CN110430389B - Image data acquisition method and device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to an image data acquisition method, an image data acquisition device, computer equipment and a storage medium. The method comprises the following steps: acquiring video information uploaded by an unmanned aerial vehicle; extracting an original image frame of which the video information contains a preset acquisition target; identifying a defective image frame contained in the original image frame; intercepting a video clip containing the defect image frame in the video information; and uploading the defect image frame and the video clip. According to the image data acquisition method, the image data are acquired through the unmanned aerial vehicle, the target defect image frame in the data acquired by the unmanned aerial vehicle is identified, the defect image frame and the video clip containing the defect image frame are directly uploaded, the data volume of data transmission is effectively reduced, and the data volume of the image data in the transmission process is obviously reduced.
Description
Technical Field
The application relates to the technical field of computers, in particular to an image data acquisition method and device based on an unmanned aerial vehicle, computer equipment and a storage medium.
Background
The unmanned plane is called unmanned plane for short, and is an unmanned aerial vehicle operated by radio remote control equipment and a self-contained program control device. Unmanned aerial vehicles are in fact a general term for unmanned aerial vehicles, and can be defined from a technical perspective as follows: unmanned fixed wing aircraft, unmanned VTOL aircraft, unmanned airship, unmanned helicopter, unmanned multi-rotor aircraft, unmanned paravane, etc. At present, unmanned aerial vehicles are widely applied in the fields of field construction, exploration, transportation, tourism, rescue and the like.
Because unmanned aerial vehicle does not receive the topography restriction and can carry on various camera equipment, be used for carrying on closely shooting to the scene of fault location or the rare place of people and observe. Unmanned aerial vehicle can feed back the video image data of shooing to, supply relevant personnel to carry out the analysis to the scene. However, the data amount of the video image data is too large, and the complexity of the acquisition and transmission process is high.
Disclosure of Invention
Based on this, it is necessary to provide an image data acquisition method and apparatus, a computer device, and a storage medium based on an unmanned aerial vehicle, aiming at the technical problem that the data volume of the existing unmanned aerial vehicle in the process of acquiring and transmitting video image data is too large.
A method of image data acquisition, the method comprising:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information contains a preset acquisition target;
identifying a defective image frame contained in the original image frame;
intercepting a video clip containing the defect image frame in the video information;
and uploading the defect image frame and the video clip.
In one embodiment, before controlling the unmanned aerial vehicle to fly according to a preset flight route and receiving and storing video information acquired by the unmanned aerial vehicle in the flight route, the method further includes:
acquiring coordinate information of each preset acquisition target;
determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target;
acquiring obstacle information of the flight area information in real time;
and planning the flight route of the unmanned aerial vehicle according to the obstacle information, and generating and pushing a preset flight route to the unmanned aerial vehicle.
In one embodiment, the uploading the defect image further comprises:
dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size;
dividing each pixel region into a plurality of sub-pixel regions of the same size;
compressing each sub-pixel region at a preset compression ratio to form a corresponding data block;
arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block;
arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip;
the uploading the defect image frame and the video clip comprises:
and uploading the compressed defect image frame and the video clip.
In one embodiment, the extracting the original image frames of which the video information contains the preset acquisition target includes:
determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle;
searching the video information in the flight time period in the video information;
and extracting an image frame in the video information in the flight time period as an original image frame.
In one embodiment, the identifying the defective image frame included in the original image frame includes:
acquiring images of all angles of the preset acquisition target;
determining real-time original image frames corresponding to the angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at each shooting moment;
acquiring the similarity between the angle image of the preset acquisition target and the corresponding real-time original image frame;
and when the similarity is lower than a preset similarity threshold value, judging the original image frame to be a defect image frame.
In one embodiment, the intercepting the video segment of the video information that includes the defective image frame includes:
determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle;
positioning the shooting time corresponding to the defect image frame to the flight time period;
and intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period.
An image data acquisition apparatus, the apparatus comprising:
the image data acquisition module is used for acquiring video information uploaded by the unmanned aerial vehicle, and the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
the image frame extraction module is used for extracting an original image frame of which the video information contains a preset acquisition target;
the image identification module is used for identifying a defect image frame contained in the original image frame;
the video intercepting module is used for intercepting a video clip containing the defect image frame in the video information;
and the information uploading module is used for uploading the defect image frame and the video clip.
