1. A temporary license plate recognition method is characterized by comprising the following steps:

when a target vehicle is detected to enter a preset area, acquiring an image to be detected of the target vehicle;

inputting the image to be detected into a target detection model to obtain a target detection result, wherein the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

judging whether the target detection result only contains the first prediction frame;

if the target detection result is determined to not only contain the first prediction frame, judging whether the first prediction frame is located in the second prediction frame;

and if the first prediction frame is determined to be positioned outside the second prediction frame, determining the license plate of the target vehicle as a temporary license plate.

2. The method of claim 1, wherein after said determining whether only the first prediction box is included in the target detection result, the method further comprises:

and if the target detection result only contains the first prediction frame, determining that the license plate of the target vehicle is a temporary license plate.

3. The method of claim 1, wherein after said determining whether the first prediction box is located within the second prediction box, the method further comprises:

if the first prediction frame is located in a second prediction frame, inputting the image content in the first prediction frame into a license plate classification model to obtain a license plate classification result, wherein the license plate classification result comprises a normal license plate and a temporary license plate;

and when the license plate classification result is a temporary license plate, determining that the license plate of the target vehicle is the temporary license plate.

4. The method of claim 3, further comprising:

and when the license plate classification result is a normal license plate, determining that the license plate of the target vehicle is a normal license plate.

5. The method of any one of claims 1-4, wherein after the determining that the license plate of the vehicle is a temporary license plate, the method further comprises:

a no pass event is triggered.

6. The method of claim 4, wherein after the determining that the license plate of the vehicle is a normal license plate, the method further comprises:

a clear to pass event is triggered.

7. A temporary license plate recognition system, the system comprising:

the device comprises an acquisition unit, a detection unit and a processing unit, wherein the acquisition unit is used for acquiring an image to be detected of a target vehicle when the target vehicle is detected to enter a preset area;

the detection classification unit is used for inputting the image to be detected into a target detection model to obtain a target detection result, the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

a first judgment unit, configured to judge whether the target detection result only includes the first prediction frame;

a second judgment unit, configured to, when the first judgment unit determines that the target detection result includes the first prediction frame, judge whether the first prediction frame is located within the second prediction frame;

a first determining unit, configured to determine that the license plate of the target vehicle is a temporary license plate when the second determining unit determines that the first prediction frame is located outside the second prediction frame.

8. The system of claim 7, wherein the first determination unit is further configured to:

and when the first judging unit determines that the target detection result only contains the first prediction frame, determining that the license plate of the target vehicle is a temporary license plate.

9. A temporary license plate recognition device, the device comprising:

the device comprises a processor, a memory, an input and output unit and a bus;

the processor is connected with the memory, the input and output unit and the bus;

the memory holds a program that the processor calls to perform the method of any one of claims 1 to 6.

10. A computer-readable storage medium having a program stored thereon, the program, when executed on a computer, performing the method of any one of claims 1 to 6.

Background

In recent years, the unattended solution of the parking lot based on the license plate recognition technology is widely applied to the market, the unattended solution not only improves the passing efficiency of the parking lot, but also saves a great deal of personnel expenditure for a property management party, and the unattended solution becomes a hotspot and future development trend of the parking lot management scheme.

In the practical application of the unattended solution, a situation that a vehicle with a temporary license plate is hung passes can exist. The temporary license plate is a paper printed license plate and is usually pasted at one corner of the front windshield and the rear windshield of the vehicle on the premise of not shielding the sight of a driver. In the prior art, vehicles which are not hung with normal license plates but have temporary license plates posted cannot be accurately identified in an unattended parking lot, so that the vehicles cannot normally drive in and out of a parking lot, traffic jam risks are caused, and parking experience of vehicle owners is influenced.

Disclosure of Invention

The application provides a temporary license plate recognition method, a system, a device and a storage medium, which are used for recognizing a temporary license plate and improving the robustness of temporary license plate recognition.

