Video processing method and device, storage medium and equipment

Abstract

The invention discloses a video processing method and device, a storage medium and equipment. The method comprises the following steps: acquiring an initial video and a video auditing request corresponding to the initial video through a human-computer interaction interface; sending the initial video and a video auditing request to a server, so that the server analyzes the video content of the initial video in response to the video auditing request to obtain optimization suggestion information for the initial video, the optimization suggestion information comprises an optimization suggestion of target video content under a target dimension which needs to be optimized and corresponds to a target purpose of the initial video; and obtaining optimization suggestion information for the initial video sent by the server, and displaying the optimization suggestion information for the initial video on the human-computer interaction interface. According to the invention, effective optimization suggestion information can be provided for the initial video created by the user, so that the user is guided to create a better video, and the efficiency and quality of video creation are improved.

Description

Technical Field

[0001] The present application relates to the field of video processing technology, and in particular to a video processing method, device, storage medium and equipment. Background Art

[0002] Currently, users can easily create videos in some video production software, but different users have different levels, especially novice users, the videos they create may have some problems. In the related technology, they can mainly refer to the video production tutorials provided by the video production software to create videos, but the video production tutorials in the related technology are universal and undifferentiated instructions, which may not meet the needs of users and reduce the efficiency of creating videos. Summary of the invention

[0003] The embodiments of the present application provide a video processing method, apparatus, storage medium and device, which can provide effective optimization suggestion information for the initial video created by the user, so as to guide the user to create a better quality video, thereby improving the efficiency and quality of video creation.

[0004] On the one hand, an embodiment of the present application provides a video processing method, the method comprising:

[0005] Obtaining an initial video and a video review request corresponding to the initial video through a human-computer interaction interface;

[0006] Sending the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under target dimensions to be optimized corresponding to the target purpose of the initial video;

[0007] The optimization suggestion information for the initial video sent by the server is obtained, and the optimization suggestion information for the initial video is displayed on the human-computer interaction interface.

[0008] On the other hand, an embodiment of the present application provides a video processing method, the method comprising:

[0009] Receiving an initial video sent by a terminal device and a video review request corresponding to the initial video;

[0010] In response to the video review request, analyzing the video content of the initial video to obtain optimization suggestion information for the initial video, the optimization suggestion information including optimization suggestions for target video content under target dimensions to be optimized corresponding to the target purpose of the initial video;

[0011] Sending optimization suggestion information for the initial video to the terminal device so that the terminal device displays the optimization suggestion information for the initial video on a human-computer interaction interface.

[0012] On the other hand, an embodiment of the present application provides a video processing device, the device comprising:

[0013] An acquisition unit, configured to acquire an initial video and a video review request corresponding to the initial video through a human-computer interaction interface;

[0014] A first sending unit is used to send the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to a target purpose of the initial video;

[0015] A display unit is used to obtain the optimization suggestion information for the initial video sent by the server, and to display the optimization suggestion information for the initial video on the human-computer interaction interface.

[0016] On the other hand, an embodiment of the present application provides a video processing device, the device comprising:

[0017] A receiving unit, configured to receive an initial video sent by a terminal device and a video review request corresponding to the initial video;

[0018] A processing unit, configured to analyze the video content of the initial video in response to the video review request, and obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to a target purpose of the initial video;

[0019] The second sending unit is used to send optimization suggestion information for the initial video to the terminal device, so that the terminal device displays the optimization suggestion information for the initial video on the human-computer interaction interface.

[0020] On the other hand, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the video processing method described in any of the above embodiments.

[0021] On the other hand, an embodiment of the present application provides a computer device, which includes a processor and a memory, wherein a computer program is stored in the memory, and the processor is used to execute the video processing method described in any of the above embodiments by calling the computer program stored in the memory.

[0022] The embodiment of the present application obtains the initial video and the video review request corresponding to the initial video through the human-computer interaction interface; sends the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request, and obtains optimization suggestion information for the initial video, the optimization suggestion information including optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video; obtains the optimization suggestion information for the initial video sent by the server, and displays the optimization suggestion information for the initial video on the human-computer interaction interface. The embodiment of the present application can provide effective optimization suggestion information for the initial video created by the user, so as to guide the user to create a better quality video, thereby improving the efficiency and quality of video creation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A schematic diagram of the structure of a video processing system provided in an embodiment of the present application.

[0025] Figure 2 A first flow chart of a video processing method provided in an embodiment of the present application.

[0026] Figure 3 A schematic diagram of a first application scenario of the video processing method provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of a second application scenario of the video processing method provided in an embodiment of the present application.

[0028] Figure 5 A schematic diagram of a third application scenario of the video processing method provided in an embodiment of the present application.

[0029] Figure 6 A schematic diagram of a fourth application scenario of the video processing method provided in an embodiment of the present application.

[0030] Figure 7 A schematic diagram of a fifth application scenario of the video processing method provided in an embodiment of the present application.

[0031] Figure 8 A schematic diagram of a sixth application scenario of the video processing method provided in an embodiment of the present application.

[0032] Fig. 9A schematic diagram of the seventh application scenario of the video processing method provided in an embodiment of the present application.

