Method, device and processor for determining agricultural operation information of farmland

Abstract

The application discloses a method, device and processor for determining farmland farming operation information, and belongs to the technical field of farmland management. The method comprises the following steps: acquiring video data of a target farmland; identifying a target farming operation activity in the video data through an image recognition technology; determining a trajectory coordinate of the target farming operation activity in an image frame of the video data through a target tracking technology; and determining a geospatial moving trajectory of the target farming operation activity according to the trajectory coordinate in the image frame based on a predetermined corresponding relationship between image coordinates and geospatial coordinates. The application can automatically record the geospatial moving trajectory of the farming operation activity occurring in the farmland, and has high efficiency.

Description

Technical Field

[0001] The present application relates to the field of farmland management technology, and in particular to a method, device and processor for determining farmland farming operation information. Background Art

[0002] For most farmland management, video surveillance equipment is typically deployed to capture real-time footage of agricultural activities and record agricultural activity information using the video data. However, this recorded agricultural activity information lacks precise location information, necessitating manual supplementation of each activity's location information. Manually supplementing location information for each activity takes a long time and is inefficient. Summary of the Invention

[0003] In order to solve the above technical problems, the purpose of the embodiments of the present application is to provide a method, device, processor and machine-readable storage medium for determining farmland agricultural operation information.

[0004] To achieve the above objectives, a first aspect of an embodiment of the present application provides a method for determining farmland agricultural operation information, the method comprising:

[0005] Obtain video data of the target farmland;

[0006] Identify target agricultural activities in video data using image recognition technology;

[0007] Determine the trajectory coordinates of the target agricultural operation activity in the image frame of the video data by using target tracking technology;

[0008] Based on the predetermined correspondence between the image coordinates and the geographic space coordinates, the geographic space movement trajectory of the target agricultural operation activity is determined according to the trajectory coordinates in the image frame.

[0009] In an embodiment of the present application, video data of the target farmland is collected by a panoramic monitoring device, and the determination of the correspondence between image coordinates and geographic space coordinates includes: constructing a spherical coordinate system with the panoramic monitoring device as the origin, and the radius of the spherical coordinate system is the service radius of the panoramic monitoring device; obtaining the origin geospatial coordinates corresponding to the panoramic monitoring device; obtaining the geospatial coordinates of multiple identification points evenly distributed at preset intervals in the target farmland; and determining the correspondence between image coordinates and geospatial coordinates based on the spherical coordinate system, the origin geospatial coordinates and the geospatial coordinates of the multiple identification points.

[0010] In an embodiment of the present application, determining the correspondence between image coordinates and geospatial coordinates based on a spherical coordinate system, the origin geospatial coordinates, and the geospatial coordinates of a plurality of identification points includes: determining the maximum elevation and the minimum elevation in the geospatial coordinates of the plurality of identification points; determining a target area in the spherical coordinate system based on the difference between the origin elevation and the maximum elevation and the minimum elevation in the geospatial coordinates of the origin, the target area consisting of a plurality of cross-sections parallel to the horizontal plane; dividing the target area into a plurality of grid points at preset intervals; determining the image coordinates of each grid point in the spherical coordinate system; determining the geospatial coordinates of each grid point based on the image coordinates and the origin geospatial coordinates; matching the geospatial coordinates of each identification point with the geospatial coordinates of each grid point to obtain a plurality of target grid points; and associating the image coordinates of each target grid point with the geospatial coordinates of the matched identification point to obtain a correspondence between the image coordinates and the geospatial coordinates.

[0011] In an embodiment of the present application, the panoramic monitoring device is an AR Hawkeye.

[0012] In an embodiment of the present application, determining the correspondence between image coordinates and geographic spatial coordinates includes: determining the target area where the target farmland is located in the video screen of the video data; rasterizing the target area to obtain multiple grid points; determining the image coordinates of each grid point in the video screen; obtaining the geographic spatial coordinates of each grid point in the target farmland; and associating the image coordinates and geographic spatial coordinates of each grid point to obtain the correspondence between the image coordinates and the geographic spatial coordinates.

[0013] In an embodiment of the present application, the method also includes: obtaining multiple target images of target agricultural operation activities in video data; identifying the multiple target images based on a pre-built agricultural tool image library, and determining the agricultural tool image corresponding to each target image to obtain multiple agricultural tool images; determining the agricultural tool image with a higher number of appearances in the multiple agricultural tool images as the target agricultural tool image; and determining the agricultural operation type of the target agricultural operation activity based on the target agricultural tool image.