The application provides a temporary license plate recognition method in a first aspect, which includes:

when a target vehicle is detected to enter a preset area, acquiring an image to be detected of the target vehicle;

inputting the image to be detected into a target detection model to obtain a target detection result, wherein the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

judging whether the target detection result only contains the first prediction frame;

if the target detection result is determined to not only contain the first prediction frame, judging whether the first prediction frame is located in the second prediction frame;

and if the first prediction frame is determined to be positioned outside the second prediction frame, determining the license plate of the target vehicle as a temporary license plate.

Optionally, after the determining whether the target detection result only includes the first prediction box, the method further includes:

and if the target detection result only contains the first prediction frame, determining that the license plate of the target vehicle is a temporary license plate.

Optionally, after the determining whether the first prediction box is located within the second prediction box, the method further includes:

if the first prediction frame is located in a second prediction frame, inputting the image content in the first prediction frame into a license plate classification model to obtain a license plate classification result, wherein the license plate classification result comprises a normal license plate and a temporary license plate;

and when the license plate classification result is a temporary license plate, determining that the license plate of the target vehicle is the temporary license plate.

Optionally, the method further includes:

and when the license plate classification result is a normal license plate, determining that the license plate of the target vehicle is a normal license plate.

Optionally, after determining that the license plate of the vehicle is a temporary license plate, the method further includes:

a no pass event is triggered.

Optionally, after determining that the license plate of the vehicle is a normal license plate, the method further includes:

a clear to pass event is triggered.

A second aspect of the present application provides a temporary license plate recognition system, including:

the device comprises an acquisition unit, a detection unit and a processing unit, wherein the acquisition unit is used for acquiring an image to be detected of a target vehicle when the target vehicle is detected to enter a preset area;

the detection classification unit is used for inputting the image to be detected into a target detection model to obtain a target detection result, the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

a first judgment unit, configured to judge whether the target detection result only includes the first prediction frame;

a second judgment unit, configured to, when the first judgment unit determines that the target detection result includes the first prediction frame, judge whether the first prediction frame is located within the second prediction frame;

a first determining unit, configured to determine that the license plate of the target vehicle is a temporary license plate when the second determining unit determines that the first prediction frame is located outside the second prediction frame.

Optionally, the first determining unit is further configured to:

and when the first judging unit determines that the target detection result only contains the first prediction frame, determining that the license plate of the target vehicle is a temporary license plate.

Optionally, the system further includes:

the input unit is used for inputting the image content in the first prediction frame into a license plate classification model to obtain a license plate classification result when the second judgment unit determines that the first prediction frame is positioned in a second prediction frame, and the license plate classification result comprises a normal license plate and a temporary license plate;

the first determination unit is further configured to:

and when the license plate classification result is a temporary license plate, determining that the license plate of the target vehicle is the temporary license plate.

Optionally, the system further includes:

and the second determining unit is used for determining the license plate of the target vehicle as a normal license plate when the license plate classification result is the normal license plate.

Optionally, the system further includes:

and the first triggering unit is used for triggering a traffic prohibition event when the first determining unit determines that the license plate of the target vehicle is a temporary license plate.

Optionally, the system further includes:

and the second triggering unit is used for triggering a traffic permission event when the second determining unit determines that the license plate of the target vehicle is a normal license plate.

A third aspect of the present application provides a temporary license plate recognition device, the device including:

the device comprises a processor, a memory, an input and output unit and a bus;

the processor is connected with the memory, the input and output unit and the bus;

the memory stores a program, and the processor calls the program to execute the temporary license plate recognition method according to any one of the first aspect and the first aspect.

A fourth aspect of the present application provides a computer-readable storage medium having a program stored thereon, where the program, when executed on a computer, performs the temporary license plate recognition method of any one of the first aspect and the first aspect.