[0033] Fig.10 A schematic diagram of an eighth application scenario of the video processing method provided in an embodiment of the present application.

[0034] Fig.11 A ninth application scenario schematic diagram of the video processing method provided in an embodiment of the present application.

[0035] Fig.12 A schematic diagram of the tenth application scenario of the video processing method provided in an embodiment of the present application.

[0036] Fig.13 A second flow chart of the video processing method provided in an embodiment of the present application.

[0037] Fig.14 A first structural schematic diagram of a video processing device provided in an embodiment of the present application.

[0038] Fig.15 A second structural diagram of the video processing device provided in an embodiment of the present application.

[0039] Fig.16 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0041] The embodiments of the present application provide a video processing method, apparatus, storage medium and device. Specifically, the video processing method of the embodiments of the present application can be executed by a terminal device or by a server. Among them, the computer device can be a terminal device or a server. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart TV, a smart speaker, a wearable smart device, a smart car terminal and other devices. The terminal device can also include a client, which can be a video client, a browser client or an instant messaging client, etc. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0042] The embodiments of the present application can be applied to various application scenarios such as video production and video review.

[0043] Please refer to Figure 1 , Figure 1 The video processing system provided in the embodiment of the present application is a schematic diagram of the structure of the video processing system. The video processing system includes a terminal device 10 and a server 20, etc. The terminal device 10 and the server 20 are connected via a network, such as a wired or wireless network connection.

[0044] The terminal device 10 can be used to display a graphical user interface. The terminal is used to interact with the user through the graphical user interface, such as downloading and installing the corresponding client through the terminal and running it, such as calling the corresponding applet and running it, such as logging into the website to present the corresponding graphical user interface, etc. In the embodiment of the present application, the terminal device 10 can be a terminal device for the user to upload the initial video and display the optimization suggestion information of the initial video.

[0045] Among them, when conducting video creation review, the initial video and the video review request corresponding to the initial video are obtained through the human-computer interaction interface of the terminal device 10 used by the user, and the initial video and the video review request are sent to the server 20. The server 20 will analyze the video content of the initial video in response to the video review request, and obtain optimization suggestion information for the initial video. The optimization suggestion information includes optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video. Then the server 20 sends the optimization suggestion information for the initial video to the terminal device 10. The terminal device 10 obtains the optimization suggestion information for the initial video sent by the server 20, and displays the optimization suggestion information for the initial video on the human-computer interaction interface.

[0046] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0047] See also Figures 2 to 12 , Figure 2 A schematic diagram of a video processing method according to an embodiment of the present invention. Figures 3 to 12 These are schematic diagrams of application scenarios of the video processing method provided in the embodiments of the present application. The method can be applied to Figure 1 The terminal device 10 shown. The method includes the following steps 110 to 130:

[0048] Step 110: obtaining an initial video and a video review request corresponding to the initial video through a human-computer interaction interface.

[0049] For example, Figure 1 The human-computer interaction interface 1 shown is an interface for realizing artificial intelligence interaction based on a generative model.

[0050] For example, the generative model may include at least one of a text-to-text model, an image-to-image model, and a cross-modal generative model.

[0051] Among them, the text generation text model is a natural language processing technology based on deep learning, which can convert the input text sequence into the target text sequence. This model usually uses a sequence-to-sequence model, which consists of an encoder and a decoder. The encoder converts the input text into an intermediate representation, and the decoder converts this intermediate representation into the target text. During the training process, the model learns to generate distributions by maximizing the likelihood probability of the real data distribution, so that it can generate text that conforms to language rules and has semantic meaning. The text generation text model can be applied to many natural language processing tasks, such as machine translation, dialogue generation, summary generation, etc. Among them, machine translation refers to the automatic translation of the input source language text into the target language text, dialogue generation refers to the generation of contextual responses based on the dialogue context, and summary generation refers to the automatic generation of concise summaries from the input text. In addition, the text generation text model can also be combined with other technologies, such as reinforcement learning, self-supervised learning, etc., to further improve the generation quality.

[0052] Among them, the image generation image model is an image processing technology based on deep learning, which can transform the input image into the target image. This model usually uses a convolutional neural network to learn the representation of the image and uses this representation to generate the target image. During the training process, the model learns to generate the distribution by minimizing the loss function of the real data distribution, so that it can generate images similar to the input image or with specific properties. The image generation image model can be applied to many image processing tasks, such as style transfer, image super-resolution, image restoration, etc. Among them, style transfer refers to the conversion of the style of the input image to the style of the target image, image super-resolution refers to the conversion of a low-resolution image into a high-resolution image, and image restoration refers to the restoration of damaged or missing images. In addition, the image generation image model can also be combined with other technologies, such as generative adversarial networks, self-supervised learning, etc., to further improve the generation quality and diversity.

