CN111476313A - Unmanned aerial vehicle photo classification method and device and computer readable storage medium - Google Patents
Unmanned aerial vehicle photo classification method and device and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a method and a device for classifying photos of an unmanned aerial vehicle and a computer readable storage medium. The method comprises the following steps: acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers; calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set; selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum; and placing the photo of the unmanned aerial vehicle into a folder corresponding to the target tower. The scheme provided by the invention can realize automatic classification of the photos of the unmanned aerial vehicle, save manpower and material resources and improve the inspection efficiency of the overhead line of the distribution network.
Description
Technical Field
The embodiment of the invention relates to the field of power grid security protection, in particular to a method and a device for classifying photos of an unmanned aerial vehicle and a computer readable storage medium.
Background
With the continuous development and popularization of unmanned aerial vehicle technology, unmanned aerial vehicles have been widely applied to overhead power transmission/distribution line inspection to reach the defect and hidden danger that find circuit and insulator etc. exist fast, guide the purpose of safety in production. To a large amount of photos that unmanned aerial vehicle scene was shot, often need artifical cost a large amount of time to classify the photo one by one according to circuit, pole number, work load is big and there is the possibility of categorised mistake, inefficiency, error are big.
Disclosure of Invention
The embodiment of the invention provides a method and a device for classifying photos of an unmanned aerial vehicle and a computer readable storage medium, which can realize automatic classification of the photos of the unmanned aerial vehicle, save manpower and material resources and improve the patrol efficiency of overhead lines of a distribution network.
In a first aspect, an embodiment of the present invention provides a method for classifying photos of an unmanned aerial vehicle, including:
acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line;
calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set;
selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum;
and placing the photo of the unmanned aerial vehicle into a folder corresponding to the target tower.
Optionally, selecting a target tower includes:
arranging the distances between the shooting coordinates of the unmanned aerial vehicle photos and the geographic coordinates of each tower according to a preset sequence;
and selecting the tower with the minimum distance as a target tower.
Optionally, the preset sequence is a sequence from small to large or a sequence from large to small.
Optionally, if the number of target shaft tower is not 1, then put into the folder that target shaft tower corresponds with the unmanned aerial vehicle photo, include:
adding special marks for the unmanned aerial vehicle photos, and putting the unmanned aerial vehicle photos into folders corresponding to all target towers.
Optionally, if the number of target shaft tower is not 1, then put into the folder that target shaft tower corresponds with the unmanned aerial vehicle photo, include:
acquiring a flight track of the unmanned aerial vehicle;
and selecting an accurate target tower from the target towers according to the flight track, and putting the photo of the unmanned aerial vehicle into a folder corresponding to the accurate target tower.
Optionally, the unmanned aerial vehicle photo further includes a shooting time;
put into the folder that target shaft tower corresponds with the unmanned aerial vehicle photo, include:
step a), acquiring a target subfolder in a folder corresponding to a target tower, wherein the target subfolder is a first subfolder in the folder;
step b) judging whether the shooting time of the unmanned aerial vehicle photo is matched with the storable time of the target subfolder;
step c), if the images are matched, placing the unmanned aerial vehicle photos into a target subfolder;
and d) if the subfolders are not matched with the subfolders, taking the next subfolder as a target subfolder, and returning to execute the step b).
Optionally, the method further includes:
deleting the unmanned aerial vehicle photos stored in the folders corresponding to the towers periodically or aperiodically.
In a second aspect, an embodiment of the present invention further provides a device for classifying photos of an unmanned aerial vehicle, including: the device comprises an acquisition module, a calculation module, a selection module and an execution module;
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring an unmanned aerial vehicle photo and a tower coordinate set, the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers;
the calculation module is used for calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set;
the selection module is used for selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum;
and the execution module is used for placing the unmanned aerial vehicle photos into the corresponding file folder of the target tower.
