CN112926359A - Crop identification method and device, and control method of operation equipment - Google Patents
Crop identification method and device, and control method of operation equipment Download PDFInfo
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Abstract
The application discloses a crop identification method and device and a control method of operation equipment. Wherein, the method comprises the following steps: acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; and identifying the individual information of the target crop according to the image data and the second point cloud height information. The method and the device solve the technical problem that the distribution range of the fruit trees is mapped by utilizing the two-dimensional RGB image at the present stage, and each fruit tree is difficult to accurately identify due to the fact that the fruit trees are intersected with each other.
Description
Technical Field
The application relates to the field of plant protection, in particular to a crop identification method and device and a control method of operation equipment.
Background
At present, when an unmanned aerial vehicle carries out plant protection operation on fruit trees, the distribution range of the fruit trees and the size of the fruit trees are required to be manually mapped, or aerial survey high-definition RGB images are used for image segmentation so as to identify the position information of the fruit trees, but the manual mapping is high in time-consuming cost, and the simple RGB images are not good for orchard with dense length.
Fig. 1 is a two-dimensional RGB image of a fruit tree, if the fruit tree is detected by using only the two-dimensional RGB image, the detection result shown in fig. 2 is obtained, and since the fruit trees are intersected with each other, it is difficult to accurately identify each fruit tree by using only the two-dimensional image.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a crop identification method and device and a control method of operation equipment, and aims to at least solve the technical problem that the distribution range of fruit trees is mapped by using a two-dimensional RGB image at the present stage, and each fruit tree is difficult to accurately identify due to the fact that the fruit trees are intersected with each other.
According to an aspect of an embodiment of the present application, there is provided a crop identification method, including: acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; and identifying the individual information of the target crop according to the image data and the second point cloud height information.
Optionally, determining second point cloud height information of the target crop according to the first point cloud height information includes: taking the area in which the height value of the point cloud corresponding to the first point cloud height information gradually decreases from the middle to the periphery as the area in which the target crop is located; and taking the first point cloud height information corresponding to the area where the target crop is located as second point cloud height information.
Optionally, determining second point cloud height information of the target crop according to the first point cloud height information, further comprising: respectively comparing the first point cloud height information with a preset height information range; and taking the first point cloud height information falling into the preset height information range as second point cloud height information.
Optionally, identifying the individual information of the target crop according to the image data and the second point cloud height information includes: and inputting the image data and the second point cloud height information into a preset deep learning model for detection to obtain the position information and the individual size information of each target crop, wherein the individual size information is used for representing the outline size when the target crop is overlooked.
Optionally, the image data includes a two-dimensional RGB image.
Optionally, after identifying the individual information of the target crop, the method further comprises: determining an operation route of operation according to the position information of the target crop; determining the dosage of the medicine sprayed on the target crops according to the individual size information of the target crops; and performing plant protection operation on the target crops according to the operation route and the dosage of the sprayed pesticide.
Optionally, the method further includes: and determining the position information of the target crop in a three-dimensional coordinate system corresponding to the digital earth surface model data according to the second point cloud height information of the target crop.
According to another aspect of the embodiments of the present application, there is also provided a method of controlling a work apparatus, including: acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; identifying individual information of the target crop according to the image data and the second point cloud height information; and controlling the operation equipment to perform plant protection operation on the target crops according to the individual information of the target crops.
According to another aspect of the embodiments of the present application, there is also provided an identification apparatus for crops, including: the acquisition module is used for acquiring image data of a plant protection area and digital earth surface model data; the first determining module is used for determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of a point cloud in the plant protection area; the second determining module is used for determining second point cloud height information of the target crop according to the first point cloud height information; and the identification module is used for identifying the individual information of the target crop according to the image data and the second point cloud height information.
According to another aspect of the embodiments of the present application, there is also provided a plant protection system, including: the surveying and mapping equipment is used for acquiring image data and digital earth surface model data of a plant protection area and sending the image data and the digital earth surface model data to the server; the server is used for determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of a point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; identifying individual information of the target crop according to the image data and the second point cloud height information; and the operation equipment is communicated with the server and is used for performing plant protection operation on the target crops.
According to another aspect of the embodiments of the present application, there is also provided a storage medium including a stored program, where the program is run to control a device on which the storage medium is located to execute the above crop identification method.
According to another aspect of the embodiments of the present application, there is also provided a processor for executing a program, where the program executes the above method for identifying crops.
