Service execution method and device, storage medium and electronic equipment

Abstract

The invention discloses a service execution method and device, a storage medium and electronic equipment. The method comprises the following steps: firstly, acquiring a target video, determining a frame rate of the target video, determining a frame rate difference value between the frame rate of the target video and a preset target frame rate, and inputting the target video and the frame rate difference value into a preset image model, so that the image model determines a size relationship between the frame rate of the target video and the target frame rate according to the frame rate difference value; and determining different adjustment frames for adjusting the target video according to the size relationship, performing frame rate adjustment on the target video according to the adjustment frames to obtain an adjusted target video, and executing a service according to the adjusted target video.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, storage medium and electronic device for executing a service. Background Art

[0002] As one of the current mainstream carriers of information expression, video has played a great role in all walks of life. Video is essentially formed by a series of continuous static images changing at high speed, and the number of static images that change per second is the frame rate of the video.

[0003] In many actual businesses, you may need to use videos with a specific frame rate to perform the business. For example, in businesses such as 3D reconstruction and motion capture using videos, a video with a frame rate that is too high will increase the processing cost of the video. Therefore, these businesses often need to use videos with a lower frame rate. In some operations and promotional businesses, there may be a need to show videos to users. In this process, videos with a higher frame rate are often needed to improve the user's viewing experience.

[0004] However, the frame rate of the target video actually obtained in the business may not meet the business requirements. Therefore, it is necessary to adjust the frame rate of the target video obtained, remove some frames of the target video with too high a frame rate, or insert intermediate frames into the target video with too low a frame rate to obtain the target video that meets the business requirements.

[0005] However, the effects of existing methods for adjusting video frame rate are not satisfactory. For example, in existing methods for removing frames, frames in the video are generally evenly removed based on the total number of frames in the video. This method may cause higher-quality frame images in the video to be removed, while lower-quality blurred frames are retained. In services that require high video quality, such as 3D reconstruction and motion capture, the effect is poor. In existing methods for inserting frames, frames that are the same as the previous frame are often inserted into the video. This method of adjusting the video frame rate may cause problems such as video jerking, which may affect the user's viewing experience in services that need to display videos to users.

[0006] Therefore, how to adjust the frame rate of the video to better perform business is an issue that needs to be solved urgently. Summary of the invention

[0007] This specification provides a method, device, storage medium and electronic device for executing a service, so as to partially solve the above problems existing in the prior art.

[0008] This manual adopts the following technical solutions:

[0009] This specification provides a method for executing a service, including:

[0010] Get the target video;

[0011] Determining a frame rate of the target video, and determining a frame rate difference between the frame rate of the target video and a preset target frame rate;

[0012] Inputting the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and performs frame rate adjustment on the target video according to the adjustment frame to obtain an adjusted target video;

[0013] The service is executed according to the adjusted target video.

[0014] Optionally, the step of inputting the target video and the frame rate difference into a preset image model so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusting the frame rate of the target video according to the adjustment frame to obtain the adjusted target video specifically includes:

[0015] The target video and the frame rate difference are input into a preset image model, so that when the image model determines that the frame rate of the target video is greater than the target frame rate based on the frame rate difference, blurred frames that do not meet the preset standards are identified from the target video as adjustment frames for adjusting the target video, and the adjustment frames are removed from the target video to obtain an adjusted target video.

[0016] Optionally, the step of identifying blurry frames that do not meet a preset standard from the target video specifically includes:

[0017] For each video frame included in the target video, determining whether the clarity at the image edge of the video frame is not less than a preset clarity;

[0018] If it is determined that the clarity at the edge of the image of the video frame is lower than the preset clarity, the video frame is determined as a blurred frame.

[0019] Optionally, the step of removing the adjusted frame from the target video to obtain an adjusted target video specifically includes:

[0020] Determining whether the number of blurry frames is not less than the frame rate difference;

[0021] If it is determined that the number of the blurred frames is less than the frame rate difference, the supplementary frames are selected from the other video frames in the target video except the blurred frames, with the sum of the number of the blurred frames and the number of supplementary frames selected from the target video being not less than the frame rate difference as a constraint condition;

[0022] The blurred frame and the supplementary frame are removed from the target video to obtain an adjusted target video.