In a third aspect, an embodiment of the present invention further provides a device for classifying photos of an unmanned aerial vehicle, including: a processor for implementing the method of any of the above embodiments when executing the computer program.
In a fourth aspect, the present invention further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method of any one of the above embodiments.
The invention provides a classification method, a device and a computer readable storage medium for unmanned aerial vehicle photos, wherein the method comprises the following steps: acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line; calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set; selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum; and placing the photo of the unmanned aerial vehicle into a folder corresponding to the target tower. By establishing a pole tower coordinate set and calculating the distance between the shooting place of the unmanned aerial vehicle photo and the geographic position of each pole tower, the pole tower closest to the shooting place of the unmanned aerial vehicle photo is selected as a target pole tower, the unmanned aerial vehicle photo is placed into a folder corresponding to the target pole tower, automatic classification of the unmanned aerial vehicle photo is realized, compared with the traditional manual photo classification method, manpower and material resources are saved, and the efficiency of aerial distribution network line inspection is improved.
Drawings
Fig. 1 is a schematic flowchart illustrating a method for classifying photos of an unmanned aerial vehicle according to an embodiment;
fig. 2 is a flowchart illustrating another method for classifying photos taken by a drone according to an embodiment;
fig. 3 is a schematic flowchart of a method for classifying photos of an unmanned aerial vehicle according to the second embodiment;
fig. 4 is a schematic structural diagram of a sorting apparatus for photos of unmanned aerial vehicles according to a third embodiment;
fig. 5 is a schematic structural diagram of another sorting apparatus for photos taken by unmanned aerial vehicles according to the third embodiment;
fig. 6 is a schematic structural diagram of a sorting apparatus for photos of an unmanned aerial vehicle according to the fourth embodiment.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
With the continuous development and popularization of unmanned aerial vehicle technology, unmanned aerial vehicles have been widely applied to overhead power transmission/distribution line inspection to reach the defect and hidden danger that find circuit and insulator etc. exist fast, guide the purpose of safety in production. To a large amount of photos that unmanned aerial vehicle scene was shot, often need artifical cost a large amount of time to classify the photo one by one according to circuit, pole number, work load is big and there is the possibility of categorised mistake, inefficiency, error are big. At present, although there has been unmanned aerial vehicle electric power cruise system in the market to be in using, this system can only take a picture to known shaft tower then file the photo in known shaft tower file, and the system is complicated, with high costs, is difficult to adapt to the complicated net overhead line tour of distribution of environment.
In order to solve the problems, the invention provides a classification method and a classification device for unmanned aerial vehicle photos and a computer readable storage medium.
It should be noted that the following embodiments of the present invention may be implemented individually, or may be implemented in combination with each other, and the embodiments of the present invention are not limited in this respect.
In the following, a classification method and apparatus for photos of an unmanned aerial vehicle and technical effects thereof are described.
Example one
Fig. 1 is a schematic flow diagram of a method for classifying photos of an unmanned aerial vehicle according to an embodiment, and as shown in fig. 1, the method provided in this embodiment is applicable to a device for classifying photos of an unmanned aerial vehicle (which may be an unmanned aerial vehicle (that is, the unmanned aerial vehicle itself classifies the captured photos) or a computer (that is, the computer classifies the photos after receiving the photos captured by the unmanned aerial vehicle), and the method includes the following steps.
S101, acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line.
The unmanned aerial vehicle photo is the photo that unmanned aerial vehicle took when joining in marriage net overhead line tour, and the quantity of unmanned aerial vehicle photo is one or many. When the quantity of unmanned aerial vehicle photo is many, the sorter of unmanned aerial vehicle photo can classify the photo one by one, also can classify a plurality of photos simultaneously.
Each unmanned aerial vehicle photo all includes shoots the coordinate, shoots the coordinate that the coordinate is this photo when shooing unmanned aerial vehicle and is located, shoots the coordinate and can adopt the form of geographical coordinate to express.