According to the technical scheme, the method has the following advantages:

the image of the target vehicle is shot, the image is input into the trained target detection model, the license plate (first prediction frame) and the vehicle head (second prediction frame) in the image are detected and classified, and whether the license plate is a temporary license plate or not is judged by combining the detected relative positions of the license plate (first prediction frame) and the vehicle head (second prediction frame), so that the judgment of the temporary license plate on site is more robust, whether the temporary license plate vehicle appears on site or not can be accurately judged, the parking lot can perform special treatment on the temporary license plate vehicle, the vehicle jam risk is reduced, and the parking experience of a vehicle owner is improved.

Drawings

In order to more clearly illustrate the technical solutions in the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

Fig. 1 is a schematic flowchart illustrating an embodiment of a temporary license plate recognition method provided in the present application;

fig. 2 is a schematic flowchart of another embodiment of a temporary license plate recognition method provided in the present application;

fig. 3 is a schematic structural diagram of an embodiment of a temporary license plate recognition system provided in the present application;

fig. 4 is a schematic structural diagram of another embodiment of a temporary license plate recognition system provided in the present application;

fig. 5 is a schematic structural diagram of an embodiment of a temporary license plate recognition device provided by the present application.

Detailed Description

The application provides a temporary license plate recognition method, a system, a device and a storage medium, which are used for recognizing a temporary license plate and improving the robustness of temporary license plate recognition.

It should be noted that the temporary license plate recognition method provided by the application is applied to a parking lot system. For convenience of explanation, the system is taken as an implementation subject in the present application for illustration.

Referring to fig. 1, fig. 1 is a diagram illustrating an embodiment of a temporary license plate recognition method according to the present application, the method including:

101. when detecting that a target vehicle enters a preset area, acquiring an image to be detected of the target vehicle;

in a parking lot system, an image acquisition device is generally used to acquire an image of a vehicle entering or exiting a parking lot, and then a license plate number of the vehicle is identified by a license plate identification technology, so that subsequent parking lot services are executed according to the license plate number. The license plate recognition technology can stably extract and recognize text characters of normal license plates, but temporary license plates are posted inside vehicle windows, and due to other reasons such as light refraction, the extraction and recognition of the temporary license plates are unstable, and the situation of recognition failure often occurs, so that vehicles of the temporary license plates can not normally drive in or out of a parking lot, and traffic jam risks are caused.

In the application, when the system detects that a target vehicle enters the identification range of the image acquisition device, namely a preset area in the application, the image to be detected of the target vehicle is acquired in real time through the image acquisition device.

102. Inputting the image to be detected into a target detection model to obtain a target detection result, wherein the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

the definition of target detection and classification is that an image is input, and a specific position and a specific category of a target object in the image are detected through an algorithm. Through the target detection and classification algorithm, the specified characteristic objects in the image can be extracted and classified. The target detection algorithm based on the convolutional neural network utilizes the advantages of big data and GPU clusters, utilizes a large number of samples of real scenes to automatically learn through the neural network, and has the characteristics of high discrimination and strong robustness.

According to the method and the device, the vehicle license plate characteristics and the vehicle head characteristics in the image input into the model can be detected and classified through the target detection model obtained through training, specifically, the target detection model outputs the detection classification result of the vehicle license plate through the first prediction frame, and outputs the detection classification result of the vehicle head through the second prediction frame.

The system inputs the acquired image to be detected of the target vehicle into the target detection model, and obtains a target detection result, it should be noted that the target detection result may only include the first prediction frame or the second prediction frame (that is, only the license plate feature or only the vehicle head feature exists in the image to be detected), or may simultaneously include the first prediction frame and the second prediction frame (that is, both the license plate feature and the vehicle head feature exist in the image to be detected).

103. Judging whether the target detection result only contains the first prediction frame, if not, executing step 104;

the system judges whether the target detection result only contains a first prediction frame, namely whether the image to be detected only has the license plate feature, if the license plate feature exists, namely the license plate feature and the vehicle head feature exist at the same time, the step 104 is executed for further judgment.