[0023] Optionally, the step of selecting the supplementary frames from other video frames in the target video except the blurry frames, with the sum of the number of the blurry frames and the number of supplementary frames selected from the target video being not less than the frame rate difference as a constraint condition, specifically includes:

[0024] Taking the sum of the number of the blurred frames and the number of supplementary frames screened from the target video as a constraint condition that is not less than the frame rate difference, screening out initial supplementary frames from other video frames in the target video except the blurred frames;

[0025] Eliminating the initial supplementary frame from the target video to obtain a video after elimination;

[0026] Inputting the removed video into a feature extraction layer in the image model to obtain video features of the removed video, and inputting the video features into a generation layer in the image model to obtain a video generated based on the video features;

[0027] According to the generated video, determine whether the initial supplementary frame meets the preset conditions, and when it is determined that the initial supplementary frame does not meet the preset conditions, re-filter the initial supplementary frame from other video frames in the target video except the blurred frame based on the constraint conditions, and input the eliminated video obtained by re-filtering the initial supplementary frame into the feature extraction layer until the initial supplementary frame that meets the preset conditions is obtained, and the initial supplementary frame that meets the preset conditions is used as the determined supplementary frame.

[0028] Optionally, the step of judging whether the initial supplementary frame meets a preset condition according to the generated video specifically includes:

[0029] For each initial supplementary frame, if it is determined that the generated video includes the initial supplementary frame, it is determined that the initial supplementary frame does not meet the preset condition.

[0030] Optionally, the step of inputting the target video and the frame rate difference into a preset image model so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusting the frame rate of the target video according to the adjustment frame to obtain the adjusted target video specifically includes:

[0031] The target video and the frame rate difference are input into a preset image model, so that when the image model determines that the frame rate of the target video is less than the target frame rate based on the frame rate difference, a number of intermediate frames are generated based on the frame rate difference as adjustment frames for adjusting the target video, and the adjustment frames are inserted into the target video to obtain the adjusted target video.

[0032] This specification provides a device for executing a service, including:

[0033] An acquisition module, used to acquire a target video;

[0034] A determination module, used to determine the frame rate of the target video, and determine a frame rate difference between the frame rate of the target video and a preset target frame rate;

[0035] A processing module, configured to input the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain an adjusted target video;

[0036] An execution module is used to execute a service according to the adjusted target video.

[0037] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for executing the above-mentioned service is implemented.

[0038] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned service execution method when executing the program.

[0039] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects:

[0040] In the method for executing a service provided in the present specification, a target video is first obtained, the frame rate of the target video is determined, and the frame rate difference between the frame rate of the target video and a preset target frame rate is determined. The target video and the frame rate difference are input into a preset image model, so that when the image model determines that the frame rate of the target video is greater than the target frame rate based on the frame rate difference, blurred frames that do not meet the preset standards are identified from the target video as adjustment frames for adjusting the target video, and the adjustment frames are removed from the target video to obtain the adjusted target video, or when the image model determines that the frame rate of the target video is less than the target frame rate based on the frame rate difference, a number of intermediate frames are generated based on the frame rate difference as adjustment frames for adjusting the target video, and the adjustment frames are inserted into the target video to obtain the adjusted target video, and finally the service is executed based on the adjusted target video.

[0041] It can be seen from the above method that this manual determines whether the target video needs to remove frames or insert frames through a preset image model, and determines the adjustment frames used to adjust the target video in different situations, which can meet the video frame rate adjustment needs of various businesses. On this basis, the frame rate of the target video is adjusted according to the adjustment frames to obtain the adjusted target video, and the adjusted target video can better perform the business. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings:

[0043] Figure 1 A flowchart of a method for executing a service provided in this specification;

[0044] Figure 2 A detailed schematic diagram of a frame rate adjustment provided in this specification;

[0045] Figure 3 A schematic diagram of a device for executing a service provided in this specification;

[0046] Figure 4 This manual provides a kind of Figure 1 Schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0048] With the rapid development of the Internet, video, as an excellent carrier of information expression, has played a huge role in more and more industries.