[0014] In an embodiment of the present application, the method also includes: obtaining the start time and end time of the target agricultural operation activity based on the video data to obtain the operation time of the target agricultural operation activity; and associating and storing the geographic spatial movement trajectory, agricultural operation type and operation time of the target agricultural operation activity.

[0015] A second aspect of an embodiment of the present application provides a processor configured to execute the above-mentioned method for determining farmland agricultural operation information.

[0016] A third aspect of an embodiment of the present application provides a device for determining farmland agricultural operation information, the device comprising:

[0017] A data acquisition module is used to acquire video data of the target farmland;

[0018] An image recognition module, used to identify target agricultural operations in video data using image recognition technology;

[0019] A first determination module is used to determine the trajectory coordinates of the target agricultural operation activity in the image frame of the video data by using target tracking technology;

[0020] The second determining module is used to determine the geospatial movement trajectory of the target agricultural operation activity according to the trajectory coordinates in the image frame based on the predetermined correspondence between the image coordinates and the geospatial coordinates.

[0021] A fourth aspect of an embodiment of the present application provides a machine-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the above-mentioned device for determining farmland agricultural operation information is implemented.

[0022] The above technical solution first obtains video data of the target farmland, then uses image recognition technology to identify the target agricultural operation activities in the video data, then uses target tracking technology to determine the trajectory coordinates of the target agricultural operation activities in the image frames of the video data, and finally, based on the predetermined correspondence between image coordinates and geospatial coordinates, the geospatial movement trajectory of the target agricultural operation activities is determined according to the trajectory coordinates in the image frames. This application can automatically record the geospatial movement trajectory of agricultural operations occurring in farmland with high efficiency.

[0023] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present application but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0025] Figure 1 A flowchart of a method for determining farmland farming operation information provided in an embodiment of the present application;

[0026] Figure 2 This is a structural block diagram of a device for determining farmland agricultural operation information provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0029] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0030] Figure 1 This is a flow chart of a method for determining farmland farming operation information provided in an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a method for determining farmland agricultural operation information. Taking the method applied to a processor as an example, the method may include the following steps:

[0031] Step S101: Acquire video data of a target farmland.

[0032] Step S102: identifying target agricultural activities in the video data using image recognition technology.

[0033] Step S103 : determining the trajectory coordinates of the target farming activity in the image frame of the video data by using target tracking technology.

[0034] Step S104 : Based on the predetermined correspondence between the image coordinates and the geographic space coordinates, the geographic space movement trajectory of the target agricultural operation is determined according to the trajectory coordinates in the image frame.

[0035] In the embodiment of the present application, the target farmland refers to the monitored farmland; the target agricultural operation activity refers to one of the multiple agricultural operation activities occurring in the target farmland. Agricultural operation information includes the operation type, geographic space movement trajectory and operation time of the agricultural operation activity. Among them, the geographic space movement trajectory refers to the movement trajectory of the agricultural operation activity in the geographic space where the target farmland is located in the absolute geodetic coordinate system. The absolute geodetic coordinate system can be the WGS84 coordinate system, etc. In order to monitor the agricultural operation activities occurring in the target farmland in real time and record the agricultural operation information of the agricultural operation activities in real time, the embodiment of the present application processes the video data of the target farmland to obtain the geographic space movement trajectory of the agricultural operation activity.

[0036] Specifically, the processor can obtain in real time the video data of the target farmland collected by the video surveillance equipment. The video surveillance equipment can be installed in a set position that can record all the target farmland according to the shape and elevation of the farmland, as well as the surrounding objects and buildings. Since the video data is composed of an image sequence, including multiple image frames, the changes in the monitoring screen over a period of time can be detected based on the multiple image frames. When changes in the monitoring screen are detected, it means that agricultural operations may have occurred at the corresponding position in the image. Furthermore, to ensure the accuracy of the recognition results, the processor can select the area where the screen has changed in the multiple image frames to obtain multiple intercepted images, and perform object recognition on the multiple intercepted images based on the characteristics of the agricultural operations to determine whether the screen change is caused by agricultural operations. When it is determined that the screen change is caused by agricultural operations, the target agricultural operations identified in the video data are determined. It should be noted that the technical method for performing object recognition on images in the embodiment of the present application can adopt existing technical means, which is not limited here.