In the embodiment of the application, image data and digital earth surface model data of a plant protection area are acquired; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; according to the method for identifying the individual information of the target crops according to the image data and the second point cloud height information, the height information of the target crops in the plant protection area is determined by utilizing the digital earth surface model data of the plant protection area, then the individual information of each crop in the plant protection area is accurately identified by combining the two-dimensional RGB image data of the plant protection area, so that the distribution information of each fruit tree in the plant protection area is accurately mapped, the automation degree of orchard plant protection operation is improved, the technical effect of reducing the complexity degree of orchard plant protection operation is reduced, and the technical problem that the distribution range of the fruit trees is difficult to accurately identify each fruit tree due to the fact that the fruit trees are intersected with each other in the current stage is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic diagram of an RGB image of a fruit tree according to an embodiment of the present application;
FIG. 2 is a schematic diagram of fruit tree distribution obtained by detecting fruit trees according to RGB images;
FIG. 3 is a flow chart of a method of identifying a crop according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a two-dimensional visualization of digital earth surface model data of a fruit tree according to an embodiment of the present application;
fig. 5 is a flowchart of a control method of a work apparatus according to an embodiment of the present application;
fig. 6 is a structural view of an identification device for crops according to an embodiment of the present application;
fig. 7 is a block diagram of a plant protection system according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present application, there is provided an embodiment of a method for controlling a work apparatus, it should be noted that the steps illustrated in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be executed in an order different from that herein.
Fig. 3 is a flowchart of a crop identification method according to an embodiment of the present application, as shown in fig. 3, the method including the steps of:
step S302, image data of a plant protection area and digital earth surface model data are obtained.
According to an alternative embodiment of the application, the image data comprises a two-dimensional RGB image. The RGB color scheme is a color standard in the industry, and various colors are obtained by changing three color channels of red, green and blue and superimposing them on each other.
In an optional embodiment of the present application, the RGB images of the plant protection area may be captured by a high-definition camera installed on the surveying and mapping drone.
The digital earth surface model is a ground elevation model comprising the heights of earth surface buildings, bridges, trees and the like. The method is used for representing the most real ground fluctuation situation, can be widely applied to various industries, such as forest regions, and can be used for detecting the growth situation of forests.
Step S304, determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area.
And S306, determining second point cloud height information of the target crop according to the first point cloud height information.
The acquired digital surface model data includes height information of a plurality of crops, and the height information of different crops is different, so that the digital surface model data of the plant protection area needs to be acquired to determine the height information of the target crop in the plant protection area. It should be noted that the target crop mentioned herein refers to a fruit tree.
In an alternative embodiment of the present application, taking an orchard as an example, fruit trees in the orchard are intersected with each other, and each fruit tree cannot be accurately identified only by using a two-dimensional RGB image, so that the height of each fruit tree needs to be determined by using digital surface model data of the orchard, and then the fruit trees are distinguished by using the height of the fruit trees.
And S308, identifying the individual information of the target crop according to the image data and the second point cloud height information.
As mentioned above, since the fruit trees in the orchard are intersected with each other, each fruit tree cannot be accurately identified only by using the two-dimensional RGB image, but after the height of each fruit tree is determined by using the digital surface model data of the orchard, the information of each fruit tree in the orchard can be accurately identified by combining the two-dimensional RGB image of the fruit tree.
Fig. 4 is a schematic diagram of two-dimensional visualization of digital surface model data of a fruit tree according to an embodiment of the present application, and as shown in fig. 4, the digital surface model data of the fruit tree is displayed in a two-dimensional visualization manner, so that fruit trees that are difficult to distinguish on two-dimensional RGB are easily distinguished after being mapped to height information, and branch information of each fruit tree can be obtained.
Through the steps, the height information of the target crops in the plant protection area is determined by utilizing the digital earth surface model data of the plant protection area, and then the individual information of each target crop in the plant protection area is accurately identified by combining the two-dimensional RGB image data of the plant protection area, so that the distribution information of each fruit tree in the plant protection area is accurately mapped, the automation degree of orchard plant protection operation is improved, and the technical effect of the complexity degree of orchard plant protection operation is reduced.
In an alternative embodiment of the present application, step S306 may be implemented by: taking the area in which the height value of the point cloud corresponding to the first point cloud height information gradually decreases from the middle to the periphery as the area in which the target crop is located; and taking the first point cloud height information corresponding to the area where the target crop is located as second point cloud height information.
