CN112543289A - AI (artificial intelligence) video point counting method, device, equipment and medium for pig breeding - Google Patents
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Abstract
The invention provides an AI video point counting method, device, equipment and medium for pig breeding, wherein the method comprises the following steps: periodically acquiring a video of a pig farm, wherein the video is a continuous video; analyzing the video to obtain a video stream of the collected specified closed area, and processing the video stream to obtain a key frame set; splicing the key frames in the key frame combination by adopting an image splicing technology to eliminate repeated images and form a complete image containing all live pigs in the pig farm; counting according to the complete image to obtain the number of live pigs; the counting efficiency and the counting precision are improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an AI video point counting method, device, equipment and medium for pig breeding.
Background
In recent years, stable production and guarantee supply of live pigs become important civil engineering concerned by governments, and policy documents are issued in sequence by all levels of governments, silver insurance guidances and silver insurance bureaus in provinces and cities, so that live pig mortgages are supported to be developed, and the financing requirements of the live pig industry are better met.
With the increase of loan dispensing force for farmers who use pigs as mortgages, it is urgent to reduce risks after loan. The live pig breeding loan evaluates the repayment capacity of the farmer according to the number of live pigs, so that banks need to know the current breeding number of live pigs of the farmer in time and take the breeding number as a means for post-loan management.
At present, the main method for knowing the number of pigs born by farmers is that a bank client manager randomly checks the number of pigs in a farm of the farmers. The method has obvious defects that firstly, time and labor are wasted, a customer manager needs to take time to reach a pig farm of a farmer, the farm is mostly in a remote rural area, the whole process is long in time consumption, if more farmers loan is available, full coverage after loan cannot be achieved, and the efficiency is extremely low; second, the artificial pig spotting error is large. Particularly, in a farm with a large number of pigs, live pigs are in a moving state, and the live pigs move positions in a long-time counting process, so that people are difficult to avoid dazzling and are easy to have counting errors. Thirdly, no effective supervision measures exist, and the operation risk of fraudulent loan communication between a customer manager and a farmer is easy to occur.
Disclosure of Invention
The invention aims to provide an AI video counting method, device, equipment and medium for pig breeding, which can improve counting efficiency and counting accuracy.
In a first aspect, the invention provides an AI video point counting method for pig breeding, which comprises the following steps:
step 1, periodically acquiring a video of a pig farm, wherein the video is a continuous video;
step 2, analyzing the video, acquiring a video stream of the collected specified closed area, processing the video stream, and acquiring a key frame set;
step 3, splicing the key frames in the key frame combination by adopting an image splicing technology to eliminate repeated images and form a complete image containing all live pigs in the pig farm;
and 4, counting according to the complete image to obtain the number of live pigs.
Further, the step 2 is further specifically: analyzing the video to obtain the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; visual features of videos are extracted from video streams, the features are clustered, and then a key frame set is selected from the clustered video frames, wherein the key frame set is a group of key frame frames used for showing the number of pigs and covers the whole pig farm completely.
Further, the step 3 is further specifically: for the overlapped part existing among the key frames in the key frame set, an image splicing technology is utilized, starting from the gray value of the key frames, the difference of the gray value of a region in the key frames and the region with the same size in the reference image is calculated, after the difference is compared, the similarity degree of the overlapped region in the key frames is judged, if the similarity degree reaches a limit value, the overlapped part is determined, and therefore the range and the position of the overlapped region of the key frames are obtained, the key frame splicing is realized, repeated images are eliminated, and a complete image containing all live pigs in a pig farm is formed.
Further, the step 4 is further specifically: and analyzing the complete image by using an example segmentation and counting technology based on deep learning, identifying and segmenting the live pigs one by one, and counting and recording the number of the live pigs in the pig farm at the current time point.