[0053] Among them, the cross-modal generative model is a cross-modal data conversion technology based on deep learning, which can convert data of one modality into data of another modality. For example, text can be converted into images, speech can be converted into text, images can be converted into text, or images can be converted into videos. This model usually uses self-attention mechanism and cross-attention mechanism to learn the correspondence between different modalities and the cross-modal interaction relationship. During the training process, the model learns to generate distribution by maximizing the likelihood probability of the true data distribution, so that the data of the input modality can be converted into the data of the target modality. The cross-modal generative model can be applied to many cross-modal data conversion tasks, such as image subtitle generation, video summary generation, speech recognition, etc. Among them, image subtitle generation refers to automatically generating text subtitles describing the content of the input image, video summary generation refers to automatically generating concise video summaries from the input video, and speech recognition refers to converting the input speech into text. In addition, the cross-modal generative model can also be combined with other technologies, such as reinforcement learning, self-supervised learning, etc., to further improve the generation quality and diversity.

[0054] In the embodiment of the present application, by running a generative model application configured with a generative model, the following is demonstrated: Figure 1The friendly human-computer interaction interface 1 shown in the figure has an input window 11 and an interactive information display window 12, and also displays prompt information of the type of relevant example questions, so that the current user (user a) can conveniently select to upload the initial video V1 to be reviewed through the input window 11, and submit operations such as video review requests. For example, the video review request is determined based on the text description "This is a video I created about a smart glass-wiping robot. Please give me some optimization suggestions." Among them, the application configured with a generative model can also obtain the corresponding user request by performing semantic analysis on the text description after obtaining the initial video and text description uploaded by user a. For example, by analyzing the text description "This is a video I created about a smart glass-wiping robot. Please give me some optimization suggestions", it is determined that the user request is a video review request.

[0055] For example, see Figure 1 and Figure 3 The generative model can be set in the terminal device 10 or in the server 20.

[0056] When the generative model runs on the terminal device 10, the terminal device 10 stores the generative model application and is used to present the relevant interactive screen and the task processing results generated when the generative execution processing task is executed. The terminal device 10 is used to interact with the user through the human-computer interaction interface 1, for example, the generative model application is downloaded and installed by the terminal device 10 and runs. The terminal device 10 may provide the human-computer interaction interface 1 to the user in a variety of ways, for example, it can be rendered and displayed on the display screen of the terminal device 10, or the human-computer interaction interface is presented through holographic projection. For example, the terminal device 10 may include a touch display screen and a processor, the touch display screen is used to present the human-computer interaction interface 1 and receive the operation instructions generated by the user acting on the human-computer interaction interface 1, the human-computer interaction interface 1 may include an input window 11, an interactive information display window 12, prompt information, an interactive screen, etc., the processor is used to run the generative model, generate the human-computer interaction interface 1, respond to the operation instructions, and control the display of the human-computer interaction interface 1 on the touch display screen, etc.

[0057] When the generative model runs on the server, the running body of the generative model application and the interactive screen presentation body are separated, and the interactive screen presentation is completed on the generative model application client of the terminal device 10. The generative model application client is mainly used for receiving and sending data and presenting the interactive screen, but the device for data processing is the server 20. When executing a processing task through the generative model, the user operates the generative model application client to send an operation instruction to the server 20. The server runs the generative model according to the operation instruction, performs relevant processing tasks on the game screen and other data, returns the task processing results through the network, and finally, decodes it through the generative model application client and outputs the corresponding task processing results on the interactive screen.

[0058] Step 120, sending the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video.

[0059] For example, in an embodiment of the present application, in order to optimize the operating capabilities of a terminal device, an initial video and the video review request may be sent to a server, so that the server analyzes the video content of the initial video in response to the video review request, and obtains optimization suggestion information for the initial video. After sending the initial video and the video review request to the server, the server analyzes the content of the initial video according to preset review rules and algorithms. For example, the server analyzes the content of the initial video based on a generative model that has been trained to provide video optimization functions. During the analysis process, the server considers multiple aspects of the video, such as content, theme, form, type, and purpose, and generates optimization suggestion information based on the analysis results.

[0060] The optimization suggestion information is optimization suggestions for the initial video, including optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video. These optimization suggestions may include optimization suggestions for video editing, special effects, color, sound effects, shooting methods, etc., as well as suggestions and guidance for video content to help users better express the theme and intention of the video.

[0061] For example, you can determine personalized optimization suggestions based on the target purpose of the initial video. For example, for food purposes, the focus is on the production steps; for travel purposes, the focus is on must-see places and travel routes, etc.

[0062] These optimization suggestions can be returned to users through the human-computer interaction interface, so that users can promptly understand the review results and optimization suggestions for the initial video. Users can modify and improve the initial video based on the optimization suggestions to better achieve the intention and goal of the video. At the same time, these optimization suggestions can also be used to improve the quality and efficiency of video production, and enhance the attractiveness and dissemination effect of the video.

[0063] For example, the optimization suggestion information may include adjustment suggestions for the order of video shooting scenes, the words, the content of the scenes shot, the choice of background music, the speed of oral broadcast, and whether to use artificial intelligence (AI) dubbing. The generative model can give optimization suggestions based on the theme and intention of the video and present each optimization suggestion in a structured form. The optimization suggestion information can also give the reasons for the modification of the modification opinions in the optimization suggestions, such as how to modify the picture to be more attractive, how to design the words to be more easy to understand, which music selection will be more suitable, whether the oral broadcast speed is moderate, too slow or too fast, and in what scenarios AI dubbing is more suitable than user self-dubbing. Subsequently, optimized videos can also be generated based on the optimization suggestion information. For example, special effects and background music matching can be intelligently added to the optimized video, such as mask effects, appearance effects, transition effects, and special effects music at key nodes, such as danger sounds and camera sounds to enhance the video.