[0049] However, different businesses may have different requirements for video frame rates. For example, in businesses such as 3D reconstruction and motion capture using video, a high frame rate will increase the processing cost of the video. Therefore, these businesses often need to use videos with lower frame rates. In some operations and promotional businesses, there may be a need to show videos to users. In this process, videos with higher frame rates are often needed to improve the user experience.

[0050] When the frame rate of the target video actually obtained in the business does not meet the business requirements, it is often necessary to adjust the frame rate of the video.

[0051] However, the effects of existing methods for adjusting video frame rate are not satisfactory. For example, in existing methods for removing frames, frames in the video are generally evenly removed based on the total number of frames in the video. This method may cause higher-quality frame images in the video to be removed, while lower-quality blurred frames are retained. In services that require high video quality, such as 3D reconstruction and motion capture, the effect is poor. In existing methods for inserting frames, frames that are the same as the previous frame are often inserted into the video. This method of adjusting the video frame rate may cause problems such as video jerking, which may affect the user's viewing experience in services that need to display videos to users.

[0052] Based on this, the present specification provides a method for executing a business, which obtains a target video, determines the frame rate of the target video, and determines the frame rate difference between the frame rate of the target video and a preset target frame rate, and inputs the target video and the frame rate difference into a preset image model so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain an adjusted target video, and finally executes the business according to the adjusted target video.

[0053] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0054] Figure 1 A flowchart of a method for executing a service provided in this specification includes the following steps:

[0055] S101: Acquire a target video.

[0056] In this specification, the execution subject of the method for implementing business execution can be a designated device such as a server, or a terminal device such as a desktop computer or a laptop computer, or a client installed in a terminal device. For the sake of ease of description, this specification only takes the server as the execution subject as an example to illustrate a business execution method provided in this specification.

[0057] The server may obtain a target video, wherein the target video is a video required in the process of executing a service, but the frame rate of the target video does not meet the video frame rate requirement of the service.

[0058] S102: Determine the frame rate of the target video, and determine a frame rate difference between the frame rate of the target video and a preset target frame rate.

[0059] The server can determine the frame rate of the acquired target video and determine the frame rate difference between the frame rate of the target video and the preset target frame rate. The preset target frame rate is a frame rate that meets the service video frame rate requirement, which can be determined according to actual needs, and the specific value is not specifically limited here.

[0060] S103: Input the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain an adjusted target video.

[0061] The server can input the target video and the frame rate difference into a preset image model, so that the image model determines the adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain the adjusted target video.

[0062] Specifically, the image model can determine the relationship between the frame rate of the target video and the target frame rate based on the frame rate difference, and when it is determined that the frame rate of the target video is greater than the target frame rate, identify blurred frames that do not meet preset standards from the target video as adjustment frames for adjusting the target video, and remove the adjustment frames from the target video to obtain the adjusted target video.

[0063] In the process of identifying blurred frames that do not meet the preset standards from the target video, the image model can determine, for each video frame contained in the target video, whether the clarity at the image edge of the video frame is not lower than the preset clarity; if it is determined that the clarity at the image edge of the video frame is lower than the preset clarity, the video frame is determined to be a blurred frame.

[0064] It should be noted that among all the video frames contained in the target video, the number of blurry frames identified by the image model may be lower than the frame rate difference between the target video frame rate and the preset target frame rate. In this way, even if all the blurry frames contained in the target video are removed, the frame rate of the target video after removal still cannot reach the target frame rate. Therefore, it is also necessary to determine whether the number of blurry frames is not less than the frame rate difference, and when the number of blurry frames is less than the frame rate difference, determine additional supplementary frames in the target video for removal so that the frame rate of the target video after removal reaches the target frame rate.