[0037] It can be understood that in order to determine the geospatial movement trajectory of the target agricultural operation activity in the target farmland, the processor can track the target agricultural operation activity based on the real-time acquired video data, determine the image coordinates of the agricultural operation activity at each moment in the video data, and thus obtain the movement trajectory of the target agricultural operation activity in the video frame of the video data, that is, the trajectory coordinates. Furthermore, since the trajectory coordinates of the target agricultural operation activity in the image frame are composed of multiple image coordinates, based on the predetermined correspondence between the image coordinates and the geospatial coordinates, the image coordinates in the trajectory coordinates can be converted into corresponding geospatial coordinates, thereby obtaining the geospatial movement trajectory of the target agricultural operation activity in the target farmland. Compared to the method of manually observing and recording the location information of agricultural operation activities in the prior art, the embodiment of the present application realizes the automated recording of the geographical location information of the agricultural operation activity by converting the trajectory coordinates of the agricultural operation activity in the video into the corresponding geospatial movement trajectory, reducing labor costs, and facilitating the accurate recording of the real-time location information of different agricultural operation activities occurring in the target farmland, providing a basis for the realization of refined planting in farmland.

[0038] The above technical solution first obtains video data of the target farmland, then uses image recognition technology to identify the target agricultural operation activities in the video data, then uses target tracking technology to determine the trajectory coordinates of the target agricultural operation activities in the image frames of the video data, and finally, based on the predetermined correspondence between image coordinates and geospatial coordinates, the geospatial movement trajectory of the target agricultural operation activities is determined according to the trajectory coordinates in the image frames. This application can automatically record the geospatial movement trajectory of agricultural operations occurring in farmland with high efficiency.

[0039] In an embodiment of the present application, video data of the target farmland is collected by a panoramic monitoring device, and determining the correspondence between image coordinates and geographic space coordinates may include: constructing a spherical coordinate system with the panoramic monitoring device as the origin, and the radius of the spherical coordinate system is the service radius of the panoramic monitoring device; obtaining the origin geospatial coordinates corresponding to the panoramic monitoring device; obtaining the geospatial coordinates of multiple identification points evenly distributed at preset intervals in the target farmland; and determining the correspondence between image coordinates and geospatial coordinates based on the spherical coordinate system, the origin geospatial coordinates, and the geospatial coordinates of the multiple identification points.

[0040] In an embodiment of the present application, in order to meet the monitoring needs of field planting, the embodiment of the present application adopts a panoramic monitoring device to collect video data of the target farmland. The panoramic monitoring device has a larger shooting range and a finer picture than ordinary monitoring equipment. The panoramic monitoring device can be a panoramic camera or AR Eagle Eye. The correspondence between the image coordinates and the geographic space coordinates can be determined in advance according to the parameters of the panoramic monitoring device itself and the collected video data. The embodiment of the present application is explained by taking the panoramic monitoring device as AR Eagle Eye as an example. By utilizing the panoramic stitching function and image optimization technology of the AR Eagle Eye system, each corner can be monitored more widely and effectively, and all parts of the monitoring area can be partially enlarged. Even in a high-resolution environment, objects within a kilometer range can be clearly marked.

[0041] It is understandable that since the AR Hawkeye installation location is fixed and the monitoring area is also fixed, after the AR Hawkeye is installed, the correspondence between image coordinates and geospatial coordinates can be determined based on the AR Hawkeye installation parameters, the monitored video data, and the geospatial coordinates of the target farmland. Specifically, a three-dimensional spherical coordinate system is first constructed with the AR Hawkeye installation location as the origin. The radius of this spherical coordinate system is the service radius of the AR Hawkeye.

[0042] After constructing the spherical coordinate system, the image coordinates of each point in the spherical coordinate system can be determined, and then the origin geospatial coordinates of AR Eagle Eye in the earth's absolute coordinate system can be obtained, that is, the longitude, latitude and elevation of AR Eagle Eye. Since the target farmland is within the monitoring range of AR Eagle Eye, the spherical coordinate system includes image coordinate data corresponding to the area where the target farmland is located. In order to determine the image coordinates of the area corresponding to the target farmland in the spherical coordinate system, the geospatial coordinates of multiple identification points on the target farmland imported by the technicians can be obtained, and the multiple identification points are evenly arranged on the target farmland according to preset intervals. It can be understood that the smaller the preset interval, the more identification points, and the higher the accuracy of the subsequent calculation results. Finally, the processor can determine the correspondence between the image coordinates and the geospatial coordinates based on the spherical coordinate system, the origin geospatial coordinates and the geospatial coordinates of the multiple identification points.