[0064] In some embodiments, sending the initial video and the video review request to the server so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video includes:

[0065] Sending the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request, determines the target purpose of the initial video, and determines a plurality of candidate dimensions to be processed corresponding to the initial video according to the target purpose, wherein different purposes correspond to different candidate dimensions to be processed;

[0066] The server obtains the video content under each of the multiple candidate dimensions in the initial video, and performs semantic analysis on the video content under each candidate dimension according to the optimization reference information corresponding to each of the multiple candidate dimensions, and determines whether the video content under each candidate dimension needs to be optimized;

[0067] The server determines optimization suggestions for the target video content under the target dimension to be optimized according to the optimization reference information corresponding to the target dimension to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video contents.

[0068] For example, the purpose of videos can be divided into talent, plot, character close-up, interest, knowledge, commentary, etc. Talent can include dressing suggestions, game commentary, music display, dance display, handicraft display, painting display, technology display, etc. Interest can include food, travel, animation, text, sports, fashion, technology, cars, good product recommendations, sports, etc. Plot can include funny, jokes, suspense, interviews, positive energy, life records, etc. Knowledge can include software usage skills, tips, culture, education, photography, maternal and child knowledge, health, workplace, creativity, etc. Commentary can include explanation, inventory, evaluation, etc.

[0069] For example, after sending the initial video and video review request to the server, the server will analyze the video content of the initial video and determine the target purpose of the initial video. The target purpose may refer to the purpose of the initial video, such as publicity, education, entertainment, etc. According to different target purposes, the server will determine multiple candidate dimensions to be processed corresponding to the initial video. For example, if the initial video is a commercial advertisement, the candidate dimensions may include the attractiveness of the video, the target audience, the brand image, etc.; if the initial video is an educational video, the candidate dimensions may include the teaching effect of the video, the coverage of knowledge points, etc.

[0070] For example, the server obtains the video content under each candidate dimension of multiple candidate dimensions in the initial video. Then, according to the optimization reference information corresponding to each candidate dimension, a semantic analysis is performed on the video content under each candidate dimension. The optimization reference information can be a pre-set rule, algorithm or reference data used to guide the server to optimize the video content. Through semantic analysis, the server can determine whether the video content under each candidate dimension needs to be optimized. For example, the optimization reference information can be the optimization reference information obtained after network learning through a large amount of data in the generative model, and can include optimization reference information related to different dimensions for different purposes. For example, different dimensions can include the order of video shooting scenes, the words, the content of the scene shot, the choice of background music, the speed of oral broadcasting, whether to use AI dubbing, the setting method of special effects, the color adjustment method, etc.

[0071] For example, if the server determines the target video content under the target dimension that needs to be optimized, it will determine the optimization suggestions for the target video content based on the optimization reference information corresponding to the target dimension. These optimization suggestions can be suggestions for video editing, special effects, color, sound effects, shooting methods, etc., or they can be suggestions and guidance for video content. Through these optimization suggestions, users can better improve video production and improve the quality and effect of the video.

[0072] By sending the initial video and video review request to the server and performing a series of analysis and processing, the server can provide users with optimization suggestions for the initial video. These optimization suggestions can help users better improve video production and improve the quality and effect of the video. At the same time, this service can also improve the efficiency and quality of video production and provide users with a better video production experience.

[0073] For example, Figure 3 and Figure 4 As shown, assuming that the initial video is an introduction video about "Smart Glass Cleaning Robot", by analyzing the video content, it is determined that the target use of the initial video is promotion and sales. Target use (promotion and sales): The video is intended to promote and sell the smart glass cleaning robot, attracting potential customers to be interested in it and eventually buy it. For example, the candidate dimensions corresponding to the target use of promotion and sales may include the dimension of video attractiveness, the dimension of information delivery, the dimension of product display, etc.

[0074] For example, Figure 4 As shown, the target purpose of the initial video is "good product recommendation", such as Figure 4 The text description related to the target use shown in the optimization suggestion information displayed in the human-computer interaction interface 1 is “identified that your video belongs to 'good things recommendation'”.

[0075] For example, regarding the attractiveness dimension: you can focus on the visual effects, sound effects, editing and other elements of the video to attract the audience's attention; for example, the optimization reference information corresponding to the attractiveness dimension can be specific optimization suggestions for the visual effects, sound effects, editing and other elements of the video content; the optimization reference information can be other successful technology product promotion video cases, or some known effective techniques and strategies for attracting audiences. Information transmission dimension: you can focus on whether the video clearly conveys the product's features, functions and advantages. The optimization reference information corresponding to the information transmission dimension can be the product's technical documentation, relevant copywriting on the product's features, functions and advantages, etc.

[0076] For example, regarding the product display dimension, you can focus on whether the video fully demonstrates the product's appearance, functions, and operation process. The optimization reference information corresponding to the product display dimension can be physical photos of the product, operation process pictures, etc.