104. Judging whether the first prediction frame is located in the second prediction frame, if not, executing step 105;

when the system determines that the first prediction frame and the second prediction frame exist in the target detection result at the same time, whether the first prediction frame is located in the second prediction frame is judged, namely when the system determines that the license plate feature and the vehicle head feature exist in the image to be detected at the same time, whether the feature range of the extracted license plate is located in the feature range of the vehicle head is further judged, and if not, the step 105 is executed.

105. And determining the license plate of the target vehicle as a temporary license plate.

And when the system determines that the first prediction frame in the target detection result is not positioned in the second prediction frame, namely when the system determines that the license plate feature range in the image to be detected is not positioned in the vehicle head feature range, determining that the license plate of the target vehicle is a temporary license plate.

According to the relevant regulations, vehicles not hanging normal license plates (e.g., newly purchased vehicles, etc.) need to be pasted with temporary license plates in order to travel on the road. The temporary license plate is a paper motor vehicle license plate which is used for granting the motor vehicle to temporarily run on the road and is also called as a temporary running license plate. Generally, the temporary license plate needs to be pasted on a front window of a vehicle, for example, the temporary license plate can be pasted on a position which does not affect the sight of a driver, such as the lower left corner or the lower right corner of the front window. Therefore, whether the license plate is a temporary license plate can be judged by judging the relative position of the first prediction frame (license plate characteristic) and the second prediction frame (vehicle head characteristic) in the target detection result. Specifically, when a first prediction frame and a second prediction frame exist in the target detection result at the same time, and the first prediction frame is not located in the second prediction frame, the license plate can be determined to be a temporary license plate.

In the embodiment, images of target vehicles are shot and input into a trained target detection model to detect and classify license plates (first prediction frames) and vehicle heads (second prediction frames) in the images, and then whether the license plates are temporary license plates or not is judged according to the detected relative positions of the license plates (first prediction frames) and the vehicle heads (second prediction frames), so that the judgment of the temporary license plates on site is more robust, whether the vehicles with the temporary license plates appear on site or not can be accurately judged, a parking lot can perform special treatment on the vehicles with the temporary license plates, the risk of traffic jam is reduced, and the parking experience of vehicle owners is improved.

Referring to fig. 2, fig. 2 is another embodiment of the temporary license plate recognition method provided in the present application, where the method includes:

201. when detecting that a target vehicle enters a preset area, acquiring an image to be detected of the target vehicle;

202. inputting the image to be detected into a target detection model to obtain a target detection result, wherein the target detection model is used for detecting and classifying the license plate and the vehicle head in the input image and outputting a detection classification result, the detection classification result comprises a first prediction frame and a second prediction frame, the first prediction frame is the detection classification result of the license plate in the input image, and the second prediction frame is the detection classification result of the vehicle head in the input image;

in this embodiment, steps 201 to 202 are similar to steps 101 to 102 of the previous embodiment, and are not described again here.

203. Judging whether the target detection result only contains the first prediction frame, if not, executing the step 204, and if so, directly executing the step 206;

the system judges whether the target detection result only contains a first prediction frame, namely whether the image to be detected only has the license plate feature, if the license plate feature exists, namely the license plate feature and the vehicle head feature exist at the same time, the step 204 is executed for further judgment. If the target detection result only contains the first prediction frame, that is, only the license plate feature exists in the image to be detected and no vehicle head feature exists, step 206 is directly executed to determine that the license plate of the target vehicle is a temporary license plate.

204. Judging whether the first prediction frame is located in the second prediction frame, if not, directly executing a step 206, and if so, executing a step 205;

when the system determines that the first prediction frame and the second prediction frame exist in the target detection result at the same time, whether the first prediction frame is located in the second prediction frame is judged, namely when the system determines that the license plate feature and the vehicle head feature exist in the image to be detected at the same time, whether the extracted license plate feature range is located in the vehicle head feature range is further judged, and if not, the step 206 is directly executed.