[0065] Specifically, the image model can determine whether the number of blurred frames contained in the target video is not less than the frame rate difference. If it is determined that the number of blurred frames is less than the frame rate difference, the supplementary frames are screened out from the video frames other than the blurred frames in the target video, with the sum of the number of blurred frames and the number of supplementary frames screened out from the target video being not less than the frame rate difference as a constraint condition.

[0066] In order to make the target video as smooth as possible after elimination, the supplementary frames selected in the target video cannot carry key information, and the supplementary frames cannot be gathered in the same video segment. To achieve this goal, the image model can use the number of blurred frames and the number of supplementary frames selected from the target video as a constraint condition that the sum of the number of blurred frames and the number of supplementary frames selected from the target video is not less than the frame rate difference, and select the initial supplementary frames from the other video frames in the target video except the blurred frames, and eliminate the initial supplementary frames from the target video to obtain the eliminated video.

[0067] The server can input the removed video into the feature extraction layer in the image model to obtain the video features of the removed video, and input the video features into the generation layer in the image model to obtain the video generated based on the video features.

[0068] It should be noted that the above-mentioned removed video is the target video with the initial supplementary frame removed, and the above-mentioned image model can extract the video features of the removed video and generate a video based on the video features. Among them, the feature extraction layer of the image model is equivalent to an encoder, and the generation layer is equivalent to a decoder. When the image model receives the input removed video, the feature extraction layer can extract the video features of the removed video and input the video features into the generation layer in the image model to generate a video. The image model is equivalent to restoring the removed video. The generated video may contain the removed frame images compared to the removed video.

[0069] That is to say, the above-mentioned image model can restore the video after elimination to obtain a generated video that is closer to the target video. On this basis, if the video generated by the above-mentioned model contains the eliminated initial supplementary frame, it means that the eliminated initial supplementary frame contains key information and cannot be used as the eliminated video frame. Correspondingly, if the video generated by the above-mentioned model does not contain the eliminated initial supplementary frame, it means that the eliminated initial supplementary frame has little impact on the target video and can be used as the eliminated video frame.

[0070] The above-mentioned image model can use an existing deep learning model that can achieve the above-mentioned effect, and can be trained on a preset data set to obtain an image model that can achieve the above-mentioned effect. For example, the server can obtain a preset data set, which includes a training video and a training video with some video frames removed, and input the training video with some video frames removed into the image model to be trained, so that the image model to be trained can restore the training video with some video frames removed to generate a new video, and train the image model to be trained with the goal of minimizing the deviation between the generated new video and the training video to obtain a trained image model. The training video may not contain any redundant image frames, and all frame images contained in the training video may be video frames containing key information, and the fluency of the training video is relatively high.

[0071] On the basis of the above, the image model can judge whether the initial supplementary frame meets the preset conditions according to the generated video, and when it is determined that the initial supplementary frame does not meet the preset conditions, the initial supplementary frame is re-screened from other video frames in the target video except the blurred frame with the constraint conditions, and the removed video obtained by re-screening the initial supplementary frame is input into the feature extraction layer until the initial supplementary frame that meets the preset conditions is obtained, and the initial supplementary frame that meets the preset conditions is used as the determined supplementary frame. Among them, for each initial supplementary frame, if it is determined that the generated video contains the initial supplementary frame, it is determined that the initial supplementary frame does not meet the preset conditions.

[0072] In this way, if the image model determines that the initial supplementary frame does not meet the preset conditions based on the generated video, it means that the initial supplementary frame determined this time will affect the smoothness of the target video, that is, the initial supplementary frame determined this time contains key information and cannot be used as the image frame to be eliminated. Therefore, the image model can re-select the initial supplementary frame from other video frames in the target video except the blurred frame based on the constraint conditions, and input the eliminated video obtained by re-selecting the initial supplementary frame into the feature extraction layer until the initial supplementary frame that meets the preset conditions is obtained, and the initial supplementary frame that meets the preset conditions is used as the determined supplementary frame. For the initial supplementary frame that meets the preset conditions, the initial supplementary frame does not contain key information and can be used as the eliminated image frame. In this way, the image model can directly use the initial supplementary frame that meets the preset conditions as the supplementary frame, and eliminate the blurred frame and supplementary frame contained in the target video to obtain the adjusted target video.