[0077] For example, regarding optimization reference information: based on the above candidate dimensions, you can set optimization reference information for optimizing videos from several aspects. For example, add special effects and animations to enhance the visual effects and appeal of the video; for example, adjust background music and sound effects to create a more attractive atmosphere; for example, improve editing rhythm and transition effects to enhance the video viewing experience; for example, add user reviews and case studies to enhance the audience's trust in the product and willingness to buy; for example, improve the product display process in the video to more clearly display the characteristics and functions of the product.

[0078] For example, after determining the target video content under the target dimension that needs to be optimized, the optimization suggestions for the target video content can be determined based on the optimization reference information corresponding to the target dimension that needs to be optimized. Specifically, by analyzing the optimization reference information of each dimension, the server will provide specific optimization suggestions for the target video content under each target dimension that needs to be optimized in the initial video. For example, for the attractiveness dimension, optimization suggestions may include dubbing, sound effect adjustment, adding special effects, improving color matching, increasing editing rhythm, etc.; for the information transmission dimension, optimization suggestions may include adjusting the way information is transmitted, modifying promotional copy to better attract the target audience, etc.; for the product display dimension, optimization suggestions may include improving the product display process, adding product function demonstrations, etc.

[0079] For example, Figure 4 As shown, the optimization suggestion information for the initial video may include Figure 4 The 4 optimization suggestions are shown. The first optimization suggestion is about the product display process, such as "1. Move the content from 12s to 14s to 57s. It will be more attractive to introduce the feature of wiping clean first." The second optimization suggestion is about modifying the promotional copy to better attract the target audience, such as "2. Change the 37s oral copy "Press the power button to adsorb it on the glass with one click" to "One-click start it will automatically start working", which is more colloquial." The third optimization suggestion is about the sound effect adjustment, such as "3. The current volume is too high, and the sudden high volume seems very abrupt. It is recommended to increase the overall background music, reduce the oral voice, and appropriately reduce the special effect sound." The fourth optimization suggestion is about whether to use AI dubbing, such as "4. The overall speaking speed is too slow, and AI dubbing has been adjusted."

[0080] Step 130, obtaining optimization suggestion information for the initial video sent by the server, and displaying the optimization suggestion information for the initial video on the human-computer interaction interface.

[0081] This step is to allow users to easily obtain and understand the optimization suggestions for the initial video, so as to better improve and perfect the user's video production. At the same time, it provides a real-time feedback mechanism so that users can understand the quality and effect of the video in a timely manner and make adjustments and improvements in a timely manner.

[0082] For example, the optimization suggestion information can be obtained and displayed through data transmission between the server and the human-computer interaction interface on the terminal device. For example, the server can send the optimization suggestion information to the human-computer interaction interface on the terminal device in the form of a data stream, and then display the optimization suggestion information to the user based on the human-computer interaction interface.

[0083] There are many ways to display the optimization suggestion information, such as text, icons, images, or videos. These optimization suggestion information can be displayed in a designated area of ​​the human-computer interaction interface, or presented to the user through a pop-up window or other means.

[0084] For example, when displaying optimization suggestions for the initial video on the human-computer interaction interface, the implementation effect and evaluation indicators of each optimization suggestion can also be displayed. The implementation effect and evaluation indicators of each optimization suggestion can help users better understand the characteristics and effects of each optimization suggestion, so as to make more targeted edits and adjustments.

[0085] In addition, interactive design can also be used to enable users to better understand and apply optimization recommendations. For example, users can select the dimensions to be optimized on the human-computer interaction interface, and then the system will only display optimization recommendations for these selected dimensions based on the user's selection. At the same time, some auxiliary tools or prompt information can also be provided to help users better understand and apply these optimization recommendations.

[0086] For example, Figure 4 As shown, after the terminal device obtains the optimization suggestion information for the initial video sent by the server, it displays the optimization suggestion information for the initial video on the human-computer interaction interface. For example, the optimization suggestion information may include Figure 4 The 4 optimization suggestions shown.

[0087] In some embodiments, the optimization suggestion information further includes initial optimized content corresponding to the target video content generated based on the optimization suggestion for the target video content;

[0088] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface includes:

[0089] On the human-computer interaction interface, optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video are displayed, and initial optimization content corresponding to the target video content is displayed.

[0090] For example, the optimization suggestion information includes not only optimization suggestions for the target video content itself, but also initial optimization content generated based on the optimization suggestions for the target video content. It is understandable that the optimization suggestion information may include specific modification suggestions and preliminary optimization results for these modification suggestions.

[0091] When displaying optimization suggestion information on the human-computer interaction interface, in addition to displaying the optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video, the initial optimization content corresponding to the target video content should also be displayed. In this way, users can more intuitively understand the specific implementation effects of the optimization suggestions, and thus better understand and apply these optimization suggestions.

[0092] For example, if the target video content is a product demonstration video, optimization suggestions may include changing the background music, adjusting the lighting, etc. These optimization suggestions can be displayed in the form of text or icons on the human-computer interaction interface, and the initial effect after the modification, that is, the initial optimization content, can also be displayed. In this way, users can see the effect of the modification suggestions more clearly and decide whether to adopt these optimization suggestions.