The crown of the fruit tree is generally high in the middle and low in the surrounding area, so that when the fruit tree is identified, the area in which the height value of the point cloud corresponding to the point cloud height information is gradually reduced from the middle to the periphery is used as a planting area of the fruit tree, and the point cloud height information corresponding to the area is also the point cloud height information of the fruit tree, namely the second point cloud height information mentioned above.
In an optional embodiment of the present application, step S306 may also be implemented by the following method: respectively comparing the first point cloud height information with a preset height information range; and taking the first point cloud height information falling into the preset height information range as second point cloud height information.
Various crops may be distributed in the plant protection area, and the heights of the different crops are different, for example, the distribution range of fruit trees in the plant protection area needs to be surveyed, the height information of the various crops is acquired through digital earth surface model data of an orchard, and if the height information of the fruit trees is acquired, the acquired height information of the various crops needs to be further compared with the height range of the fruit trees prestored in a database, so that the height information of the fruit trees needing to be surveyed is determined.
In an alternative embodiment of the present application, step S308 can be implemented by the following method: and inputting the image data and the second height information into a preset deep learning model for detection to obtain the position information and the individual size information of each target crop, wherein the individual size information is used for representing the outline size of the overlooking target crop.
According to an optional embodiment of the application, after the height information of the fruit tree is obtained, the height information of the fruit tree and the RGB image of the fruit tree are used as depth channels and RGB channels which are used as input of a machine learning model, and the input is input into the machine learning model trained in advance for segmentation and detection. And obtaining the position information and the individual size information of each fruit tree. The individual size information here refers to the size of the crown outline in a plan view of the fruit tree. By the method, the robustness and the accuracy of the machine learning model can be greatly improved.
In an alternative embodiment of the present application, before identifying the location information and the individual size information of the target crop by using the machine learning model, a training data set is acquired, wherein the training data set comprises: image data of a plant protection area, point cloud height information of a target crop, position information of the target crop and individual size information of the target crop; and generating the trained machine learning model based on the training data set.
In another alternative embodiment of the present application, after step S308 is executed, the operation route of the operation is further determined according to the position information of the target crop; determining the dosage of the medicine sprayed on the target crops according to the individual size information of the target crops; and performing plant protection operation on the target crops according to the operation route and the dosage of the sprayed pesticide. The route of the plant protection unmanned aerial vehicle can be formulated according to the distribution information of the fruit trees; the dosage of the pesticide is sprayed when the plant protection operation is carried out on the fruit tree is determined according to the size of the crown of the fruit tree.
By the method, the position distribution information of the fruit trees is utilized to set the route of the plant protection operation in advance, and the dosage of the pesticide sprayed on the fruit trees during the plant protection operation is determined according to the individual size of the fruit trees, so that the efficiency of the plant protection operation can be improved, and the resources can be saved.
In some optional embodiments of the present application, the method for identifying crops further includes determining position information of the target crop in a three-dimensional coordinate system corresponding to the digital surface model data according to the second point cloud height information of the target crop.
It was mentioned above that the position subsection information and the individual size information of the crop are determined using the digital terrain model data of the plant protection area in combination with the RGB image data of the plant protection area. Or after the height information of the crops is determined by directly utilizing the digital earth surface model data of the plant protection area, the crops are identified in the three-dimensional space corresponding to the digital earth surface model data of the plant protection area.
By the method, after the surveying and mapping unmanned aerial vehicle shoots the high-definition images, the positions and the individual sizes of the fruit trees are directly detected according to the high-definition images and the digital earth surface model data, and then the high-definition images and the digital earth surface model data are directly used for plant protection operation, so that the automation degree of the plant protection operation can be improved, and the complexity of orchard operation is reduced.
Fig. 5 is a flowchart of a method for controlling a work apparatus according to an embodiment of the present application, and as shown in fig. 5, the method includes the steps of:
step S502, acquiring image data of a plant protection area and digital earth surface model data.
Step S504, determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area.
And S506, determining second point cloud height information of the target crop according to the first point cloud height information.
And step S508, identifying the individual information of the target crop according to the image data and the second point cloud height information.
According to an alternative embodiment of the present application, the identification of the individual information of the target crop in step S508 refers to identification of the position information and the individual size information of the target crop.