[0073] After determining the blurred frames and the supplementary frames in the target video, the image model can remove the blurred frames and the supplementary frames from the target video to obtain an adjusted target video.

[0074] Furthermore, when the image model determines that the frame rate of the target video is less than the target frame rate, the image model can generate several intermediate frames according to the frame rate difference as adjustment frames for adjusting the target video, and insert the adjustment frames into the target video to obtain the adjusted target video.

[0075] Specifically, the image model can determine the number of intermediate frames that need to be inserted into the target video according to the frame rate difference, and generate a corresponding number of intermediate frames according to the target video as adjustment frames for adjusting the target video, and insert the adjustment frames into the target video to obtain the adjusted target video. The image model can generate an intermediate frame between any two consecutive image frames in the target video.

[0076] S104: Execute a service according to the adjusted target video.

[0077] The server can execute the service according to the adjusted target video.

[0078] For example, in a 3D reconstruction service, if the frame rate of the target video actually obtained in the service is too high and cannot meet the service requirements, the server can remove some image frames in the target video according to the method provided in this specification, so as to perform the service based on the removed target video. For another example, in a private domain operation service, it is necessary to upload a target video to be displayed to the user, but the frame rate of the target video actually obtained is too low, which may affect the user's viewing experience. In this case, the server can interpolate the target video according to the method provided in this specification, so as to perform the service based on the interpolated target video.

[0079] In order to describe the solution in this specification in more detail, this specification also provides a detailed schematic diagram of frame rate adjustment, such as Figure 2 shown.

[0080] Figure 2 A detailed schematic diagram of a frame rate adjustment provided in this specification;

[0081] from Figure 2 It can be seen from the specification that when adjusting the frame rate, the server can obtain the target video and determine the frame rate difference between the target video and the preset target frame rate, and input the target video and the frame rate difference into the preset image model, so that the image model determines the frame rate adjustment operation required for the target video according to the frame rate difference. When the frame rate of the target video is greater than the target frame rate, the blurred frames and supplementary frames contained in the target video are determined and eliminated in the target video. When the frame rate of the target video is less than the target frame rate, a number of intermediate frames are generated according to the target video, and the intermediate frames are inserted into the target video to finally obtain the adjusted target video.

[0082] It can be seen from the above method that this specification can determine that the frame rate of the target video is greater than the target frame rate based on the frame rate difference between the frame rate of the target video and the preset target frame rate, identify blurred frames that do not meet the preset standards from the target video as adjustment frames for adjusting the target video, and remove the adjustment frames from the target video to obtain the adjusted target video, or when it is determined that the frame rate of the target video is less than the target frame rate based on the frame rate difference, generate several intermediate frames based on the frame rate difference as adjustment frames for adjusting the target video, and insert the adjustment frames into the target video to obtain the adjusted target video, thereby adjusting the frame rate of the target video in a targeted manner according to the video frame rate requirements of different businesses, and finally obtaining a target video with a frame rate that meets the business requirements, so as to better execute the business.

[0083] At the same time, during the process of removing frames, this manual will identify blurred frames and supplementary frames in the target video, and give priority to removing blurred frames and supplementary frames to ensure that the removed frame images will not affect the smoothness of the target video, and ensure that the removed frame images will not contain key information, thereby improving the quality of the adjusted target video to a certain extent.

[0084] The above are one or more methods for implementing service execution in this specification. Based on the same idea, this specification also provides corresponding service execution devices such as Figure 3 shown.

