, save the score mask of each target plate through a Map data structure. The key of the Map is the target plate ID, and the value is the score mask corresponding to the target plate. Whenever the score mask of the target plate is generated, the mask and the corresponding target plate ID will be cached together for quick retrieval next time to avoid repeated calculation.

[0065] S208, in order to avoid performance problems caused by memory overflow or excessive cache, the cache will be emptied regularly. Every once in a while, the score mask that is no longer used will be automatically cleared, or according to the usage of the cache, it will intelligently determine which data should be deleted or updated. This mechanism ensures efficient management of cache data, so that stable operation can be maintained under high load conditions.

[0066] S300, receiving the coordinate data transmitted by the shooting device, and mapping the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache, specifically including:

[0067] S301, according to the image size and coordinate system of the target board, the coordinates of the shooting point are converted into the corresponding position on the target board image using a coordinate mapping algorithm. If the coordinate system of the shooting device is inconsistent with the coordinate system of the target board image, the coordinate normalization process will be performed so that the shooting point is accurately mapped to the corresponding position on the target board image.

[0068] S302, after the mapping is completed, the target board area where the shooting point is located is identified according to the position of the shooting point. By comparing the coordinates of the shooting point with the corresponding area of ​​the target board score mask, it is possible to accurately determine which scoring area the point is located in and assign the correct score to it.

[0069] S400 calculates the score of the shooting based on the mapping results and provides real-time feedback to the training personnel, including:

[0070] S401, after receiving the shooting point coordinates and completing the mapping, the score information of the corresponding area in the score mask will be searched. If the shooting point is located in multiple overlapping areas, the most appropriate score will be selected for calculation according to the preset rules, that is, the area target is based on the layer height, and the playground target is based on the score size.

[0071] S402, if the score mask required for the shooting already exists in the cache, the score mask in the cache will be directly used for calculation, avoiding repeated execution of data extraction and score coverage steps, thereby improving calculation efficiency.

[0072] S403, after the calculation is completed, the final score of the shooting will be fed back immediately, and the shooting position and scoring area will be displayed on the front-end interface to provide instant feedback and analysis for the training personnel.

[0073] The present application provides a target plate modeling and intelligent scoring system based on image processing technology, including:

[0074] An acquisition unit, used for acquiring curve ring shape data of the target plate, black and white area image data related to the target plate, and ring score setting data or area score setting data;

[0075] A cache generation unit is used to generate a score mask based on the curved ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data when a shooting event is detected, and cache the score mask;

[0076] A mapping unit, for receiving coordinate data transmitted by the shooting device, and mapping the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache;

[0077] The calculation unit is used to calculate the score of the shooting according to the mapping result and provide real-time feedback to the training personnel.

[0078] The target plate modeling and intelligent scoring system based on image processing technology provided by the present application may also include: a memory and a processor; the memory is used to store instructions;

[0079] The processor is used to operate according to the instructions to execute the steps of the aforementioned target plate modeling and intelligent scoring method based on image processing technology.

[0080] The present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the aforementioned target plate modeling and intelligent scoring method based on image processing technology are implemented.

[0081] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0082] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0085] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A target plate modeling and intelligent scoring method based on image processing technology, characterized in that: include: Acquire the curved circular ring shape data of the target plate, the black and white area image data related to the target plate, and the circular ring score setting data or the area score setting data; When a shooting event is detected, a score mask is generated based on the curved ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data, and the score mask is cached; When a shooting event is detected, a score mask is generated based on the curved ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data, specifically including: Initialize a two-dimensional short integer array of the same size as the target plate as the initial fractional mask. The height of the array is equal to the height of the target plate, and the width is equal to the width of the target plate. Each array element corresponds to a pixel on the target plate, and the initial value is 0. For regional target plates, the processing is performed based on the black and white images of the region. The black and white images of the region represent different target areas, and the pixel values ​​in the corresponding regions will be assigned according to the set scores. In this process, the black and white images of the region are sorted, and the scores are assigned in sequence from the low layer area to the high layer area of ​​the target plate, so that the score of each area is gradually covered from the low layer to the high layer; For the playground target, cover the playground rings according to their scores, sort the playground rings in ascending order of scores, and cover the pixels of each ring according to the scores, so that the scores of the inner rings cover the scores of the outer rings; According to the saved black and white image of the valid area, some score values ​​of the corresponding area in the score mask are set to 0; Receive the coordinate data transmitted by the shooting device, and map the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache; Based on the mapping results, the score of the shooting is calculated and fed back to the training staff in real time.