[0043] In one example, the processor can convert the image coordinates of each point in the spherical coordinate system into corresponding geospatial coordinates based on the origin geospatial coordinates of AR Eagle Eye, and then match the geospatial coordinates of multiple identification points of the target farmland with the geospatial coordinates of each point in the spherical coordinate system, mark all coordinate points in the spherical coordinate system that are successfully matched, and obtain the coordinate area corresponding to the target farmland in the spherical coordinate system. Finally, the image coordinates of all points in the coordinate area are associated with the corresponding geospatial coordinates and the correspondence between the image coordinates and the geospatial coordinates is obtained. In this way, when subsequently determining the geospatial movement trajectory of agricultural operations, it is only necessary to obtain the image coordinates in the video data based on the correspondence between the pre-stored image coordinates and the geospatial coordinates, thereby realizing spatial processing of video data.

[0044] In an embodiment of the present application, determining the correspondence between image coordinates and geospatial coordinates based on a spherical coordinate system, the origin geospatial coordinates, and the geospatial coordinates of a plurality of identification points may include: determining the maximum elevation and the minimum elevation in the geospatial coordinates of the plurality of identification points; determining a target area in the spherical coordinate system based on the difference between the origin elevation and the maximum elevation and the minimum elevation in the origin geospatial coordinates, the target area consisting of a plurality of cross-sections parallel to the horizontal plane; dividing the target area into a plurality of grid points at preset intervals; determining the image coordinates of each grid point in the spherical coordinate system; determining the geospatial coordinates of each grid point based on the image coordinates and the origin geospatial coordinates; matching the geospatial coordinates of each identification point with the geospatial coordinates of each grid point to obtain a plurality of target grid points; and associating the image coordinates of each target grid point with the geospatial coordinates of the matched identification point to obtain a correspondence between the image coordinates and the geospatial coordinates.

[0045] Specifically, in order to improve the efficiency of data processing and reduce the amount of data that needs to be processed, multiple sections in the spherical coordinate system can be located by the maximum elevation and minimum elevation of multiple identification points of the target farmland. It can be understood that the elevation difference between the AR Eagle Eye and the target farmland is determined, and the elevation difference between the maximum elevation and minimum elevation of multiple identification points and the AR Eagle Eye is determined respectively, that is, the maximum elevation difference and the minimum elevation difference are obtained. It is known that the target farmland is on the plane directly below the AR Eagle Eye. Therefore, the target area in the spherical coordinate system can be determined based on the maximum elevation difference and the minimum elevation difference. The target area refers to the area between the plane directly below the origin and the plane with the maximum elevation difference and the plane with the minimum elevation difference from the origin in the spherical coordinate system. Since multiple identification points in the target farmland are selected according to preset intervals, the target area can be divided into multiple sections parallel to the horizontal plane with elevation differences of preset intervals in the embodiment of the present application. In this way, the amount of data during subsequent data processing can be reduced and the data processing efficiency can be improved.

[0046] Furthermore, each slice is rasterized at preset intervals to obtain multiple grid points. The image coordinates of each grid point in the spherical coordinate system are determined, and the image coordinates of each grid point are converted into corresponding geospatial coordinates based on the origin's geospatial coordinates. The geospatial coordinates of each marker point are then matched with the geospatial coordinates of each grid point to obtain multiple successfully matched target grid points. Finally, the image coordinates of each target grid point are associated and stored with the geospatial coordinates of the matched marker point, thereby obtaining a corresponding relationship between the image coordinates and the geospatial coordinates. This significantly reduces the amount of data to be processed and improves data processing efficiency.

[0047] In an embodiment of the present application, determining the correspondence between image coordinates and geographic spatial coordinates may include: determining the target area where the target farmland is located in the video screen of the video data; performing rasterization processing on the target area to obtain multiple grid points; determining the image coordinates of each grid point in the video screen; obtaining the geographic spatial coordinates of each grid point in the target farmland; associating the image coordinates and geographic spatial coordinates of each grid point to obtain the correspondence between the image coordinates and the geographic spatial coordinates.