[0085] Figure 3 A schematic diagram of a device for executing a service provided in this specification includes:

[0086] An acquisition module 301 is used to acquire a target video;

[0087] A determination module 302 is used to determine the frame rate of the target video and determine a frame rate difference between the frame rate of the target video and a preset target frame rate;

[0088] The processing module 303 is used to input the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain an adjusted target video;

[0089] The execution module 304 is used to execute a service according to the adjusted target video.

[0090] Optionally, the processing module 303 is specifically used to input the target video and the frame rate difference into a preset image model, so that when the image model determines that the frame rate of the target video is greater than the target frame rate based on the frame rate difference, blurred frames that do not meet preset standards are identified from the target video as adjustment frames for adjusting the target video, and the adjustment frames are removed from the target video to obtain an adjusted target video.

[0091] Optionally, the processing module 303 is specifically used to determine, for each video frame contained in the target video, whether the clarity at the image edge of the video frame is not lower than a preset clarity; if it is determined that the clarity at the image edge of the video frame is lower than the preset clarity, the video frame is determined to be a blurred frame.

[0092] Optionally, the processing module 303 is specifically used to determine whether the number of the blurred frames is not less than the frame rate difference; if it is determined that the number of the blurred frames is less than the frame rate difference, the supplementary frames are screened out from other video frames in the target video except the blurred frames, with the sum of the number of the blurred frames and the number of supplementary frames screened out from the target video being not less than the frame rate difference as a constraint condition; the blurred frames and the supplementary frames are removed from the target video to obtain an adjusted target video.

[0093] Optionally, the processing module 303 is specifically configured to select an initial supplementary frame from other video frames in the target video except the blurred frame, with the sum of the number of the blurred frames and the number of supplementary frames selected from the target video being not less than the frame rate difference as a constraint condition;

[0094] Eliminating the initial supplementary frame from the target video to obtain a video after elimination;

[0095] Inputting the removed video into a feature extraction layer in the image model to obtain video features of the removed video, and inputting the video features into a generation layer in the image model to obtain a video generated based on the video features;

[0096] According to the generated video, judging whether the initial supplementary frame satisfies a preset condition, and when it is determined that the initial supplementary frame does not satisfy the preset condition, re-screening the initial supplementary frame from other video frames in the target video except the blurred frame according to the constraint condition, and inputting the eliminated video obtained by re-screening the initial supplementary frame into the feature extraction layer until the initial supplementary frame satisfying the preset condition is obtained, and the initial supplementary frame satisfying the preset condition is used as the determined supplementary frame;

[0097] Optionally, the processing module 303 is specifically configured to, for each initial supplementary frame, if it is determined that the generated video includes the initial supplementary frame, determine that the initial supplementary frame does not meet the preset condition.

[0098] Optionally, the processing module 303 is specifically used to input the target video and the frame rate difference into a preset image model, so that when the image model determines that the frame rate of the target video is less than the target frame rate according to the frame rate difference, a plurality of intermediate frames are generated according to the frame rate difference as adjustment frames for adjusting the target video, and the adjustment frames are inserted into the target video to obtain the adjusted target video.

[0099] This specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 A method for executing a business is provided.

[0100] This specification also provides a corresponding Figure 1 A schematic diagram of the electronic device. Figure 4 shown.

[0101] Figure 4 This manual provides an application for Figure 1 Schematic diagram of the structure of an electronic device.

[0102] As shown in the figure, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 The method of executing the business.

[0103] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the executor of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0104] For the improvement of a technology, it can be clearly distinguished whether it is a hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or a software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming themselves, without having to ask chip manufacturers to design and produce dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0105] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0106] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0107] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0108] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0109] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0112] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0113] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0114] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0115] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0116] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0118] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0119] The above description is only an embodiment of the present specification and is not intended to limit the present specification. For those skilled in the art, the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A method for executing a business, It is characterized in that include: Get the target video; Determining a frame rate of the target video, and determining a frame rate difference between the frame rate of the target video and a preset target frame rate; Inputting the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and performs frame rate adjustment on the target video according to the adjustment frame to obtain an adjusted target video; The service is executed according to the adjusted target video.