If the first prediction frame in the target detection result is located in the second prediction frame, it indicates that the license plate feature range is located in the vehicle head feature range, and then step 205 is executed to perform further determination.

205. Inputting the image content in the first prediction frame into a license plate classification model to obtain a license plate classification result;

if the first prediction frame is located in the second prediction frame in the target detection result, it is indicated that the license plate feature is located on the vehicle head feature, and at this time, the license plate may be a normal license plate, or the vehicle owner may stick a temporary license plate on the vehicle head position, so that further judgment is needed: the system inputs the image content in the first prediction frame, namely the license plate characteristics, into the license plate classification model and obtains a license plate classification result. And (4) the license plate classification result comprises a normal license plate and a temporary license plate, when the license plate classification result is the temporary license plate, the step 206 is executed, and when the license plate classification result is the normal license plate, the step 207 is executed.

It should be noted that the license plate classification model refers to a trained model capable of classifying a normal license plate and a temporary license plate, and the license plate classification model is used for judging whether a license plate image input into the model is a normal license plate or a temporary license plate.

206. Determining the license plate of the target vehicle as a temporary license plate and triggering a no-pass event;

when the system determines that the target detection result only contains the first prediction frame, determining that the license plate of the target vehicle is a temporary license plate;

when the system determines that the target detection result simultaneously contains a first prediction frame and a second prediction frame and determines that the first prediction frame is not positioned in the second prediction frame, determining that the license plate of the target vehicle is a temporary license plate;

when the system determines that the target detection result simultaneously comprises a first prediction frame and a second prediction frame and determines that the first prediction frame is positioned in the second prediction frame, inputting the license plate image in the first prediction frame into a license plate classification model, and when the license plate classification result output by the license plate classification model is a temporary license plate, determining that the license plate of the target vehicle is the temporary license plate.

And when the system determines that the license plate of the target vehicle is the temporary license plate, the target vehicle is not automatically released, corresponding information is reported, and the vehicle owner is prompted to enter the vehicle through card taking or code scanning and other possible modes.

207. And determining the license plate of the target vehicle as a normal license plate, and triggering a traffic permission event.

When the system determines that the target detection result simultaneously comprises a first prediction frame and a second prediction frame and determines that the first prediction frame is positioned in the second prediction frame, inputting the license plate image in the first prediction frame into a license plate classification model, and when the license plate classification result output by the license plate classification model is a normal license plate, determining that the license plate of the target vehicle is the normal license plate.

And when the system determines that the license plate of the target vehicle is a normal license plate, releasing the target vehicle according to the conventional parking lot service logic.

In the embodiment, an image of a target vehicle is shot, the image is input into a trained target detection model, so that a license plate (a first prediction frame) and a vehicle head (a second prediction frame) in the image are detected and classified, and whether the license plate is a temporary license plate is judged by combining the detected relative positions of the license plate (the first prediction frame) and the vehicle head (the second prediction frame), so that the judgment of the temporary license plate on site is more robust, whether the vehicle with the temporary license plate appears on site can be accurately judged, if the vehicle with the temporary license plate appears, the vehicle is not automatically released, but relevant information is reported or the vehicle owner is reminded to enter the site in other modes, thereby reducing the risk of traffic jam and improving the parking experience of the vehicle owner.

Referring to fig. 3, fig. 3 is a diagram illustrating an embodiment of a temporary license plate recognition system according to the present application, the system including:

the acquiring unit 301 is configured to acquire an image to be detected of a target vehicle when the target vehicle is detected to enter a preset area;

a detection classification unit 302, configured to input the image to be detected into a target detection model, so as to obtain a target detection result, where the target detection model is configured to detect and classify a license plate and a vehicle head in the input image, and output a detection classification result, where the detection classification result includes a first prediction frame and a second prediction frame, the first prediction frame is a detection classification result of the license plate in the input image, and the second prediction frame is a detection classification result of the vehicle head in the input image;

a first determining unit 303, configured to determine whether the target detection result only includes the first prediction frame;

a second determining unit 304, configured to determine whether the first prediction frame is located in the second prediction frame when the first determining unit 303 determines that the target detection result does not include the first prediction frame;

a first determining unit 305, configured to determine that the license plate of the target vehicle is a temporary license plate when the second determining unit 304 determines that the first prediction frame is outside the second prediction frame.