In one embodiment, the system further includes a path planning module, where the path planning module is specifically configured to:
acquiring coordinate information of each preset acquisition target;
determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target;
acquiring obstacle information of the flight area information in real time;
and planning the flight route of the unmanned aerial vehicle according to the obstacle information to obtain a preset flight route.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information contains a preset acquisition target;
identifying a defective image frame contained in the original image frame;
intercepting a video clip containing the defect image frame in the video information;
and uploading the defect image frame and the video clip.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information contains a preset acquisition target;
identifying a defective image frame contained in the original image frame;
intercepting a video clip containing the defect image frame in the video information;
and uploading the defect image frame and the video clip.
According to the image data acquisition method, the image data acquisition device, the computer equipment and the storage medium, the video information uploaded by the unmanned aerial vehicle is acquired; extracting an original image frame of which the video information contains a preset acquisition target; identifying a defective image frame contained in the original image frame; intercepting a video clip containing the defect image frame in the video information; and uploading the defect image frame and the video clip. According to the image data acquisition method, the image data are acquired through the unmanned aerial vehicle, the target defect image frame in the data acquired by the unmanned aerial vehicle is identified, the defect image frame and the video clip containing the defect image frame are directly uploaded, the data volume of data transmission is effectively reduced, and the data volume of the image data in the transmission process is obviously reduced.
Drawings
FIG. 1 is a diagram of an exemplary embodiment of a method for image data acquisition;
FIG. 2 is a schematic flow chart diagram illustrating a method for image data acquisition according to one embodiment;
FIG. 3 is a schematic sub-flow chart of step S300 of FIG. 2 in one embodiment;
FIG. 4 is a schematic sub-flow chart illustrating step S500 of FIG. 2 according to an embodiment;
FIG. 5 is a block diagram showing the structure of an image data acquisition apparatus according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The unmanned aerial vehicle management method can be applied to the application environment shown in fig. 1, wherein the unmanned aerial vehicle 102 communicates with the unmanned aerial vehicle management server 104 through a network, the unmanned aerial vehicle management server 104 communicates with the cloud server 106 through the network, and the unmanned aerial vehicle management server 104 is located in an unmanned aerial vehicle parking room and used for controlling the work of the unmanned aerial vehicle. In addition, unmanned aerial vehicle stops quick-witted room and has included the storehouse body and door, and the storehouse body has waterproof, thermal-insulated function. The storehouse body bottom is equipped with one and is used for laying "carry of carry such as unmanned aerial vehicle upper camera, laser radar and places the hole". The unmanned aerial vehicle management server is used for acquiring defect images of a preset acquisition target and providing technical support for maintaining normal work of the preset acquisition target, firstly, the unmanned aerial vehicle management server acquires video information uploaded by the unmanned aerial vehicle, and the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route; identifying a defect image frame contained in an original image frame; intercepting a video clip containing a defective image frame in video information; and uploading the defect image frames and the video clips to a cloud server for data analysis workers to use.
As shown in fig. 2, in one embodiment, the image data acquisition method is implemented by an unmanned aerial vehicle management server, and specifically includes the following steps:
s100, video information uploaded by the unmanned aerial vehicle is obtained, and the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route.
The preset flight route is preset by the unmanned aerial vehicle management server according to actual conditions and is used for guiding the unmanned aerial vehicle to execute a flight task, a preset acquisition target for acquiring images by the unmanned aerial vehicle is contained in the route, meanwhile, obstacles in a flight area can be avoided, the obstacles are prevented from interfering the flight of the unmanned aerial vehicle, the unmanned aerial vehicle management server can lead the preset flight route into the unmanned aerial vehicle, and the unmanned aerial vehicle flies according to the flight route to acquire required video information. After unmanned aerial vehicle takes off, unmanned aerial vehicle management server can be through setting up with unmanned aerial vehicle parking house in, the router of being connected with unmanned aerial vehicle management server receives unmanned aerial vehicle and flies the video information with gathering again on the way.
And S300, extracting the original image frame of which the video information contains a preset acquisition target.
The video information contains all image frames acquired by a camera of the unmanned aerial vehicle in the flying process, wherein some image frames are image frames which do not contain a preset acquisition target, the image frames are useless for the data analysis process of image data acquisition, the image frames can be removed through extraction of the data frames, and the original image frames containing the preset acquisition target are directly acquired.
And S500, identifying a defect image frame contained in the original image frame.