2. The method according to claim 1, It is characterized in that The step of inputting the target video and the frame rate difference into a preset image model so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusting the frame rate of the target video according to the adjustment frame to obtain the adjusted target video specifically includes: The target video and the frame rate difference are input into a preset image model, so that when the image model determines that the frame rate of the target video is greater than the target frame rate based on the frame rate difference, blurred frames that do not meet the preset standards are identified from the target video as adjustment frames for adjusting the target video, and the adjustment frames are removed from the target video to obtain an adjusted target video.

3. The method according to claim 2, It is characterized in that The step of identifying blurry frames that do not meet the preset standard from the target video specifically includes: For each video frame included in the target video, determining whether the clarity at the edge of the image of the video frame is not less than a preset clarity; If it is determined that the clarity at the edge of the image of the video frame is lower than the preset clarity, the video frame is determined as a blurred frame.

4. The method according to claim 2, It is characterized in that The step of removing the adjusted frame from the target video to obtain the adjusted target video specifically includes: Determining whether the number of blurry frames is not less than the frame rate difference; If it is determined that the number of the blurred frames is less than the frame rate difference, the supplementary frames are selected from the other video frames in the target video except the blurred frames, with the sum of the number of the blurred frames and the number of supplementary frames selected from the target video being not less than the frame rate difference as a constraint condition; The blurred frame and the supplementary frame are removed from the target video to obtain an adjusted target video.

5. The method according to claim 4, It is characterized in that The step of selecting the supplementary frames from other video frames in the target video except the blurry frames, with the sum of the number of the blurry frames and the number of supplementary frames selected from the target video being not less than the frame rate difference as a constraint condition, specifically comprises: Taking the sum of the number of the blurred frames and the number of supplementary frames screened from the target video as a constraint condition that is not less than the frame rate difference, screening out initial supplementary frames from other video frames in the target video except the blurred frames; Eliminating the initial supplementary frame from the target video to obtain a video after elimination; Inputting the removed video into a feature extraction layer in the image model to obtain video features of the removed video, and inputting the video features into a generation layer in the image model to obtain a video generated based on the video features; According to the generated video, determine whether the initial supplementary frame meets the preset conditions, and when it is determined that the initial supplementary frame does not meet the preset conditions, re-filter the initial supplementary frame from other video frames in the target video except the blurred frame based on the constraint conditions, and input the eliminated video obtained by re-filtering the initial supplementary frame into the feature extraction layer until the initial supplementary frame that meets the preset conditions is obtained, and the initial supplementary frame that meets the preset conditions is used as the determined supplementary frame.

6. The method according to claim 5, It is characterized in that The step of judging whether the initial supplementary frame meets a preset condition according to the generated video specifically includes: For each initial supplementary frame, if it is determined that the generated video includes the initial supplementary frame, it is determined that the initial supplementary frame does not meet the preset condition.

7. The method according to claim 1, It is characterized in that The step of inputting the target video and the frame rate difference into a preset image model so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusting the frame rate of the target video according to the adjustment frame to obtain the adjusted target video specifically includes: The target video and the frame rate difference are input into a preset image model, so that when the image model determines that the frame rate of the target video is less than the target frame rate based on the frame rate difference, a number of intermediate frames are generated based on the frame rate difference as adjustment frames for adjusting the target video, and the adjustment frames are inserted into the target video to obtain the adjusted target video.

8. A device for executing a service, It is characterized in that include: An acquisition module, used to acquire a target video; A determination module, used to determine the frame rate of the target video, and determine a frame rate difference between the frame rate of the target video and a preset target frame rate; A processing module, configured to input the target video and the frame rate difference into a preset image model, so that the image model determines an adjustment frame for adjusting the target video according to the frame rate difference, and adjusts the frame rate of the target video according to the adjustment frame to obtain an adjusted target video; An execution module is used to execute a service according to the adjusted target video.

9. A computer-readable storage medium, It is characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

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