The tower coordinate set can be pre-established and stored in the classification device of the unmanned aerial vehicle photos, and can also be established in real time by the classification device of the unmanned aerial vehicle photos. The tower coordinate set comprises geographic coordinates of all towers on a distribution network overhead line which the unmanned aerial vehicle can patrol, and the geographic coordinates are spherical coordinates which represent the position of the ground point by latitude and longitude.
S102, calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set.
S103, selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum.
The distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower reflects the distance between the shooting location of the unmanned aerial vehicle photo and the geographic position of each tower, so that the target tower is the tower closest to the shooting location of the unmanned aerial vehicle photo, and the unmanned aerial vehicle photo most possibly reflects relevant information of the target tower, peripheral lines of the target tower, insulators and the like.
In one embodiment, the method for selecting a target tower may include the following two steps:
step 1, arranging the distances between the shooting coordinates of the unmanned aerial vehicle photos and the geographic coordinates of each tower according to a preset sequence.
The preset sequence is from small to large or from large to small.
And 2, selecting the tower with the minimum distance as a target tower.
S104, placing the unmanned aerial vehicle photos into a folder corresponding to the target pole tower.
And after the target tower is selected, placing the photos of the unmanned aerial vehicle into the folder corresponding to the target tower, and repeating the steps until each photo of the unmanned aerial vehicle is placed into the folder corresponding to the corresponding tower. So that the monitoring of the tower, peripheral lines, insulators and the like can be realized by looking up the photos in the folders corresponding to different towers.
In an embodiment, after the distances between the shooting coordinates of the photos of the unmanned aerial vehicle and the geographic coordinates of each tower are arranged according to the preset sequence in step S103, it is found that there may be two or more towers with the smallest distance, that is, the number of target towers is not 1.
The method I comprises the steps of adding special marks to the photos of the unmanned aerial vehicle, and placing the photos of the unmanned aerial vehicle into folders corresponding to all target towers.
Exemplarily, it is assumed that the number of target towers is 2 (which is recorded as tower 1 and tower 2), the shooting coordinate of the photo of the unmanned aerial vehicle is located at the middle point of the connecting line between the tower 1 and the tower 2, and it cannot be determined whether the photo shoots the tower 1 or the tower 2 on the ground at this time, so that in the first mode, the classification device of the photo of the unmanned aerial vehicle adds a special mark to the photo of the unmanned aerial vehicle, and places the photo of the unmanned aerial vehicle into the folder corresponding to the tower 1 and the folder corresponding to the tower 2.
Therefore, no matter whether the picture is taken from the tower 1 or the tower 2, the picture can be found from the file folders corresponding to the tower 1 and the tower 2. In addition, because the unmanned aerial vehicle photo has added special mark, can make monitoring personnel can discern this photo fast, make things convenient for subsequent reply to handle.
Optionally, the special mark may be any mark that can be specially recognized, such as a character and a mark added to the attribute information of the photo of the unmanned aerial vehicle.
Acquiring the flight track of the unmanned aerial vehicle; and selecting an accurate target tower from the target towers according to the flight track, and putting the photo of the unmanned aerial vehicle into a folder corresponding to the accurate target tower.
Exemplarily, assuming that the number of target towers is 2 (which is recorded as tower 1 and tower 2), the shooting coordinate of the photo of the unmanned aerial vehicle is located at the middle point of the connecting line between the tower 1 and the tower 2, and it cannot be determined whether the photo shoots the tower 1 or the tower 2 on the ground at this time, therefore, in the second mode, the classification device of the photo of the unmanned aerial vehicle acquires the flight trajectory of the unmanned aerial vehicle (flying from point a to point B, and going to the tower 2), selects the tower 2 from the tower 1 and the tower 2 according to the flight trajectory, and places the photo of the unmanned aerial vehicle into the folder corresponding to the tower 2.
Therefore, the tower to which the unmanned aerial vehicle photo belongs can be accurately judged, and compared with the first mode, the storage space is saved.