The original image frames refer to all image frames containing the preset acquisition target, and if the original image frames are used for maintaining the preset acquisition target, the normal original image frames are useless, and the image frames with abnormal phenomena in the original image frames can be identified and used as defect image frames for the maintenance and analysis process.
S700, intercepting a video clip containing the defect image frame in the video information.
The video information contains all the video information collected by the unmanned aerial vehicle, and it is necessary to intercept all the video clips of the video information containing the defective image frames to assist the image analysis work of maintenance workers.
And S900, uploading the defect image frame and the video clip.
After the defect video frames and the corresponding video clips are extracted and obtained, the router can be used for establishing connection with the cloud server, the defect video frames and the corresponding video clips are transmitted to the cloud server, only the defect video frames and the video clips are uploaded, and through edge calculation, collected images are processed nearby the unmanned aerial vehicle, so that the data transmission amount can be effectively reduced, the complexity of image data in the collection and transmission processes is reduced, and the image data processing efficiency is improved.
According to the image data acquisition method, the image data acquisition device, the computer equipment and the storage medium, the video information uploaded by the unmanned aerial vehicle is acquired; extracting an original image frame of which the video information contains a preset acquisition target; identifying a defective image frame contained in the original image frame; intercepting a video clip containing the defect image frame in the video information; and uploading the defect image frame and the video clip. According to the image data acquisition method, the image data are acquired through the unmanned aerial vehicle, the target defect image frame in the data acquired by the unmanned aerial vehicle is identified, the defect image frame and the video clip containing the defect image frame are directly uploaded, the data volume of data transmission is effectively reduced, and the data volume of the image data in the transmission process is obviously reduced.
In one embodiment, S100 includes:
the method comprises the steps of obtaining coordinate information of each preset collection target, determining flight area information of the unmanned aerial vehicle according to the coordinate information of each preset collection target, obtaining barrier information of the flight area information in real time, planning a flight route of the unmanned aerial vehicle according to the barrier information, and generating and pushing the preset flight route to the unmanned aerial vehicle.
Unmanned aerial vehicle management server prestores whole flight area's information, and unmanned aerial vehicle's image information acquisition work has corresponding target acquisition point, and the user can input unmanned aerial vehicle management server with these target points, and unmanned aerial vehicle management server can be through these coordinate points of mark on the map, discernment judgement unmanned aerial vehicle possible flight area. In addition, the unmanned aerial vehicle can also acquire real-time obstacle information of the areas, and the obstacle information is particularly an obstacle located in the flight height range of the unmanned aerial vehicle. Carry out unmanned aerial vehicle's flight route planning through flight area information and barrier information, obtain preset flight route, can obtain best flight route to with this preset flight route propelling movement to unmanned aerial vehicle, improve unmanned aerial vehicle image acquisition process's efficiency.
In one embodiment, S900 is preceded by:
each of the defective image frame and the video clip of the defective image frame is divided into a plurality of pixel regions of the same size.
Each pixel region is divided into a plurality of sub-pixel regions of the same size.
And compressing each sub-pixel region at a preset compression ratio to form a corresponding data block.
All data blocks related to one pixel area are arranged according to a preset sequence and stored in a corresponding data block.
And arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip.
And S900, uploading the compressed defect image frame and the compressed video clip.
The pixel region refers to a video image display region including a plurality of pixels. Each frame of video image can be divided into a plurality of pixel areas, then the divided pixel areas are divided again to obtain sub-pixel areas, so that a complete video image is divided into a plurality of smaller pixel display areas, each sub-pixel area is compressed and encoded respectively to form different data blocks corresponding to each sub-pixel area, the preset compression ratio can comprise 25%, 50% and 75%, and the specific percentage of compression can be set according to the resolution of the acquired image and the required definition of the image data for analysis. The storage structure of the block data is formed by compressing each sub-pixel area to form a corresponding data block, storing the corresponding data block in the data block associated with each pixel area, and arranging and storing the data blocks in a raster scanning manner, thereby facilitating the access to the storage data. The compressed fast data can be uploaded to a cloud server, and the cloud server decodes the compressed block data to obtain original defect image frames and video clips. The data volume uploaded to the cloud server can be further reduced through compression, and the efficiency of the data uploading process is improved.
As shown in fig. 3, in one embodiment, S300 includes:
s320, determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle.
S340, searching the video information in the flight time period in the video information.
And S360, extracting the image frame in the video information in the flight time period as an original image frame.