In a second aspect, the present invention provides an AI video spot count device for pig breeding, comprising:
the video acquisition module is used for periodically acquiring a video of a pig farm, wherein the video is a continuous video;
the key frame module is used for analyzing the video, acquiring a video stream of the acquired specified closed area, processing the video stream and acquiring a key frame set;
the splicing module is used for splicing the key frames in the key frame combination by adopting an image splicing technology to eliminate repeated images and form a complete image containing all live pigs in the pig farm;
and the counting module counts according to the complete image to obtain the number of the live pigs.
Further, the key frame module is further specifically: analyzing the video to obtain the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; visual features of videos are extracted from video streams, the features are clustered, and then a key frame set is selected from the clustered video frames, wherein the key frame set is a group of key frame frames used for showing the number of pigs and covers the whole pig farm completely.
Further, the splicing module further specifically includes: for the overlapped part existing among the key frames in the key frame set, an image splicing technology is utilized, starting from the gray value of the key frames, the difference of the gray value of a region in the key frames and the region with the same size in the reference image is calculated, after the difference is compared, the similarity degree of the overlapped region in the key frames is judged, if the similarity degree reaches a limit value, the overlapped part is determined, and therefore the range and the position of the overlapped region of the key frames are obtained, the key frame splicing is realized, repeated images are eliminated, and a complete image containing all live pigs in a pig farm is formed.
Further, the point module is further specifically: and analyzing the complete image by using an example segmentation and counting technology based on deep learning, identifying and segmenting the live pigs one by one, and counting and recording the number of the live pigs in the pig farm at the current time point.
In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of the first aspect when executing the program.
In a fourth aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the first aspect.
One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:
1. compared with the traditional mode of ordering pigs on site by depending on manpower, the time cost is greatly reduced by uploading a video remote analysis point number mode, a customer manager does not need to arrive at the site in person, and various costs consumed on the way are saved;
2. compared with the traditional method, the video pig counting method has the advantages that the video pig counting method can count the number of live pigs in one pig farm within seconds by utilizing high-speed operation of a background, and compared with manual pig counting method, the efficiency is greatly improved as the pigs are counted one by one within tens of minutes;
3. compared with the traditional method, the video is shot and automatically uploaded through the mobile phone APP, the video stream is analyzed by the background to finish pig ordering, time is saved, meanwhile, full coverage of post-loan management can be achieved, and loan risks are reduced;
4. compared with the traditional method, the video frequency pig process is reserved in a bank system every time, and the management after each loan can be traced, so that the supervision is facilitated, and the operation risk is reduced.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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The invention will be further described with reference to the following examples with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method according to one embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device according to a second embodiment of the present invention.
Detailed Description
The embodiment of the application provides an AI video counting method, device, equipment and medium for live pig breeding, solves the problems of low counting efficiency and cheating credit, and improves the counting efficiency and the counting accuracy.
The technical scheme in the embodiment of the application has the following general idea:
1. the raiser shoots a section of continuous video around the pig farm regularly through the mobile phone APP, and the system automatically uploads the video to the background.
2. The method comprises the steps that after a system background obtains a video, the video is analyzed, the collected video stream of the appointed closed area is obtained, the video stream comprises a moving target moving in the appointed closed area, the characteristics of the video, such as vision, are extracted from the video stream, then the characteristics are clustered, and then a key frame set is selected from the clustered video frames. The key frame set can well display a group of key frame frames of the number of pigs, and can fully cover the whole pig farm.
3. For the overlapped part existing between the image frames, an image splicing technology is utilized, starting from the gray value of the image to be spliced, the difference of the gray value of an area in the image to be registered and the area with the same size in the reference image is calculated by using a least square method or other mathematical methods, the similarity degree of the overlapped area of the image to be spliced is judged after the difference is compared, and therefore the range and the position of the overlapped area of the image to be spliced are obtained, the image splicing is realized, the repeated image is eliminated, and a complete image containing all live pigs in a pig farm is formed.
4. Pig farm images were analyzed using example segmentation and counting techniques based on deep learning. Inputting the acquired image into a trained deep learning model to obtain the deep learning model, wherein the deep learning model is used for identifying a moving target from the input image and outputting parameter information of the moving target; the moving targets are identified from the images through the trained deep learning model, the parameter information of the moving targets is obtained, the image area information and the type labels in the parameter information of different moving targets are used for counting the number of the moving targets in the designated area, and therefore the moving targets of different types are counted through pure machine vision. Identifying and dividing the pigs one by one, and counting and recording the number of live pigs in the pig farm at the current time point.