2. The target plate modeling and intelligent scoring method based on image processing technology according to claim 1 is characterized in that: When a shooting event is detected, the method for generating a score mask based on the curved ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data also includes: When the black and white image of the target is not the same size as the target, it is scaled using the nearest neighbor difference: Assume that the width and height of the target plate are W target , H target , the size of the regional black and white image is W origin , H origin , then a pixel point (x origin ,y origin ), the corresponding pixel position in the score mask (x target ,y target ) is calculated as follows:

3. The target plate modeling and intelligent scoring method based on image processing technology according to claim 1 is characterized in that: Methods for caching fractional masks include: The score mask of each target board is saved through the Map data structure. The key of the Map is the target board ID, and the value is the score mask corresponding to the target board. When the score mask of the target board is generated, the mask is cached together with the corresponding target board ID. Set intervals to automatically clear unused fractional masks, or intelligently determine cache data that should be deleted or updated based on cache usage.

4. The target plate modeling and intelligent scoring method based on image processing technology according to claim 1 is characterized in that: A method for receiving coordinate data transmitted by a shooting device and mapping a shooting position to each scoring area of ​​a target board according to a target board coordinate system and a score mask in a cache includes: According to the image size and coordinate system of the target board, the coordinates of the shooting point are converted into the corresponding position on the target board image using a coordinate mapping algorithm; if the coordinate system of the shooting device is inconsistent with the coordinate system of the target board image, coordinate normalization processing is performed so that the shooting point is accurately mapped to the corresponding position on the target board image; After the mapping is completed, the target board area where the shooting point is located is identified according to its location. By comparing the coordinates of the shooting point with the corresponding area of ​​the target board score mask, it is determined in which scoring area the point is located and the correct score is assigned to it.

5. The target plate modeling and intelligent scoring method based on image processing technology according to claim 1 is characterized in that: The method of calculating the score of the shooting according to the mapping result and providing real-time feedback to the training personnel includes: After receiving the coordinates of the shooting point and completing the mapping, find the score information of the corresponding area in the score mask. If the shooting point is located in multiple overlapping areas, select the appropriate score for calculation according to the preset rules; If the score mask required for the shot already exists in the cache, the score mask in the cache will be used directly for calculation; After the calculation is completed, the final score of the shooting is fed back instantly, and the shooting position and scoring area are displayed through the interface, providing instant feedback and analysis for the trainers.

6. The target plate modeling and intelligent scoring method based on image processing technology according to claim 1 is characterized in that: The curve ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data are generated based on a visualization drawing board of scalable vector graphics technology.

7. A target plate modeling and intelligent scoring system based on image processing technology, characterized in that: include: An acquisition unit, used for acquiring curve ring shape data of the target plate, black and white area image data related to the target plate, and ring score setting data or area score setting data; A cache generation unit is used to generate a score mask based on the curved ring shape data of the target board, the black and white area image data related to the target board, and the ring score setting data or the area score setting data when a shooting event is detected, and cache the score mask; When a shooting event is detected, a score mask is generated based on the curved ring shape data of the target plate, the black and white area image data related to the target plate, and the ring score setting data or the area score setting data, specifically including: Initialize a two-dimensional short integer array of the same size as the target plate as the initial fractional mask. The height of the array is equal to the height of the target plate, and the width is equal to the width of the target plate. Each array element corresponds to a pixel on the target plate, and the initial value is 0. For regional target plates, the processing is performed based on the black and white images of the region. The black and white images of the region represent different target areas, and the pixel values ​​in the corresponding regions will be assigned according to the set scores. In this process, the black and white images of the region are sorted, and the scores are assigned in sequence from the low layer area to the high layer area of ​​the target plate, so that the score of each area is gradually covered from the low layer to the high layer; For the playground target, cover the playground rings according to their scores, sort the playground rings in ascending order of scores, and cover the pixels of each ring according to the scores, so that the scores of the inner rings cover the scores of the outer rings; According to the saved black and white image of the valid area, some score values ​​of the corresponding area in the score mask are set to 0; A mapping unit, for receiving coordinate data transmitted by the shooting device, and mapping the shooting position to each scoring area of ​​the target board according to the target board coordinate system and the score mask in the cache; The calculation unit is used to calculate the score of the shooting according to the mapping result and provide real-time feedback to the training personnel.

8. A target plate modeling and intelligent scoring system based on image processing technology, characterized in that: including memory and processor; The memory is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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