On the basis of the foregoing embodiment, fig. 2 is a schematic flowchart of another classification method for photos taken by an unmanned aerial vehicle according to the first embodiment, and as shown in fig. 2, the method further includes:
and S105, deleting the unmanned aerial vehicle photos stored in the folders corresponding to the towers periodically or aperiodically.
Considering the limitation of the storage space of the file folders and the characteristic that the unmanned aerial vehicle photos do not need to be stored for a long time, the classification device of the unmanned aerial vehicle photos can delete the unmanned aerial vehicle photos stored in the file folders corresponding to the towers periodically or non-periodically.
For example, the photos of the unmanned aerial vehicle stored in the folder corresponding to each tower may be deleted monthly/weekly, or the photos of the unmanned aerial vehicle stored in the folder corresponding to each tower for more than a certain period of time may be deleted.
The invention provides a method for classifying photos of an unmanned aerial vehicle, which comprises the following steps: acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line; calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set; selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum; and placing the photo of the unmanned aerial vehicle into a folder corresponding to the target tower. By establishing a pole tower coordinate set and calculating the distance between the shooting place of the unmanned aerial vehicle photo and the geographic position of each pole tower, the pole tower closest to the shooting place of the unmanned aerial vehicle photo is selected as a target pole tower, the unmanned aerial vehicle photo is placed into a folder corresponding to the target pole tower, automatic classification of the unmanned aerial vehicle photo is realized, compared with the traditional manual photo classification method, manpower and material resources are saved, and the efficiency of aerial distribution network line inspection is improved.
Example two
Fig. 3 is a schematic flow chart of a method for classifying photos of an unmanned aerial vehicle according to a second embodiment, and as shown in fig. 3, the method according to the second embodiment is applicable to a device for classifying photos of an unmanned aerial vehicle or a computer. The method comprises the following steps.
S201, acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line.
S202, calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set.
S203, selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum.
S204, step a) obtaining a target subfolder in a folder corresponding to the target tower, wherein the target subfolder is a first subfolder in the folder.
S205, step b) judges whether the shooting time of the unmanned aerial vehicle photo is matched with the storable time of the target subfolder.
S206, if the images are matched in the step c), placing the unmanned aerial vehicle photos into the target subfolder.
S207, if the subfolders are not matched in the step d), taking the next subfolder as the target subfolder, and returning to execute the step b).
Therefore, the unmanned aerial vehicle photos can be classified in a secondary mode to adapt to more use scenes.
For example, assuming that four subfolders (denoted as subfolder 1, subfolder 2, subfolder 3 and subfolder 4 respectively) are included in the corresponding folder of the target tower, the storable time of subfolder 1 is 2020.1.1-2020.1.31, the storable time of subfolder 2 is 2020.2.1-2020.2.29, the storable time of subfolder 3 is 2020.3.1-2020.3.31, the storable time of subfolder 4 is 2020.4.1-now, and the shooting time of the drone photo is 2020.4.3.
The classification device of the unmanned aerial vehicle photo firstly takes the subfolder 1 as a target subfolder, judges that the shooting time 2020.4.3 of the unmanned aerial vehicle photo is not matched with the storable time 2020.1.1-2020.1.31 of the subfolder 1, then takes the subfolder 2 as the target subfolder, and continuously judges that the shooting time 2020.4.3 of the unmanned aerial vehicle photo is not matched with the storable time 2020.2.1-2020.2.29 of the subfolder 2. With subfolder 3 as the target subfolder, judge that the shooting time 2020.4.3 that reachs the unmanned aerial vehicle photo does not match with storable time 2020.3.1-2020.3.31 of subfolder 3, regard subfolder 4 as the target subfolder, judge that the shooting time 2020.4.3 that reachs the unmanned aerial vehicle photo matches with storable time 2020.4.1-so far of subfolder 4, put into the subfolder 4 with the unmanned aerial vehicle photo.