Example one
As shown in fig. 1, the present embodiment provides an AI video point method for pig breeding, which includes:
step 1, periodically acquiring a video of a pig farm, wherein the video is a continuous video;
step 2, analyzing the video to obtain the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; extracting visual features of videos from video streams, clustering the features, and selecting a key frame set from the clustered video frames, wherein the key frame set is a group of key frame frames for showing the number of pigs and covers the whole pig farm completely;
step 3, calculating the difference of the gray values of a region in the key frame and a region with the same size in the reference image from the gray value of the key frame by using an image splicing technology for the overlapped part existing among the key frames in the key frame set, comparing the difference, judging the similarity degree of the overlapped region in the key frame, and if the similarity degree reaches a limit value, determining the overlapped part, thereby obtaining the range and the position of the overlapped region of the key frame, realizing key frame splicing, eliminating repeated images and forming a complete image containing all live pigs in a pig farm;
and 4, analyzing the complete image by using an example segmentation and counting technology based on deep learning, identifying and segmenting the live pigs one by one, and counting and recording the number of the live pigs in the pig farm at the current time point.
Based on the same inventive concept, the application also provides a device corresponding to the method in the first embodiment, which is detailed in the second embodiment.
Example two
As shown in fig. 2, in the second aspect provided in the present embodiment, the present invention provides an AI video spot count device for live pig breeding, including:
the video acquisition module is used for periodically acquiring a video of a pig farm, wherein the video is a continuous video;
the key frame module is used for analyzing the video and acquiring the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; extracting visual features of videos from video streams, clustering the features, and selecting a key frame set from the clustered video frames, wherein the key frame set is a group of key frame frames for showing the number of pigs and covers the whole pig farm completely;
the splicing module is used for calculating the difference of gray values of a region in the key frame and a region with the same size in the reference image from the gray value of the key frame by using an image splicing technology for the overlapped part existing among the key frames in the key frame set, judging the similarity degree of the overlapped region in the key frame after comparing the difference, and obtaining the range and the position of the overlapped region of the key frame if the similarity degree reaches a limit value, so that the key frame splicing is realized, repeated images are eliminated, and a complete image containing all live pigs in a pig farm is formed;
and the counting module analyzes the complete image by utilizing an example segmentation and counting technology based on deep learning, identifies and segments the live pigs one by one, and counts and records the number of the live pigs in the pig farm at the current time point.
Since the apparatus described in the second embodiment of the present invention is an apparatus used for implementing the method of the first embodiment of the present invention, based on the method described in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the apparatus, and thus the details are not described herein. All the devices adopted in the method of the first embodiment of the present invention belong to the protection scope of the present invention.
Based on the same inventive concept, the application provides an electronic device embodiment corresponding to the first embodiment, which is detailed in the third embodiment.
EXAMPLE III
The embodiment provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, any one of the embodiments may be implemented.
Since the electronic device described in this embodiment is a device used for implementing the method in the first embodiment of the present application, based on the method described in the first embodiment of the present application, a specific implementation of the electronic device in this embodiment and various variations thereof can be understood by those skilled in the art, and therefore, how to implement the method in the first embodiment of the present application by the electronic device is not described in detail herein. The equipment used by those skilled in the art to implement the methods in the embodiments of the present application is within the scope of the present application.
Based on the same inventive concept, the application provides a storage medium corresponding to the fourth embodiment, which is described in detail in the fourth embodiment.
Example four
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, any one of the first embodiment can be implemented.
The technical scheme provided in the embodiment of the application at least has the following technical effects or advantages: the method, device, equipment and medium provided by the embodiment of the application,
as will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.