Specifically, include orientation module on the unmanned aerial vehicle, unmanned aerial vehicle management server can fix a position current unmanned aerial vehicle's position through orientation module, thereby can confirm that unmanned aerial vehicle reachs and leaves each and predetermine the time point when gathering the target, unmanned aerial vehicle management server can directly intercept the video information that unmanned aerial vehicle gathered in each flight time quantum of predetermineeing the collection target, and extract the video data frame in these video information, as pending original image frame. Can extract target video image from the video image of unmanned aerial vehicle camera collection through unmanned aerial vehicle's position and the corresponding relation constantly, avoid the video image of processing too much, influence the treatment effeciency.
As shown in fig. 4, in one embodiment, S500 includes:
and S520, acquiring images of all angles of a preset acquisition target.
And S540, determining real-time original image frames corresponding to the angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at each shooting moment.
And S560, acquiring the similarity between the angle image of the preset acquisition target and the corresponding real-time original image frame.
And S580, when the similarity is lower than a preset similarity threshold, judging the original image frame to be a defect image frame.
The images of the preset collection target are taken from different directions and possible shooting angles by the unmanned aerial vehicle, and can be collected by the unmanned aerial vehicle in advance and taken as the images of the preset collection target after being qualified through manual inspection. Each image video frame corresponds to the positioning information and the camera angle of the unmanned aerial vehicle at that time one by one, and the angle image corresponding to the current original image frame can be searched from each angle image of the preset acquisition target through the positioning information (including position information and flight height information) and the camera angle. Then, by comparing the preset angle image and the acquired image data frame, when the difference between the image data frame and the preset angle image is too large, the current preset acquisition target is considered to have a certain change compared with the original preset acquisition target, so that the image data frame can be determined as a defect image frame. In one embodiment, the preset acquisition target is a building site high-rise building, and when a green protection cover of the building site high-rise building is damaged, an image video frame containing the damaged green protection cover can be uploaded as a defect image frame. By uploading the defect image frames to the cloud server, maintenance workers at the cloud can analyze the implementation condition of the preset acquisition target through the defect image frames.
In one embodiment, S700 includes:
according to the positioning information of the unmanned aerial vehicle, determining the flight time period of the unmanned aerial vehicle at each preset acquisition target.
And positioning the shooting moment corresponding to the defect image frame to the flight time period.
And intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period.
Under the condition that the defect image frame occurs, more powerful analysis basis is necessarily provided for the cloud server side, at the moment, the video clips containing the defect image frame can be intercepted to serve as further evidence to help cloud workers to further analyze actual conditions, at the moment, the video clips containing the preset acquisition targets can be intercepted from the whole video information, the defect image frame is positioned in the clips, the video clips from the first occurrence to the last occurrence of the defect image frame are intercepted from the video clips to serve as the video clips uploaded to the cloud server, and the effectiveness of video image data analysis can be effectively improved by providing the analysis video.
In one embodiment, an image data acquisition method of the present application includes: acquiring coordinate information of each preset acquisition target; determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target; acquiring obstacle information of flight area information in real time; and planning the flight route of the unmanned aerial vehicle according to the barrier information, and generating and pushing a preset flight route to the unmanned aerial vehicle. Acquiring video information uploaded by an unmanned aerial vehicle; determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; searching video information in the flight time period in the video information; and extracting the image frames in the video information in the flight time period as original image frames. Acquiring images of all angles of a preset acquisition target; determining real-time original image frames corresponding to all angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at all shooting moments; acquiring the similarity between an angle image of a preset acquisition target and a corresponding real-time original image frame; and when the similarity is lower than a preset similarity threshold value, judging the original image frame as a defect image frame. Determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; positioning the shooting time corresponding to the defect image frame to a flight time period; and intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period. Dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size; dividing each pixel region into a plurality of sub-pixel regions of the same size; compressing each sub-pixel region at a preset compression ratio to form a corresponding data block; arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block; and arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip. And uploading the compressed defect image frames and the video clips.
It should be understood that although the various steps in the flow charts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
As shown in fig. 5, the present application further includes an image data acquisition apparatus, comprising:
the image data acquisition module 100 is used for acquiring video information uploaded by the unmanned aerial vehicle, and the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
the image frame extraction module 300 is configured to extract an original image frame of which video information includes a preset acquisition target;
an image recognition module 500, configured to recognize a defective image frame included in an original image frame;
the video intercepting module 700 is configured to intercept a video segment containing a defective image frame in video information;
and an information uploading module 900, configured to upload the defect image frame and the video clip.