[0048] It can be understood that since the position of the target farmland in the video data is fixed in the video screen, the geographic spatial coordinate information of the target farmland can be directly entered in advance by manual calibration. Specifically, first calibrate the target area where the target farmland is located in the video screen, and then rasterize the target area to rasterize the target farmland in the video screen into multiple cells to obtain multiple grid points. Among them, one cell corresponds to one grid point. Then determine the image coordinates of each grid point in the video screen, and the image coordinates are two-dimensional coordinates. Furthermore, based on the multiple grid points, manually collect the geographic spatial coordinates of the block in the target farmland corresponding to each grid point in the real scene, and then import the collected multiple geographic spatial coordinates into the system. After the processor obtains the geographic spatial coordinates of each grid point in the target farmland, it associates and stores the image coordinates and geographic spatial coordinates of each grid point, that is, obtains the corresponding relationship between the image coordinates and the geographic spatial coordinates.

[0049] In an embodiment of the present application, the method may further include: obtaining multiple target images of target agricultural operation activities in the video data; identifying the multiple target images respectively based on a pre-built agricultural tool image library, and determining the agricultural tool image corresponding to each target image to obtain multiple agricultural tool images; determining the agricultural tool image with a higher number of appearances in the multiple agricultural tool images as the target agricultural tool image; and determining the agricultural operation type of the target agricultural operation activity based on the target agricultural tool image.

[0050] Specifically, the agricultural tool image library refers to a database that includes multiple agricultural tool images, and each agricultural tool image is associated with and stored with a corresponding agricultural operation type. The processor can obtain multiple target images of the target agricultural operation activity in the video data. The target image refers to an image that only includes the area where the target agricultural operation activity is located after cropping. Then, based on the pre-built agricultural tool image library, image recognition is performed on each target image separately, and the agricultural tool image with the highest matching degree with the target image in the agricultural tool image library is identified, thereby obtaining the agricultural tool images corresponding to the multiple target images. Furthermore, the agricultural tool image that appears the most times among the multiple agricultural tool images is used as the target agricultural tool image, and the agricultural operation type corresponding to the target agricultural tool image is determined, that is, the agricultural operation type of the target agricultural operation activity is obtained. In this way, the agricultural operation type of the agricultural operation activity is determined by image recognition, which facilitates subsequent inquiries and farmland management, and provides a data foundation for realizing refined farmland operations.

[0051] In an embodiment of the present application, the method may further include: obtaining the start time and end time of the target agricultural operation activity based on the video data to obtain the operation time of the target agricultural operation activity; and associating and storing the geographic spatial movement trajectory, agricultural operation type and operation time of the target agricultural operation activity.

[0052] Specifically, to achieve refined farmland management, the processor can obtain the operating time of a target agricultural activity, including its start and end times, which can be directly captured from video data. Furthermore, the geospatial movement trajectory of the target agricultural activity, the agricultural activity type, and the operating time are associated and stored to obtain agricultural operation information for the target agricultural activity. In this way, by utilizing target tracking and image recognition technologies to analyze the geospatial coordinate information of agricultural activities in video footage in real time, and combining this with other agricultural action recognition algorithms, the combined automated reporting of agricultural operations and spatial location information is achieved, facilitating refined farmland management.

[0053] An embodiment of the present application also provides a processor configured to execute the above-mentioned method for determining farmland agricultural operation information.

[0054] Figure 2 This is a structural block diagram of a device for determining farmland farming operation information provided in an embodiment of the present application. Figure 2 As shown, the embodiment of the present application further provides a device 200 for determining farmland agricultural operation information, the device 200 comprising:

[0055] The data acquisition module 210 is used to acquire video data of the target farmland.

[0056] The image recognition module 220 is configured to recognize target agricultural operations in the video data using image recognition technology.

[0057] The first determining module 230 is configured to determine the trajectory coordinates of the target farming activity in the image frame of the video data by using target tracking technology.

[0058] The second determining module 240 is configured to determine the geospatial movement trajectory of the target agricultural operation activity according to the trajectory coordinates in the image frame based on the predetermined correspondence between the image coordinates and the geospatial coordinates.