Claims (10)
1. An AI video point counting method for pig breeding is characterized in that: the method comprises the following steps:
step 1, periodically acquiring a video of a pig farm, wherein the video is a continuous video;
step 2, analyzing the video, acquiring a video stream of the collected specified closed area, processing the video stream, and acquiring a key frame set;
step 3, splicing the key frames in the key frame combination by adopting an image splicing technology to eliminate repeated images and form a complete image containing all live pigs in the pig farm;
and 4, counting according to the complete image to obtain the number of live pigs.
2. The AI video point method for pig breeding according to claim 1, characterized in that: the step 2 is further specifically as follows: analyzing the video to obtain the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; visual features of videos are extracted from video streams, the features are clustered, and then a key frame set is selected from the clustered video frames, wherein the key frame set is a group of key frame frames used for showing the number of pigs and covers the whole pig farm completely.
3. The AI video point method for pig breeding according to claim 1, characterized in that: the step 3 is further specifically as follows: for the overlapped part existing among the key frames in the key frame set, an image splicing technology is utilized, starting from the gray value of the key frames, the difference of the gray value of a region in the key frames and the region with the same size in the reference image is calculated, after the difference is compared, the similarity degree of the overlapped region in the key frames is judged, if the similarity degree reaches a limit value, the overlapped part is determined, and therefore the range and the position of the overlapped region of the key frames are obtained, the key frame splicing is realized, repeated images are eliminated, and a complete image containing all live pigs in a pig farm is formed.
4. The AI video point method for pig breeding according to claim 1, characterized in that: the step 4 is further specifically as follows: and analyzing the complete image by using an example segmentation and counting technology based on deep learning, identifying and segmenting the live pigs one by one, and counting and recording the number of the live pigs in the pig farm at the current time point.
5. The utility model provides a device is counted to AI video for live pig is bred which characterized in that: the method comprises the following steps:
the video acquisition module is used for periodically acquiring a video of a pig farm, wherein the video is a continuous video;
the key frame module is used for analyzing the video, acquiring a video stream of the acquired specified closed area, processing the video stream and acquiring a key frame set;
the splicing module is used for splicing the key frames in the key frame combination by adopting an image splicing technology to eliminate repeated images and form a complete image containing all live pigs in the pig farm;
and the counting module counts according to the complete image to obtain the number of the live pigs.
6. The AI video point device for live pig breeding of claim 5, wherein: the key frame module is further specifically: analyzing the video to obtain the collected video stream of the appointed closed area, wherein the video stream comprises a moving target moving in the appointed closed area; visual features of videos are extracted from video streams, the features are clustered, and then a key frame set is selected from the clustered video frames, wherein the key frame set is a group of key frame frames used for showing the number of pigs and covers the whole pig farm completely.
7. The AI video point device for live pig breeding of claim 5, wherein: the splicing module further specifically comprises: for the overlapped part existing among the key frames in the key frame set, an image splicing technology is utilized, starting from the gray value of the key frames, the difference of the gray value of a region in the key frames and the region with the same size in the reference image is calculated, after the difference is compared, the similarity degree of the overlapped region in the key frames is judged, if the similarity degree reaches a limit value, the overlapped part is determined, and therefore the range and the position of the overlapped region of the key frames are obtained, the key frame splicing is realized, repeated images are eliminated, and a complete image containing all live pigs in a pig farm is formed.
8. The AI video point device for live pig breeding of claim 5, wherein: the counting module is further specifically: and analyzing the complete image by using an example segmentation and counting technology based on deep learning, identifying and segmenting the live pigs one by one, and counting and recording the number of the live pigs in the pig farm at the current time point.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 4 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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| CN202110285790.2A CN113038035B (en) | 2020-10-29 | 2021-03-17 | AI video point counting method for live pig breeding |
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| US10574692B2 (en) * | 2016-05-30 | 2020-02-25 | Christopher Nathan Tyrwhitt Drake | Mutual authentication security system with detection and mitigation of active man-in-the-middle browser attacks, phishing, and malware and other security improvements |
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| CN108090357A (en) * | 2017-12-14 | 2018-05-29 | 湖南财政经济学院 | A kind of computer information safe control method and device |
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