[0093] In addition, in order to better help users understand and apply optimization suggestions, the human-computer interaction interface can also provide more interactive functions. For example, users can select the optimization suggestions they need to adopt on the human-computer interaction interface and view the final effect after adopting these suggestions. Alternatively, users can also sort or filter the optimization suggestions to prioritize the most important or most urgent suggestions.

[0094] By displaying optimization suggestions for target video content under target dimensions that need to be optimized corresponding to the target purpose of the initial video, and displaying the initial optimized content corresponding to the target video content, users can more comprehensively understand and evaluate the optimization suggestions, thereby more effectively improving and perfecting the user's video production.

[0095] For example, Figure 4 As shown, the terminal device obtains the optimization suggestion information and the corresponding initial optimization content for the initial video sent by the server, and displays several optimization suggestions and the corresponding initial optimization content for the initial video on the human-computer interaction interface. The initial optimization content may include the initial optimization content V1-1 corresponding to the first optimization suggestion, and the initial optimization content V1-2 corresponding to the second optimization suggestion. Figure 4The initial optimization content corresponding to the third and fourth optimization suggestions is not shown, but in actual application, the initial optimization content corresponding to all optimization suggestions for the initial video, or the initial optimization content corresponding to some optimization suggestions, can be displayed on the human-computer interaction interface.

[0096] In some embodiments, the method further includes: displaying a first optimized video on the human-computer interaction interface, wherein the first optimized video is generated by adjusting the initial video according to the optimization suggestion information.

[0097] Among them, displaying the first optimized video on the human-computer interaction interface is an important way to make optimization suggestions for the initial video. The first optimized video is generated by adjusting the initial video according to the optimization suggestion information. It can show the optimized video effect so that users can evaluate and confirm the optimization suggestions.

[0098] When generating the first optimized video, the dimensions of the initial video may be adjusted according to the optimization suggestion information. For example, if the optimization suggestion information mentions adding special effects and improving color matching, the first optimized video may improve the visual effect of the initial video by adding special effects and adjusting color matching.

[0099] When the first optimization video is displayed on the human-computer interaction interface, it can be displayed through a video player or a preview window. The user can watch the first optimization video in full or in detail to evaluate the effectiveness and implementation effect of the optimization suggestion. At the same time, the human-computer interaction interface can also provide a playback control function, so that the user can pause, play or loop the first optimization video at any time.

[0100] For example, in addition to displaying the first optimized video, the human-computer interaction interface may also provide other relevant information and auxiliary tools to help users better evaluate and adjust the optimization suggestions. For example, a list of optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video may be displayed, and the implementation effect and importance of each suggestion may be marked. In addition, a marking, annotation or feedback function may be provided to enable users to record their opinions and suggestions on the first optimized video in order to further improve and adjust the initial video.

[0101] Among them, displaying the first optimization video on the human-computer interaction interface is an important means to help users intuitively understand and evaluate the optimization suggestions. By watching the first optimization video, users can better understand the implementation effect and feasibility of the optimization suggestions, so as to improve and perfect their video production in a more targeted manner.

[0102] In some embodiments, displaying the first optimized video on the human-computer interaction interface includes:

[0103] Displaying a new video generation control on the human-computer interaction interface;

[0104] Obtaining a first new video generation request generated based on a first trigger operation of the new video generation control, and sending the first new video generation request to the server, so that the server adjusts the initial video according to the optimization suggestion information in response to the first new video generation request to generate a first optimized video;

[0105] The first optimized video sent by the server is obtained, and the first optimized video is displayed on the human-computer interaction interface.

[0106] First, a new video generation control is displayed on the human-computer interaction interface. This new video generation control can be a button, an icon, or a menu item. The user can trigger the operation of generating the first optimized video by clicking or selecting this new video generation control. The new video generation control can clearly identify its function, such as displaying prompt text such as "generate a new video", "generate an optimized video", or "adjust and generate a new video". Figure 4 The new video generation control 14 shown has a prompt text displayed as "Generate new video".

[0107] Then, a first new video generation request generated based on the first trigger operation of the new video generation control is obtained. When the user performs the first trigger operation on the new video generation control, the human-computer interaction interface captures the first trigger operation and generates a first new video generation request. The first new video generation request is used to indicate that the initial video is adjusted based on the optimization suggestion information. For example, Figure 4 As shown, when the user performs a first trigger operation on the new video generation control 14, the human-computer interaction interface 1 captures the first trigger operation and generates a first new video generation request.

[0108] Then, a first new video generation request is sent to the server. The human-computer interaction interface sends the first new video generation request to the server to request the server to adjust the initial video according to the optimization suggestion information. The server can perform corresponding processing after receiving the first new video generation request, for example, adjusting various dimensions of the initial video according to the optimization suggestion information to generate a first optimized video.

[0109] Then, the first optimized video sent by the server is obtained. When the server completes the generation of the first optimized video, the first optimized video is sent to the human-computer interaction interface. After receiving the first optimized video, the human-computer interaction interface can perform corresponding processing, such as storing the first optimized video in the terminal device or displaying it on the human-computer interaction interface of the terminal device.