[0059] The above-mentioned device 200 for determining farmland agricultural operation information first obtains video data of the target farmland, then uses image recognition technology to identify the target agricultural operation activity in the video data, then uses target tracking technology to determine the trajectory coordinates of the target agricultural operation activity in the image frame of the video data, and finally, based on the predetermined correspondence between the image coordinates and the geographic space coordinates, determines the geospatial movement trajectory of the target agricultural operation activity according to the trajectory coordinates in the image frame. This application can automatically record the geospatial movement trajectory of agricultural operation activities occurring in farmland with high efficiency.

[0060] In one embodiment, video data of the target farmland is collected by a panoramic monitoring device, and the device 200 is also used to: construct a spherical coordinate system with the panoramic monitoring device as the origin, and the radius of the spherical coordinate system is the service radius of the panoramic monitoring device; obtain the origin geospatial coordinates corresponding to the panoramic monitoring device; obtain the geospatial coordinates of multiple identification points uniformly distributed at preset intervals in the target farmland; determine the correspondence between image coordinates and geospatial coordinates based on the spherical coordinate system, the origin geospatial coordinates and the geospatial coordinates of multiple identification points.

[0061] In one embodiment, the device 200 is also used to: determine the maximum elevation and the minimum elevation in the geospatial coordinates of multiple identification points; determine the target area in the spherical coordinate system based on the difference between the origin elevation and the maximum elevation and the minimum elevation in the origin geospatial coordinates, the target area consisting of multiple sections parallel to the horizontal plane; divide the target area into multiple grid points according to preset intervals; determine the image coordinates of each grid point in the spherical coordinate system; determine the geospatial coordinates of each grid point based on the image coordinates and the origin geospatial coordinates; match the geospatial coordinates of each identification point with the geospatial coordinates of each grid point to obtain multiple target grid points; associate the image coordinates of each target grid point with the geospatial coordinates of the matched identification point to obtain a corresponding relationship between the image coordinates and the geospatial coordinates.

[0062] In one embodiment, the panoramic monitoring device is an AR Hawkeye.

[0063] In one embodiment, the device 200 is also used to: determine the target area where the target farmland is located in the video screen of the video data; perform rasterization processing on the target area to obtain multiple grid points; determine the image coordinates of each grid point in the video screen; obtain the geographic spatial coordinates of each grid point in the target farmland; associate the image coordinates and geographic spatial coordinates of each grid point to obtain the corresponding relationship between the image coordinates and the geographic spatial coordinates.

[0064] In one embodiment, the device 200 is also used to: obtain multiple target images of target agricultural operation activities in video data; identify the multiple target images based on a pre-built agricultural tool image library, determine the agricultural tool image corresponding to each target image, and obtain multiple agricultural tool images; determine the agricultural tool image with a higher number of appearances in the multiple agricultural tool images as the target agricultural tool image; determine the agricultural operation type of the target agricultural operation activity based on the target agricultural tool image.

[0065] In one embodiment, the device 200 is also used to: obtain the start time and end time of the target agricultural operation activity based on the video data to obtain the operation time of the target agricultural operation activity; and associate and store the geographic spatial movement trajectory, agricultural operation type and operation time of the target agricultural operation activity.

[0066] An embodiment of the present application also provides a machine-readable storage medium, which stores a program or instruction. When the program or instruction is executed by a processor, the device for determining farmland agricultural operation information in the above-mentioned embodiment is implemented.

[0067] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems or computer program products. Therefore, the present application can 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 can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0068] 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 produce 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 1A device that provides the functions specified in a block or multiple blocks.

[0069] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0070] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0071] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0072] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0073] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0074] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0075] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for determining farmland agricultural operation information, characterized in that: The method comprises: Obtain video data of the target farmland; identifying target agricultural operations in the video data using image recognition technology; Determining the trajectory coordinates of the target agricultural operation activity in the image frame of the video data by target tracking technology; Based on the predetermined correspondence between the image coordinates and the geographic space coordinates, determining the geographic space movement trajectory of the target agricultural operation activity according to the trajectory coordinates in the image frame; The video data of the target farmland is collected by panoramic monitoring equipment, and the corresponding relationship between the image coordinates and the geographic space coordinates is determined including: Constructing a spherical coordinate system with the panoramic monitoring device as the origin, where the radius of the spherical coordinate system is the service radius of the panoramic monitoring device; Obtaining the origin geographic space coordinates corresponding to the panoramic monitoring device; Obtaining the geographic spatial coordinates of a plurality of identification points evenly distributed at preset intervals in the target farmland; Determining the maximum elevation and the minimum elevation in the geospatial coordinates of the plurality of identification points; Determining a target area in the spherical coordinate system according to differences between the origin elevation in the origin geographic space coordinates and the maximum elevation and the minimum elevation, wherein the target area is composed of a plurality of sections parallel to a horizontal plane; Dividing the target area into a plurality of grid points according to preset intervals; Determining the image coordinates of each of the grid points in the spherical coordinate system; Determining the geospatial coordinates of each grid point based on the image coordinates and the geospatial coordinates of the origin; Matching the geospatial coordinates of each identification point with the geospatial coordinates of each grid point to obtain a plurality of target grid points; The image coordinates of each target grid point are associated with the geographic space coordinates of the matching identification point to obtain a corresponding relationship between the image coordinates and the geographic space coordinates.

