CN117036401A - Distribution network line inspection method and system based on target tracking - Google Patents
Distribution network line inspection method and system based on target tracking Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims abstract description 105
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- 238000002372 labelling Methods 0.000 claims abstract description 12
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
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- G06V2201/07—Target detection
Abstract
The application discloses a distribution network line inspection method and system based on target tracking, wherein the method comprises the following steps: acquiring first equipment visual field information; obtaining a target inspection area and a first acquisition image set corresponding to the target inspection area based on the first equipment visual field information; labeling a target object on a certain first acquired image to obtain a certain first preliminary detection frame; if the size of a certain first preliminary detection frame is smaller than a preset threshold value, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame; determining the centroid position of a target object in a certain first acquired image according to a preset centroid tracking algorithm and a target detection frame to obtain centroid coordinates; and adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates. The problem that automatic focusing and posture adjustment are difficult to realize after the position and the shooting angle of the unmanned aerial vehicle are changed in the prior art can be solved.
Description
Technical Field
The application belongs to the technical field of power distribution network line inspection, and particularly relates to a power distribution network line inspection method and system based on target tracking.
Background
Unmanned aerial vehicle plays an important role in the automatic inspection of distribution network circuit, to every target inspection point, can all take many photos and return to control operation platform, but to same target inspection point, unmanned aerial vehicle need adjust different angles, even distance to obtain diversified image, fault or other circumstances on the target line that just can be accurate reflection.
In the current unmanned aerial vehicle inspection process, in order to ensure that the unmanned aerial vehicle can acquire accurately cleaned distribution network line images each time, a fixed-distance shooting mode is generally adopted, so that pose variation of the unmanned aerial vehicle is reduced, focusing is facilitated, and clear images are acquired; however, in the actual working process, if the unmanned aerial vehicle needs to change the pose greatly, the shooting angle is adjusted, no better mechanism exists, and the requirements of automatic adjustment of the pose and focusing of the unmanned aerial vehicle can be met.
Disclosure of Invention
The application provides a distribution network line inspection method and system based on target tracking, which are used for solving the technical problem that automatic focusing and posture adjustment are difficult to realize after the position and the shooting angle of an unmanned aerial vehicle are changed in the prior art.
In a first aspect, the present application provides a method for inspecting a distribution network line based on target tracking, including:
monitoring a power grid line in real time through a patrol equipment to acquire first equipment visual field information of the patrol equipment;
obtaining a target inspection area based on the first equipment visual field information, and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
labeling a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judging whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
if the size of a certain first preliminary detection frame is smaller than a preset threshold value, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
determining the centroid position of a target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates to finish accurate focusing shooting.
In a second aspect, the present application provides a distribution network line inspection system based on target tracking, including:
the system comprises an acquisition module, a first monitoring module and a second monitoring module, wherein the acquisition module is configured to monitor a power grid line in real time through a patrol equipment and acquire first equipment visual field information of the patrol equipment;
the acquisition module is configured to obtain a target inspection area based on the first equipment visual field information and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
the judging module is configured to label a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judge whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
the merging module is configured to acquire a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image if the size of the certain first preliminary detection frame is smaller than a preset threshold value, and merge the first preliminary detection frame and the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
the determining module is configured to determine the centroid position of the target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and the adjusting module is configured to adjust the pose of the unmanned aerial vehicle according to the barycenter coordinates so as to finish accurate focusing shooting.
In a third aspect, there is provided an electronic device, comprising: the system comprises at least one processor and a memory communicatively connected with the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the target tracking-based distribution network line inspection method of any of the embodiments of the present application.
In a fourth aspect, the present application further provides a computer readable storage medium, on which a computer program is stored, where the program instructions, when executed by a processor, cause the processor to execute the steps of the distribution network line inspection method based on object tracking according to any of the embodiments of the present application.
According to the distribution network line inspection method and system based on target tracking, the target detector obtained through training is used for carrying out target positioning on the obtained current image, the target detection frame can be used for determining the approximate position of the target object, the preset centroid tracking algorithm can be used for determining the accurate position of the target object, the pose of the unmanned aerial vehicle is adjusted based on the change of the centroid coordinates, and then the target object is focused, so that a clear target image can be obtained, and the technical problem that automatic focusing and pose adjustment are difficult to achieve after the pose and shooting angle of the unmanned aerial vehicle are changed in the prior art can be solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a distribution network line inspection method based on target tracking according to an embodiment of the present application;
fig. 2 is a block diagram of a distribution network line inspection system based on object tracking according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, a flowchart of a distribution network line inspection method based on target tracking according to the present application is shown.