EXAMPLE III
Fig. 4 is a schematic structural diagram of a sorting apparatus for photos of an unmanned aerial vehicle according to a third embodiment, as shown in fig. 4, including: the system comprises an acquisition module 10, a calculation module 11, a selection module 12 and an execution module 13;
the acquisition module 10 is used for acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers;
the calculation module 11 is configured to calculate a distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set;
the selection module 12 is configured to select a target tower according to a distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, where the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the smallest;
and the execution module 13 is used for placing the unmanned aerial vehicle photos into the corresponding folders of the target tower.
The classification device of unmanned aerial vehicle photo that this embodiment provided is for realizing the classification method of the unmanned aerial vehicle photo of above-mentioned embodiment, and the classification device of unmanned aerial vehicle photo that this embodiment provided realizes principle and technological effect similar with above-mentioned embodiment, and this here is no longer repeated.
Optionally, the selection module 12 is specifically configured to arrange distances between shooting coordinates of the photos of the unmanned aerial vehicle and geographic coordinates of each tower according to a preset sequence; and selecting the tower with the minimum distance as a target tower.
Optionally, the preset sequence is a sequence from small to large or a sequence from large to small.
Optionally, if the number of the target towers is not 1, the execution module 13 is specifically configured to add a special mark to the photos of the unmanned aerial vehicle, and place the photos of the unmanned aerial vehicle into folders corresponding to all the target towers.
Optionally, if the number of the target towers is not 1, the execution module 13 is specifically configured to acquire a flight trajectory of the unmanned aerial vehicle; and selecting an accurate target tower from the target towers according to the flight track, and putting the photo of the unmanned aerial vehicle into a folder corresponding to the accurate target tower.
Optionally, the unmanned aerial vehicle photo further includes a shooting time;
the execution module 13 is specifically configured to execute steps a) to d), where steps a) to d) include:
step a), acquiring a target subfolder in a folder corresponding to a target tower, wherein the target subfolder is a first subfolder in the folder;
step b) judging whether the shooting time of the unmanned aerial vehicle photo is matched with the storable time of the target subfolder;
step c), if the images are matched, placing the unmanned aerial vehicle photos into a target subfolder;
and d) if the subfolders are not matched with the subfolders, taking the next subfolder as a target subfolder, and returning to execute the step b).
Optionally, with reference to fig. 4, fig. 5 is a schematic structural diagram of another sorting apparatus for photos taken by an unmanned aerial vehicle according to the third embodiment, as shown in fig. 5, the apparatus further includes: a deletion module 14;
and the deleting module 14 is used for periodically or aperiodically deleting the unmanned aerial vehicle photos stored in the folders corresponding to the towers.
Example four
Fig. 6 is a schematic structural diagram of a sorting apparatus for photos of a drone provided in the fourth embodiment, as shown in fig. 6, the sorting apparatus for photos of a drone includes a processor 30, a memory 31, and a communication interface 32; the number of the processors 30 in the classification device of the photos of the unmanned aerial vehicle can be one or more, and one processor 30 is taken as an example in fig. 6; the processor 30, the memory 31 and the communication interface 32 in the sorting device of the photos of the drone may be connected through a bus or in other ways, and fig. 6 illustrates the connection through the bus as an example. A bus represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures.
The memory 31, which is a computer-readable storage medium, may be configured to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the methods in the embodiments of the present invention. The processor 30 executes at least one functional application of the sorting device of the photos of the drone and data processing by running software programs, instructions and modules stored in the memory 31, i.e. implements the method described above.
The memory 31 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the sorting device of the drone photograph, and the like. Further, the memory 31 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 31 may include memory remotely located from the processor 30, which may be connected to the sorting device of the drone photograph over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The communication interface 32 may be configured for the reception and transmission of data.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method provided in any embodiment of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. Computer-readable storage media include (a non-exhaustive list): an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an erasable programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, or a combination of programming languages, including AN object oriented programming language such as Java, Smalltalk, C + +, Ruby, Go, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.