Step S510, controlling the operation device to perform plant protection operation on the target crop according to the individual information of the target crop.
Optionally, after the individual information of the target crop is identified, determining a working route of the work according to the position information of the target crop; and determining the dosage of the medicine sprayed on the target crops according to the individual size information of the target crops. And the operation equipment performs plant protection operation on the target crops according to the determined operation route and the dosage of the sprayed medicine.
It should be noted that reference may be made to the description related to the embodiment shown in fig. 3 for a preferred implementation of the embodiment shown in fig. 5, and details are not repeated here.
Fig. 6 is a block diagram of a crop recognition apparatus according to an embodiment of the present application, as shown in fig. 6, the apparatus including:
and an obtaining module 60, configured to obtain image data of the plant protection area and digital earth surface model data.
According to an alternative embodiment of the application, the image data comprises a two-dimensional RGB image. The RGB color scheme is a color standard in the industry, and various colors are obtained by changing three color channels of red, green and blue and superimposing them on each other.
In an optional embodiment of the present application, the RGB images of the plant protection area may be captured by a high-definition camera installed on the surveying and mapping drone.
A Digital Surface Model (Digital Surface Model) is a ground elevation Model including the heights of Surface buildings, bridges, trees, and the like. The digital earth model represents the most real ground fluctuation situation, and can be widely applied to various industries, such as forest regions, and can be used for detecting the growth situation of forests.
And the first determining module 62 is configured to determine first point cloud height information in the plant protection area according to the digital surface model data, where the first point cloud height information includes a height value of a point cloud in the plant protection area.
And a second determining module 64, configured to determine second point cloud height information of the target crop according to the first point cloud height information.
The acquired digital surface model data includes height information of a plurality of crops, and the height information of different crops is different, so that the digital surface model data of the plant protection area needs to be acquired to determine the height information of the target crop in the plant protection area. It should be noted that the target crop mentioned herein refers to a fruit tree.
And the identification module 66 is used for identifying the individual information of the target crop according to the image data and the second point cloud height information.
Through the device, height information of target crops in the plant protection area is determined through digital earth surface model data of the plant protection area, then the individual information of each target crop in the plant protection area is accurately identified by combining two-dimensional RGB image data of the plant protection area, so that distribution information of each fruit tree in the plant protection area is accurately mapped, the automation degree of orchard plant protection operation is improved, and the technical effect of the complexity of orchard plant protection operation is reduced.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 3 for a preferred implementation of the embodiment shown in fig. 6, and details are not described here again.
Fig. 7 is a block diagram of a plant protection system according to an embodiment of the present application, as shown in fig. 6, the system comprising: a mapping device 70, a server 72, and a work device 74, wherein,
the surveying and mapping device 70 is configured to collect image data and digital earth surface model data of a plant protection area, and send the image data and the digital earth surface model M data to the server 72;
optionally, the surveying equipment may be a surveying and mapping unmanned aerial vehicle, and the high-definition images of the plant protection area are acquired by installing a high-definition camera on the surveying and mapping unmanned aerial vehicle, so as to obtain two-dimensional RGB images of the plant protection area. Through installing three-dimensional imager on survey and drawing unmanned aerial vehicle, acquire the regional digital earth's surface model data of plant protection. Be provided with communication module on the survey and drawing unmanned aerial vehicle, image data and the GSM data transmission who will gather send server 72.
The server 72 is used for determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of a point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; and identifying the individual information of the target crop according to the image data and the second point cloud height information.
And a working device 74, in communication with the server 72, for performing plant protection work on the target crop.
According to an alternative embodiment of the present application, the server 72 determines the operation route of the operation according to the position information of the target crop after identifying the individual information of the target crop; and determining the dosage of the medicine sprayed on the target crops according to the individual size information of the target crops. The working equipment 74 performs plant protection work on the target crop according to the working route and the dose of the sprayed pesticide.
Alternatively, work equipment 74 includes, but is not limited to, unmanned equipment such as plant protection drones.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 3 for a preferred implementation of the embodiment shown in fig. 7, and details are not described here again.
The embodiment of the application also provides a storage medium which comprises a stored program, wherein when the program runs, the device where the storage medium is located is controlled to execute the above crop identification method or the control method of the operation device.
The storage medium stores a program for executing the following functions: acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; and identifying the individual information of the target crop according to the image data and the second point cloud height information. Or
Acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; identifying individual information of the target crop according to the image data and the second point cloud height information; and controlling the operation equipment to perform plant protection operation on the target crops according to the individual information of the target crops.