2. The method according to claim 1, characterized in that The panoramic monitoring device is AR Eagle Eye.

3. The method according to claim 1, characterized in that Determining the correspondence between the image coordinates and the geographic space coordinates includes: Determining a target area where the target farmland is located in a video frame of the video data; Performing a rasterization process on the target area to obtain a plurality of grid points; Determining the image coordinates of each of the grid points in the video image; Obtaining the geographic spatial coordinates of each of the grid points in the target farmland; The image coordinates and the geographic space coordinates of each grid point are associated to obtain a corresponding relationship between the image coordinates and the geographic space coordinates.

4. The method according to claim 1, wherein The method further comprises: Acquire multiple target images of the target agricultural operation activity in the video data; Recognizing the plurality of target images based on a pre-built agricultural tool image library, and determining an agricultural tool image corresponding to each target image, so as to obtain a plurality of agricultural tool images; determining the agricultural tool image with a higher number of appearances among the plurality of agricultural tool images as a target agricultural tool image; The agricultural operation type of the target agricultural operation activity is determined according to the target agricultural implement image.

5. The method according to claim 1, wherein The method further comprises: Acquire the start time and end time of the target agricultural operation activity according to the video data to obtain the operation time of the target agricultural operation activity; The geographic space movement trajectory of the target agricultural operation activity, the agricultural operation type and the operation time are associated and stored.

6. A processor, characterized in that: The method is configured to execute the method for determining farmland farming operation information according to any one of claims 1 to 5.

7. A device for determining farmland agricultural operation information, characterized in that: The device comprises: A data acquisition module is used to acquire video data of the target farmland; An image recognition module, configured to identify target agricultural operations in the video data using image recognition technology; A first determining module is configured to determine the trajectory coordinates of the target agricultural operation in the image frame of the video data by using target tracking technology; a second determining module, configured to determine the geospatial movement trajectory of the target agricultural operation activity according to the trajectory coordinates in the image frame based on a predetermined correspondence between the image coordinates and the geospatial coordinates; The video data of the target farmland is collected by panoramic monitoring equipment, and the second determination module is further configured to: Constructing a spherical coordinate system with the panoramic monitoring device as the origin, where the radius of the spherical coordinate system is the service radius of the panoramic monitoring device; Obtaining the origin geographic space coordinates corresponding to the panoramic monitoring device; Obtaining the geographic spatial coordinates of a plurality of identification points evenly distributed at preset intervals in the target farmland; Determining the maximum elevation and the minimum elevation in the geospatial coordinates of the plurality of identification points; Determining a target area in the spherical coordinate system according to differences between the origin elevation in the origin geographic space coordinates and the maximum elevation and the minimum elevation, wherein the target area is composed of a plurality of sections parallel to a horizontal plane; Dividing the target area into a plurality of grid points according to preset intervals; Determining the image coordinates of each of the grid points in the spherical coordinate system; Determining the geospatial coordinates of each grid point based on the image coordinates and the geospatial coordinates of the origin; Matching the geospatial coordinates of each identification point with the geospatial coordinates of each grid point to obtain a plurality of target grid points; The image coordinates of each target grid point are associated with the geographic space coordinates of the matching identification point to obtain a corresponding relationship between the image coordinates and the geographic space coordinates.

8. A machine-readable storage medium storing a program or instruction, characterized in that: When the program or the instructions are executed by a processor, the method for determining farmland agricultural operation information according to any one of claims 1 to 5 is implemented.

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