It will be clear to a person skilled in the art that the term user terminal covers any suitable type of wireless user equipment, such as a mobile phone, a portable data processing device, a portable web browser or a car mounted mobile station.
In general, the various embodiments of the invention may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto.
Embodiments of the invention may be implemented by a data processor of a mobile device executing computer program instructions, for example in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.
Any logic flow block diagrams in the figures of the present invention may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored on a memory. The memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), optical storage devices and systems (digital versatile disks, DVDs, or CD discs), etc. The computer readable medium may include a non-transitory storage medium. The data processor may be of any type suitable to the local technical environment, such as but not limited to general purpose computers, special purpose computers, microprocessors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Programmable logic devices (FGPAs), and processors based on a multi-core processor architecture.
Claims (10)
1. A classification method for photos of unmanned aerial vehicles is characterized by comprising the following steps:
acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers on a line;
calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set;
selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum;
and putting the unmanned aerial vehicle photo into a folder corresponding to the target tower.
2. The method of claim 1, wherein selecting the target tower comprises:
arranging the distances between the shooting coordinates of the unmanned aerial vehicle photos and the geographic coordinates of each tower according to a preset sequence;
and selecting the tower with the minimum distance as the target tower.
3. The method of claim 2, wherein the preset order is a small to large order or a large to small order.
4. The method according to claim 1, wherein if the number of the target towers is not 1, placing the photos of the unmanned aerial vehicle into folders corresponding to the target towers comprises:
adding special marks for the unmanned aerial vehicle photos, and placing the unmanned aerial vehicle photos into folders corresponding to all target towers.
5. The method according to claim 1, wherein if the number of the target towers is not 1, placing the photos of the unmanned aerial vehicle into folders corresponding to the target towers comprises:
acquiring a flight track of the unmanned aerial vehicle;
and selecting an accurate target tower from the target towers according to the flight track, and putting the unmanned aerial vehicle photo into a folder corresponding to the accurate target tower.
6. The method of any of claims 1-5, wherein the drone photograph further includes a time of capture;
putting the unmanned aerial vehicle photo into a folder corresponding to the target tower, comprising:
step a), acquiring a target subfolder in a folder corresponding to the target tower, wherein the target subfolder is a first subfolder in the folder;
step b) judging whether the shooting time of the unmanned aerial vehicle photo is matched with the storable time of the target subfolder;
step c), if the unmanned aerial vehicle photos are matched with the target subfolder, placing the unmanned aerial vehicle photos into the target subfolder;
and d) if the subfolders are not matched with the target subfolder, taking the next subfolder as the target subfolder, and returning to execute the step b).
7. The method of claim 1, further comprising:
deleting the unmanned aerial vehicle photos stored in the folders corresponding to the towers periodically or aperiodically.
8. The utility model provides a sorter of unmanned aerial vehicle photo, its characterized in that includes: the device comprises an acquisition module, a calculation module, a selection module and an execution module;
the acquisition module is used for acquiring an unmanned aerial vehicle photo and a tower coordinate set, wherein the unmanned aerial vehicle photo comprises shooting coordinates, and the tower coordinate set comprises geographic coordinates of all towers;
the calculation module is used for calculating the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower according to the shooting coordinate of the unmanned aerial vehicle photo and the tower coordinate set;
the selection module is used for selecting a target tower according to the distance between the shooting coordinate of the unmanned aerial vehicle photo and the geographic coordinate of each tower, wherein the distance between the geographic coordinate of the target tower and the shooting coordinate of the unmanned aerial vehicle photo is the minimum;
and the execution module is used for placing the unmanned aerial vehicle photos into the folder corresponding to the target tower.
9. The utility model provides a sorter of unmanned aerial vehicle photo, its characterized in that includes: a processor for implementing the method of classifying a drone photo according to any one of claims 1 to 7 when executing a computer program.
10. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements the method of classifying a drone photo according to any one of claims 1 to 7.
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