As shown in fig. 1, the distribution network line inspection method based on target tracking specifically includes the following steps:
step S101, monitoring a power grid line in real time through an inspection device, and acquiring first device visual field information of the inspection device.
In the step, the power grid line is monitored in real time through the inspection equipment, and first equipment visual field information of the inspection equipment is obtained, wherein the inspection equipment comprises an intelligent acquisition module, an image processing module, an image storage module, a data terminal module and the like. The intelligent acquisition module comprises an image pickup device, a user can monitor the power grid circuit in real time based on the target view of the image pickup device, and can acquire first device view information shot by the image pickup device through monitoring, namely, the user can observe an image scene of the power grid circuit in a lens of the image pickup device in real time.
Step S102, a target inspection area and a first collection image set corresponding to the target inspection area are obtained based on the first equipment visual field information, wherein the first collection image set comprises at least one first collection image.
In the step, the inspection area needing image acquisition can be selected through monitoring, after a user selects a target inspection area, the intelligent acquisition module can be controlled to take a picture to obtain a first acquired image, and the first acquired image is not processed and still needs to be further optimized so as to meet the image quality requirement of inspection.
It should be noted that, according to the first device visual field information and the first collected image, the second collected image is obtained, by comparing the first device visual field information and the first collected image, whether the collected first collected image meets the imaging quality requirement, for example, whether the first collected image is located in the middle of an imaging visual field specified by a user, whether the content of the image main body meets the image duty ratio and the like is judged, if the conditions are met, the first collected image is specified to meet the preset visual field and duty ratio requirement, and at this time, the position of the image capturing device of the intelligent collection module does not need to be moved again, and the first collected image can be directly processed to obtain the target collected image.
If the acquired first acquired image does not meet the imaging quality requirement, acquiring a plurality of first coordinates corresponding to the first acquired image and target position information corresponding to the target inspection area; calculating the coordinate offset of the first acquired image and the first equipment visual field information according to the target position information and the first coordinates; adjusting the visual field position of the inspection equipment according to the coordinate offset to acquire visual field information of second equipment of the inspection equipment; based on the second equipment visual field information, a second acquisition image set corresponding to the target inspection area is acquired again, wherein the second acquisition image set comprises at least one second acquisition image.
Step S103, labeling a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judging whether the size of the certain first preliminary detection frame is smaller than a preset threshold value.
In this step, the target object in a certain first acquired image may be framed based on a preset target detector, so as to track the position of the target object. And (3) carrying out coordinate labeling on the framed target object, and further obtaining the contour of the specific target object. The size of a certain first preliminary detection frame can be calculated through the coordinate information of the target object, and the size is compared with a preset threshold value, so that whether the target object in the certain first preliminary detection frame is complete or not can be analyzed.
Step S104, if the size of the certain first preliminary detection frame is smaller than a preset threshold, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates.
In this step, the size of a certain first preliminary detection frame may be calculated according to the coordinate information of the target object, and the size may be compared with a preset threshold value, so as to analyze whether the target object in the certain first preliminary detection frame is complete.
It should be noted that, if the target object in a certain first preliminary detection frame is incomplete, the size of the certain first preliminary detection frame is smaller than a preset threshold, at this time, a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image is acquired, and a certain first preliminary detection frame of the first preliminary detection frame can be fused based on the features, so as to realize the combination of the detection frames, thereby obtaining the target detection frame.
In one embodiment, if the size of a certain first preliminary detection frame is not smaller than a preset threshold, the certain first preliminary detection frame is directly defined as the target detection frame.
Step S105, determining the centroid position of the target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame, and obtaining centroid coordinates.
In the step, calculating a first centroid position of a target object in a current inspection image according to a target detection frame;
acquiring a second centroid position of a target object in the current inspection image based on a preset centroid tracking algorithm;
calculating a euclidean distance between the first centroid position and the second centroid position;
and selecting a second centroid position corresponding to the minimum Euclidean distance as an updated centroid position to obtain centroid coordinates.
The preset centroid tracking algorithm can process the boundary frame and the key point coordinates of each target object in each frame of image, so that the centroid position of each target object can be calculated, further, the distance analysis is carried out on the centroid position determined by the target detection frame, the closest centroid position is regarded as the execution of the same target object, and the second execution position is adopted as the updated centroid position, so that the method is more accurate and reliable.
And S106, adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates, and completing the accurate focusing shooting.