In one embodiment, the system further comprises a path planning module, wherein the path planning module is specifically used for acquiring coordinate information of each preset acquisition target; determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target; acquiring obstacle information of flight area information in real time; and planning the flight route of the unmanned aerial vehicle according to the barrier information, and generating and pushing a preset flight route to the unmanned aerial vehicle.
In one embodiment, the system further comprises a data compression module, configured to divide each of the video images of the defect image frame and the video clip of the defect image frame into a plurality of pixel regions of the same size; dividing each pixel region into a plurality of sub-pixel regions of the same size; compressing each sub-pixel region at a preset compression ratio to form a corresponding data block; arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block; and arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip. The information uploading module 900 is specifically configured to upload the compressed defect image frames and video clips.
In one embodiment, the image frame extraction module 300 is configured to determine a flight time period of the drone at each preset acquisition target according to the positioning information of the drone; searching video information in the flight time period in the video information; and extracting the image frames in the video information in the flight time period as original image frames.
In one embodiment, the image recognition module 500 is configured to obtain images of various angles of a preset acquisition target; determining real-time original image frames corresponding to all angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at all shooting moments; acquiring the similarity between an angle image of a preset acquisition target and a corresponding real-time original image frame; and when the similarity is lower than a preset similarity threshold value, judging the original image frame as a defect image frame.
In one embodiment, the video capture module 700 is configured to determine a flight time period of the drone at each preset acquisition target according to the positioning information of the drone; positioning the shooting time corresponding to the defect image frame to a flight time period; and intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period.
For specific limitations of the image data acquisition device, reference may be made to the above limitations of the image data acquisition method, which are not described herein again. The respective modules in the image data acquisition apparatus described above may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an image data acquisition method.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information comprises a preset acquisition target;
identifying a defect image frame contained in an original image frame;
intercepting a video clip containing a defective image frame in video information;
and uploading the defect image frame and the video clip.
In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring coordinate information of each preset acquisition target; determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target; acquiring obstacle information of flight area information in real time; and planning the flight route of the unmanned aerial vehicle according to the barrier information, and generating and pushing a preset flight route to the unmanned aerial vehicle.
In one embodiment, the processor, when executing the computer program, further performs the steps of: dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size; dividing each pixel region into a plurality of sub-pixel regions of the same size; compressing each sub-pixel region at a preset compression ratio to form a corresponding data block; arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block; and arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; searching video information in the flight time period in the video information; and extracting the image frames in the video information in the flight time period as original image frames.
In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring images of all angles of a preset acquisition target; determining real-time original image frames corresponding to all angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at all shooting moments; acquiring the similarity between an angle image of a preset acquisition target and a corresponding real-time original image frame; and when the similarity is lower than a preset similarity threshold value, judging the original image frame as a defect image frame.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; positioning the shooting time corresponding to the defect image frame to a flight time period; and intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information comprises a preset acquisition target;
identifying a defect image frame contained in an original image frame;
intercepting a video clip containing a defective image frame in video information;
and uploading the defect image frame and the video clip.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring coordinate information of each preset acquisition target; determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target; acquiring obstacle information of flight area information in real time; and planning the flight route of the unmanned aerial vehicle according to the barrier information, and generating and pushing a preset flight route to the unmanned aerial vehicle.
In one embodiment, the computer program when executed by the processor further performs the steps of: dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size; dividing each pixel region into a plurality of sub-pixel regions of the same size; compressing each sub-pixel region at a preset compression ratio to form a corresponding data block; arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block; and arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; searching video information in the flight time period in the video information; and extracting the image frames in the video information in the flight time period as original image frames.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring images of all angles of a preset acquisition target; determining real-time original image frames corresponding to all angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at all shooting moments; acquiring the similarity between an angle image of a preset acquisition target and a corresponding real-time original image frame; and when the similarity is lower than a preset similarity threshold value, judging the original image frame as a defect image frame.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; positioning the shooting time corresponding to the defect image frame to a flight time period; and intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of image data acquisition, the method comprising:
acquiring video information uploaded by an unmanned aerial vehicle, wherein the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
extracting an original image frame of which the video information contains a preset acquisition target;
identifying a defective image frame contained in the original image frame;
intercepting a video clip containing the defect image frame in the video information;
uploading the defect image frame and the video clip;
the video information that obtains unmanned aerial vehicle and upload, video information by before unmanned aerial vehicle gathers according to the flight of predetermineeing the flight route, still include:
acquiring coordinate information of each preset acquisition target;
determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target;
acquiring barrier information of the flight area information in real time, wherein the barrier is a barrier in the flight height range of the unmanned aerial vehicle;
planning a flight route of the unmanned aerial vehicle according to the obstacle information, and generating and pushing a preset flight route to the unmanned aerial vehicle;
the intercepting the video segment containing the defect image frame in the video information comprises:
determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle;
positioning the shooting time corresponding to the defect image frame to the flight time period;
intercepting a video clip containing the defect image frame in the video information according to the shooting time corresponding to the first defect image frame and the shooting time corresponding to the last defect image frame in each flight time period;
the uploading the defect image frame and the video clip comprises:
and establishing connection with a cloud server through a router, and transmitting the defect image frame and the video clip to the cloud server.