In the embodiment, images of target vehicles are shot and input into a trained target detection model to detect and classify license plates (first prediction frames) and vehicle heads (second prediction frames) in the images, and then whether the license plates are temporary license plates or not is judged according to the detected relative positions of the license plates (first prediction frames) and the vehicle heads (second prediction frames), so that the judgment of the temporary license plates on site is more robust, whether the vehicles with the temporary license plates appear on site or not can be accurately judged, a parking lot can perform special treatment on the vehicles with the temporary license plates, the risk of traffic jam is reduced, and the parking experience of vehicle owners is improved.

Referring to fig. 4, fig. 4 is a diagram illustrating another embodiment of a temporary license plate recognition system provided in the present application, where the system includes:

an obtaining unit 401, configured to obtain an image to be detected of a target vehicle when it is detected that the target vehicle enters a preset area;

a detection classification unit 402, configured to input the image to be detected into a target detection model, so as to obtain a target detection result, where the target detection model is configured to detect and classify a license plate and a vehicle head in the input image, and output a detection classification result, where the detection classification result includes a first prediction frame and a second prediction frame, the first prediction frame is a detection classification result of the license plate in the input image, and the second prediction frame is a detection classification result of the vehicle head in the input image;

a first determining unit 403, configured to determine whether the target detection result only includes the first prediction frame;

a second determining unit 404, configured to determine whether the first prediction frame is located in the second prediction frame when the first determining unit 403 determines that the target detection result includes the first prediction frame;

a first determining unit 405, configured to determine that the license plate of the target vehicle is a temporary license plate when the second determining unit 404 determines that the first prediction frame is located outside the second prediction frame.

Further, the first determining unit 405 is further configured to:

when the first determining unit 403 determines that the target detection result only includes the first prediction frame, it determines that the license plate of the target vehicle is a temporary license plate.

Further, the system further comprises:

an input unit 406, configured to input, when the second determining unit 404 determines that the first prediction frame is located in the second prediction frame, the image content in the first prediction frame to a license plate classification model to obtain a license plate classification result, where the license plate classification result includes a normal license plate and a temporary license plate;

the first determination unit 405 is further configured to:

and when the license plate classification result is a temporary license plate, determining that the license plate of the target vehicle is the temporary license plate.

Further, the system further comprises:

the second determining unit 407 is configured to determine that the license plate of the target vehicle is a normal license plate when the license plate classification result is the normal license plate.

Further, the system further comprises:

the first triggering unit 408 is configured to trigger a pass prohibition event when the first determining unit determines that the license plate of the target vehicle is a temporary license plate.

Further, the system further comprises:

a second triggering unit 409, configured to trigger a pass-allowing event when the second determining unit determines that the license plate of the target vehicle is a normal license plate.

In the system of this embodiment, the functions of each unit correspond to the steps in the method embodiment shown in fig. 2, and are not described herein again.

Referring to fig. 5, fig. 5 is a diagram illustrating an embodiment of a temporary license plate recognition device according to the present application, where the temporary license plate recognition device includes:

a processor 501, a memory 502, an input/output unit 503, and a bus 504;

the processor 501 is connected with the memory 502, the input/output unit 503 and the bus 504;

the memory 502 holds a program that the processor 501 calls to perform any of the temporary license plate recognition methods described above.

The present application also relates to a computer-readable storage medium having a program stored thereon, wherein the program, when executed on a computer, causes the computer to perform any of the above-described temporary license plate recognition methods.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.