In the step, after the accurate object is positioned, the pose of the unmanned aerial vehicle can be adjusted according to the positioning data, and even if the angle or the position of the unmanned aerial vehicle is changed greatly, the target object is lost, the target object on the distribution line can be accurately shot through accurate target tracking and unmanned aerial vehicle pose adjustment.
Specifically, constructing a position association relation based on a plurality of centroid coordinates to obtain a plurality of association labeling data; and adjusting the pose of the unmanned aerial vehicle according to the plurality of associated labeling data to finish accurate focusing shooting.
In summary, the method of the application carries out target positioning on the acquired current image through the target detector obtained by training, the target detection frame can determine the approximate position of the target object, the preset centroid tracking algorithm can determine the accurate position of the target object, the pose of the unmanned aerial vehicle is adjusted based on the change of the centroid coordinates, and then the target object is focused, so that a clear target image can be acquired, and the technical problem that the automatic focusing and the pose adjustment are difficult to realize after the pose and the shooting angle of the unmanned aerial vehicle are changed in the prior art can be solved.
Referring to fig. 2, a block diagram of a distribution network line inspection system based on target tracking according to the present application is shown.
As shown in fig. 2, the distribution network line inspection system 200 includes an acquisition module 210, an acquisition module 220, a judgment module 230, a combination module 240, a determination module 250, and an adjustment module 260.
The acquiring module 210 is configured to monitor the power grid line in real time through the inspection device, and acquire first device visual field information of the inspection device; the acquisition module 220 is configured to obtain a target inspection area based on the first device visual field information, and a first acquired image set corresponding to the target inspection area, where the first acquired image set includes at least one first acquired image; the judging module 230 is configured to label a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judge whether the size of the certain first preliminary detection frame is smaller than a preset threshold; the merging module 240 is configured to obtain a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image if the size of the certain first preliminary detection frame is smaller than a preset threshold, and merge the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, where the target detection frame includes key point coordinates; the determining module 250 is configured to determine a centroid position of the target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame, so as to obtain a centroid coordinate; and the adjusting module 260 is configured to adjust the pose of the unmanned aerial vehicle according to the barycenter coordinates, so as to complete the accurate focusing shooting.
It should be understood that the modules depicted in fig. 2 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations and features described above for the method and the corresponding technical effects are equally applicable to the modules in fig. 2, and are not described here again.
In other embodiments, the present application further provides a computer readable storage medium, on which a computer program is stored, where the program instructions, when executed by a processor, cause the processor to perform the method for inspecting a distribution network line based on object tracking in any of the above method embodiments;
as one embodiment, the computer-readable storage medium of the present application stores computer-executable instructions configured to:
monitoring a power grid line in real time through a patrol equipment to acquire first equipment visual field information of the patrol equipment;
obtaining a target inspection area based on the first equipment visual field information, and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
labeling a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judging whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
if the size of a certain first preliminary detection frame is smaller than a preset threshold value, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
determining the centroid position of a target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates to finish accurate focusing shooting.
The computer readable storage medium may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created from use of the target tracking based distribution network line inspection system, and the like. In addition, the computer-readable storage medium may include high-speed random access memory, and may also include memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer readable storage medium optionally includes memory remotely located with respect to the processor, the remote memory being connectable over a network to the target tracking based distribution network line inspection system. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in fig. 3, where the device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, memory 320, input device 330, and output device 340 may be connected by a bus or other means, for example in fig. 3. Memory 320 is the computer-readable storage medium described above. The processor 310 executes various functional applications of the server and data processing by running non-volatile software programs, instructions and modules stored in the memory 320, i.e. implements the method for inspecting distribution network lines based on object tracking in the above method embodiment. The input device 330 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the target tracking based distribution network line inspection system. The output device 340 may include a display device such as a display screen.
The electronic equipment can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. Technical details not described in detail in this embodiment may be found in the methods provided in the embodiments of the present application.
As an implementation manner, the electronic device is applied to a distribution network line inspection system based on target tracking, and is used for a client, and includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to:
monitoring a power grid line in real time through a patrol equipment to acquire first equipment visual field information of the patrol equipment;
obtaining a target inspection area based on the first equipment visual field information, and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
labeling a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judging whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
if the size of a certain first preliminary detection frame is smaller than a preset threshold value, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
determining the centroid position of a target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates to finish accurate focusing shooting.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product, which may be stored in a computer-readable storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the various embodiments or methods of some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (8)
1. The utility model provides a distribution network line inspection method based on target tracking, which is characterized by comprising the following steps:
monitoring a power grid line in real time through a patrol equipment to acquire first equipment visual field information of the patrol equipment;
obtaining a target inspection area based on the first equipment visual field information, and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
labeling a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judging whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
if the size of a certain first preliminary detection frame is smaller than a preset threshold value, acquiring a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image, and combining the first preliminary detection frame with the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
determining the centroid position of a target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and adjusting the pose of the unmanned aerial vehicle according to the barycenter coordinates to finish accurate focusing shooting.