The embodiment of the application also provides a processor which is used for running the program, wherein the program executes the identification method of the crops or the control method of the working equipment when running.
The processor is used for running a program for executing the following functions: acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; and identifying the individual information of the target crop according to the image data and the second point cloud height information. Or
Acquiring image data and digital earth surface model data of a plant protection area; determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; identifying individual information of the target crop according to the image data and the second point cloud height information; and controlling the operation equipment to perform plant protection operation on the target crops according to the individual information of the target crops.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (12)
1. A method of identifying a crop, comprising:
acquiring image data and digital earth surface model data of a plant protection area;
determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area;
determining second point cloud height information of the target crop according to the first point cloud height information;
and identifying the individual information of the target crop according to the image data and the second point cloud height information.
2. The method of claim 1, wherein determining second point cloud height information for a target crop from the first point cloud height information comprises:
taking the area in which the height value of the point cloud corresponding to the first point cloud height information gradually decreases from the middle to the periphery as the area where the target crop is located;
and taking the first point cloud height information corresponding to the area where the target crop is located as the second point cloud height information.
3. The method of claim 1, wherein determining second point cloud height information for a target crop from the first point cloud height information further comprises:
comparing the first point cloud height information with a preset height information range respectively;
and taking the first point cloud height information falling into the preset height information range as the second point cloud height information.
4. The method of claim 2 or 3, wherein identifying individual information of the target crop from the image data and the second point cloud height information comprises:
inputting the image data and the second point cloud height information into a preset deep learning model for detection to obtain position information and individual size information of each target crop, wherein the individual size information is used for representing the outline size of the target crop when overlooked.
5. The method of claim 1, wherein the image data comprises a two-dimensional RGB image.
6. The method of claim 4, wherein after identifying the individual information of the target crop, the method further comprises:
determining an operation route of operation according to the position information of the target crop;
determining the dosage of the medicine sprayed on the target crops according to the individual size information of the target crops;
and performing plant protection operation on the target crops according to the operation route and the dosage of the sprayed medicine.
7. The method of claim 1, further comprising:
and determining the position information of the target crop in a three-dimensional coordinate system corresponding to the digital earth surface model data according to the second point cloud height information of the target crop.
8. A method for controlling a work apparatus, comprising:
acquiring image data and digital earth surface model data of a plant protection area;
determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area;
determining second point cloud height information of the target crop according to the first point cloud height information;
identifying individual information of the target crop according to the image data and the second point cloud height information;
and controlling operation equipment to perform plant protection operation on the target crops according to the individual information of the target crops.
9. An apparatus for identifying a crop, comprising:
the acquisition module is used for acquiring image data of a plant protection area and digital earth surface model data;
the first determination module is used for determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of a point cloud in the plant protection area;
the second determining module is used for determining second point cloud height information of the target crop according to the first point cloud height information;
and the identification module is used for identifying the individual information of the target crop according to the image data and the second point cloud height information.
10. A plant protection system, comprising:
the surveying and mapping equipment is used for acquiring image data and digital earth surface model data of a plant protection area and sending the image data and the digital earth surface model data to a server;
the server is used for determining first point cloud height information in the plant protection area according to the digital earth surface model data, wherein the first point cloud height information comprises a height value of point cloud in the plant protection area; determining second point cloud height information of the target crop according to the first point cloud height information; identifying individual information of the target crop according to the image data and the second point cloud height information;
and the operation equipment is communicated with the server and is used for performing plant protection operation on the target crops.
11. A storage medium comprising a stored program, wherein the program is operable to control a device on which the storage medium is located to perform the method of identifying a crop of any one of claims 1 to 7.
12. A processor for executing a program, wherein the program is executed to execute the crop identification method according to any one of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911236923.6A CN112926359A (en) | 2019-12-05 | 2019-12-05 | Crop identification method and device, and control method of operation equipment |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911236923.6A CN112926359A (en) | 2019-12-05 | 2019-12-05 | Crop identification method and device, and control method of operation equipment |
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| CN112926359A true CN112926359A (en) | 2021-06-08 |
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| CN201911236923.6A Pending CN112926359A (en) | 2019-12-05 | 2019-12-05 | Crop identification method and device, and control method of operation equipment |
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