[0110] Then, the first optimization video is displayed on the human-computer interaction interface. The human-computer interaction interface can provide a dedicated area or window to display the first optimization video so that users can watch and evaluate the implementation effect of the optimization suggestion. The displayed video can be a full version or a preview version, and can also provide playback control functions, such as pause, play, or loop. For example, Figure 5 As shown, the first optimized video V2 is displayed on the interactive information display window 12 of the human-computer interaction interface 1, wherein the first optimized video V2 is displayed on the chat information bar corresponding to the robot b in the interactive information display window 12. In addition to displaying the first optimized video V2, a check prompt message can also be displayed, for example, the check prompt message is "A new video has been generated for you, please check it."

[0111] In some embodiments, the method further comprises:

[0112] Displaying adjustment controls on the human-computer interaction interface;

[0113] A third trigger operation based on the adjustment control is obtained, and an edit control and a delete control are displayed on the human-computer interaction interface.

[0114] First, display adjustment controls on the human-computer interaction interface. In addition to displaying optimization suggestion information and new video generation controls, the human-computer interaction interface can also provide adjustment controls so that users can freely adjust the parameters or settings of the optimization suggestions. These adjustment controls can be various sliders, buttons, icons, or menu items, so that users can adjust the optimization suggestions according to their needs.

[0115] Then, a third trigger operation based on the adjustment control is obtained, and the edit control and the delete control are displayed on the human-computer interaction interface. When the user operates the adjustment control, such as clicking or dragging the slider, the human-computer interaction interface captures this operation and generates a third trigger operation. This trigger operation can be used to trigger the display of the edit control and the delete control.

[0116] The display of the edit control and the delete control can be associated with the adjustment control. For example, when the user adjusts a parameter, an edit control and a delete control can be displayed at the same time, so that the user can edit and delete the corresponding optimization suggestions at any time. In this way, the user can adjust, edit or delete each optimization suggestion at any time according to their needs, thereby improving the flexibility and controllability of video production.

[0117] Through the above steps, the human-computer interaction interface can provide richer and more flexible functions, allowing users to make and optimize videos more conveniently. Users can freely adjust the parameters of optimization suggestions, edit the content of optimization suggestions, or delete unnecessary optimization suggestions according to their needs to improve the quality and effect of the video. At the same time, the interface can also provide relevant information and auxiliary tools to help users better understand and apply these functions.

[0118] For example, see Figure 6 and Figure 7 ,exist Figure 6 The adjustment control 13 is displayed on the human-computer interaction interface shown in FIG. 1 , and then a third trigger operation based on the adjustment control 13 is obtained. Figure 7 The human-computer interaction interface 1 shown shows an edit control 131 and a delete control 132 .

[0119] In some embodiments, the method further comprises:

[0120] Displaying an editing control corresponding to each of the optimization suggestions on the human-computer interaction interface;

[0121] Obtaining an edit request for generating the first optimization suggestion based on a trigger operation of an edit control corresponding to the selected first optimization suggestion and input edit content;

[0122] In response to the edit request of the first optimization suggestion, generating an edited first optimization suggestion;

[0123] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes:

[0124] The first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is replaced with the edited first optimization suggestion to obtain updated optimization suggestion information.

[0125] First, the editing controls corresponding to each optimization suggestion are displayed on the human-computer interaction interface. In order to facilitate users to modify and adjust the optimization suggestions, the human-computer interaction interface can display the editing controls corresponding to each optimization suggestion. These editing controls can be various input fields, sliders, buttons, icons, or menu items, etc., so that users can edit and adjust the optimization suggestions as needed. For example, Figure 7 An edit control 131 is shown.

[0126] Then, an edit request for the first optimization suggestion is generated based on the trigger operation of the edit control corresponding to the selected first optimization suggestion and the edit content input. When the user operates the edit control corresponding to a certain optimization suggestion or inputs edit content, the human-computer interaction interface captures these operations and content and generates an edit request for the first optimization suggestion. This request may include specific information about the optimization suggestion edited by the user, such as adjusted parameters, newly added materials, etc. For example, Figure 7 As shown, when the user operates the editing control 131 corresponding to the first optimization suggestion or inputs editing content, the human-computer interaction interface 1 captures these operations and content and generates an editing request for the first optimization suggestion.

[0127] Then, in response to the edit request of the first optimization suggestion, an edited first optimization suggestion is generated. The terminal device can directly respond to the edit request of the first optimization suggestion to generate the edited first optimization suggestion. In addition, the edit request of the first optimization suggestion can also be sent to the server, so that after receiving the edit request of the first optimization suggestion, the server will edit the initial video according to the specific information in the request and generate the edited first optimization suggestion. This process can also include various editing operations such as adjusting the video content, adding special effects, modifying the color, etc. based on the edited first optimization suggestion.

[0128] For example, Figure 8 As shown, when the edited first optimization suggestion is generated, the editing operation on the first optimization suggestion can be canceled by touching the cancel control 1311; or the editing completion operation on the first optimization suggestion can be confirmed by touching the completion control 1312.