2. The method for inspecting a distribution network line based on target tracking according to claim 1, wherein after obtaining a target inspection area based on the first device visual field information and a first collected image set corresponding to the target inspection area, the method further comprises:
acquiring a plurality of first coordinates corresponding to the first acquired image and target position information corresponding to the target inspection area;
calculating coordinate offset of the first acquired image and the first device visual field information according to the target position information and the first coordinates;
adjusting the visual field position of the inspection equipment according to the coordinate offset to acquire second equipment visual field information of the inspection equipment;
based on the second equipment visual field information, re-acquiring a second acquired image set corresponding to the target inspection area, wherein the second acquired image set comprises at least one second acquired image;
and labeling a target object on a certain second acquired image based on a preset target detector to obtain a certain second preliminary detection frame, and judging whether the size of the certain second preliminary detection frame is smaller than a preset threshold value.
3. The method for inspecting a distribution network line based on object tracking according to claim 1, wherein after determining whether the size of the certain first preliminary detection frame is smaller than a preset threshold, the method further comprises:
if the size of the certain first preliminary detection frame is not smaller than the preset threshold value, the certain first preliminary detection frame is directly defined as a target detection frame.
4. The method for inspecting a distribution network line based on target tracking according to claim 1, wherein determining the centroid position of the target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame, and obtaining the centroid coordinates comprises:
calculating a first centroid position of a target object in the certain first acquired image according to the target detection frame;
acquiring a second centroid position of the target object in the certain first acquired image based on a preset centroid tracking algorithm;
calculating a euclidean distance between the first centroid position and the second centroid position;
and selecting a second centroid position corresponding to the minimum Euclidean distance as an updated centroid position to obtain centroid coordinates.
5. The method for inspecting a distribution network line based on target tracking according to claim 1, wherein the adjusting the pose of the unmanned aerial vehicle according to the centroid coordinates, the completing the accurate focusing shooting comprises:
constructing a position association relation based on a plurality of centroid coordinates to obtain a plurality of association labeling data;
and adjusting the pose of the unmanned aerial vehicle according to the plurality of associated labeling data to finish accurate focusing shooting.
6. The utility model provides a join in marriage net twine way inspection system based on target tracking which characterized in that includes:
the system comprises an acquisition module, a first monitoring module and a second monitoring module, wherein the acquisition module is configured to monitor a power grid line in real time through a patrol equipment and acquire first equipment visual field information of the patrol equipment;
the acquisition module is configured to obtain a target inspection area based on the first equipment visual field information and a first acquisition image set corresponding to the target inspection area, wherein the first acquisition image set comprises at least one first acquisition image;
the judging module is configured to label a target object on a certain first acquired image based on a preset target detector to obtain a certain first preliminary detection frame, and judge whether the size of the certain first preliminary detection frame is smaller than a preset threshold value;
the merging module is configured to acquire a first preliminary detection frame in at least one first acquired image adjacent to the certain first acquired image if the size of the certain first preliminary detection frame is smaller than a preset threshold value, and merge the first preliminary detection frame and the certain first preliminary detection frame to obtain a target detection frame, wherein the target detection frame comprises key point coordinates;
the determining module is configured to determine the centroid position of the target object in the certain first acquired image according to a preset centroid tracking algorithm and the target detection frame to obtain centroid coordinates;
and the adjusting module is configured to adjust the pose of the unmanned aerial vehicle according to the barycenter coordinates so as to finish accurate focusing shooting.
7. An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 5.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method of any one of claims 1 to 5.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117237978A (en) * | 2023-11-16 | 2023-12-15 | 江西少科智能建造科技有限公司 | CAD drawing electrical bridge information extraction method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117237978A (en) * | 2023-11-16 | 2023-12-15 | 江西少科智能建造科技有限公司 | CAD drawing electrical bridge information extraction method and system |
| CN117237978B (en) * | 2023-11-16 | 2024-03-08 | 江西少科智能建造科技有限公司 | CAD drawing electrical bridge information extraction method and system |
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