2. The method of claim 1, wherein said uploading said defect image further comprises, prior to:
dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size;
dividing each pixel region into a plurality of sub-pixel regions of the same size;
compressing each sub-pixel region at a preset compression ratio to form a corresponding data block;
arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block;
arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip;
the uploading the defect image frame and the video clip comprises:
and uploading the compressed defect image frame and the video clip.
3. The method of claim 1, wherein the extracting the original image frames of which the video information contains a preset acquisition target comprises:
determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle;
searching the video information in the flight time period in the video information;
and extracting an image frame in the video information in the flight time period as an original image frame.
4. The method of claim 1, wherein the identifying the defective image frames contained in the original image frames comprises:
acquiring images of all angles of the preset acquisition target;
determining real-time original image frames corresponding to the angle images of the unmanned aerial vehicle according to the positioning information and the camera angle information of the unmanned aerial vehicle at each shooting moment;
acquiring the similarity between the angle image of the preset acquisition target and the corresponding real-time original image frame;
and when the similarity is lower than a preset similarity threshold value, judging the original image frame to be a defect image frame.
5. The method of claim 1, wherein the predetermined acquisition target comprises a building of a worksite, and the defect image frames comprise video frames of images of a green cover of the building of the worksite with a break.
6. An image data acquisition apparatus, characterized in that the apparatus comprises:
the image data acquisition module is used for acquiring video information uploaded by the unmanned aerial vehicle, and the video information is acquired by the unmanned aerial vehicle in a flying mode according to a preset flying route;
the image frame extraction module is used for extracting an original image frame of which the video information contains a preset acquisition target;
the image identification module is used for identifying a defect image frame contained in the original image frame;
the video intercepting module is used for intercepting a video clip containing the defect image frame in the video information;
the information uploading module is used for uploading the defect image frame and the video clip;
a path planning module to: acquiring coordinate information of each preset acquisition target; determining the flight area information of the unmanned aerial vehicle according to the coordinate information of each preset acquisition target; acquiring barrier information of the flight area information in real time, wherein the barrier is a barrier in the flight height range of the unmanned aerial vehicle; planning a flight route of the unmanned aerial vehicle according to the obstacle information, and generating and pushing a preset flight route to the unmanned aerial vehicle;
the image frame extraction module is specifically configured to: determining the flight time period of the unmanned aerial vehicle at each preset acquisition target according to the positioning information of the unmanned aerial vehicle; searching the video information in the flight time period in the video information; extracting an image frame in the video information in the flight time period as an original image frame;
the information uploading module is specifically configured to: and establishing connection with a cloud server through a router, and transmitting the defect image frame and the video clip to the cloud server.
7. The apparatus of claim 6, further comprising a data compression module to: dividing each frame of video image in the defect image frame and the video clip of the defect image frame into a plurality of pixel areas with the same size; dividing each pixel region into a plurality of sub-pixel regions of the same size; compressing each sub-pixel region at a preset compression ratio to form a corresponding data block; arranging all data blocks related to one pixel area according to a preset sequence and storing the data blocks in a corresponding data block; arranging all the data blocks according to a preset sequence and storing the data blocks in a storage unit, and acquiring the compressed defect image frame and the compressed video clip; the information uploading module is used for: and uploading the compressed defect image frame and the video clip.
8. The apparatus of claim 6, wherein the predetermined acquisition target comprises a building of a worksite, and the defect image frames comprise video frames of images of a green cover of the building of the worksite broken.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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