[0129] Then, the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is replaced with the edited first optimization suggestion to obtain updated optimization suggestion information. In order to reflect the user's editing operation and the modified video effect, the human-computer interaction interface replaces the first optimization suggestion in the displayed optimization suggestion information with the edited first optimization suggestion. In this way, the user can see the effect of the updated optimization suggestion information in a timely manner and evaluate and adjust other optimization suggestions.

[0130] Through the above steps, users can easily edit and adjust optimization suggestions on the human-computer interaction interface and view the modified optimization suggestions in real time.

[0131] In some embodiments, the method further comprises:

[0132] Sending the edited first optimization suggestion to the server, so that the server generates new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion;

[0133] Acquire new optimization content corresponding to the edited first optimization suggestion sent by the server;

[0134] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes:

[0135] The initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is replaced with the new optimization content corresponding to the edited first optimization suggestion to obtain updated optimization suggestion information.

[0136] Among them, when the user edits the first optimization suggestion on the human-computer interaction interface and submits the modified content to generate the edited first optimization suggestion, this step allows the terminal device to locally save the edited first optimization suggestion, and then send the edited first optimization suggestion to the server for further processing. After receiving the user's modified content, the server will generate new optimization content corresponding to the edited first optimization suggestion based on these modified contents. This process may include various editing operations such as adjusting the video content, adding special effects, and modifying the color. When the server completes the generation of the new optimization content, it will send the new optimization content to the terminal device, and the terminal device can perform corresponding processing after receiving the new optimization content, such as storing the new optimization content locally or displaying it on the human-computer interaction interface. In order to reflect the user's editing operation and the modified video effect, the human-computer interaction interface will replace the initial optimization content corresponding to the first optimization suggestion in the displayed optimization suggestion information with the new optimization content. In this way, the user can see the modified effect in time and evaluate and adjust other optimization suggestions.

[0137] In some embodiments, the method further comprises:

[0138] Displaying a cancel control corresponding to the edited first optimization suggestion on the human-computer interaction interface;

[0139] Obtaining a cancellation request for generating the edited first optimization suggestion based on the triggering operation of the cancel control;

[0140] In response to the cancellation request, canceling the edited first optimization suggestion;

[0141] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes:

[0142] The edited first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is restored as the first optimization suggestion.

[0143] For example, in order to provide the user with an opportunity to cancel the first optimization suggestion after editing, the human-computer interaction interface can display a cancel control. This cancel control can be a button, icon, or other user interface element. When the user clicks or selects it, a cancel request will be triggered. For example, Figure 8 A cancel control 1311 is shown.

[0144] For example, when a user operates a cancel control, such as clicking a button or selecting an icon, the human-computer interaction interface captures the operation and generates a cancel request. The cancel request may include specific information about the optimization suggestion to be canceled, such as the content and status of the edited first optimization suggestion.

[0145] For example, after receiving the cancellation request, the terminal device and / or the server will cancel the edited first optimization suggestion according to the specific information in the request, which may involve undoing the previous editing operation, restoring to the original state, and the like.

[0146] For example, in order to reflect the cancellation operation, the human-computer interaction interface will restore the edited first optimization suggestion in the displayed optimization suggestion information to the first optimization suggestion. In this way, the optimization suggestion information seen by the user on the human-computer interaction interface will be restored to the state before editing.

[0147] Through the above steps, the user can easily cancel the editing operation of the first optimization suggestion on the human-computer interaction interface and restore it to the original state. The embodiment of the present application provides a flexible mechanism, allowing the user to undo previous modifications at any time and re-edit and adjust as needed. At the same time, this also enhances the user's sense of control over video production, allowing the user to repeatedly try and improve the video effect as needed.

[0148] In some embodiments, the method further comprises:

[0149] Displaying a deletion control corresponding to each of the optimization suggestions on the human-computer interaction interface;

[0150] Obtaining a deletion request for the second optimization suggestion generated based on a triggering operation of a deletion control corresponding to the selected second optimization suggestion;

[0151] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes:

[0152] In response to a request to delete the second optimization suggestion, the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is deleted to obtain updated optimization suggestion information.

[0153] For example, to provide users with an opportunity to delete each optimization suggestion, the human-computer interaction interface can display a delete control. This delete control can be a button, icon, or other user interface element that triggers a delete request when the user clicks or selects it. Each optimization suggestion corresponds to a delete control, allowing the user to choose to delete any optimization suggestion. For example, Fig. 9 A delete control 132 is shown.

[0154] For example, when the user selects a delete control, the human-computer interaction interface captures this operation and generates a delete request. This delete request may include specific information about the optimization suggestion to be deleted, such as the content and status of the second optimization suggestion. Fig. 9 As shown, when the user triggers the deletion control 132 corresponding to the fourth optimization suggestion to generate a deletion request, the human-computer interaction interface 1 may also display the following Fig.10 The deletion confirmation interface 2 shown is used to cancel the deletion operation by touching the cancel deletion control 1321 in the deletion confirmation interface 2, or to complete the deletion operation by touching the complete deletion control 1322 in the deletion confirmation interface 2.

[0155] For example, after receiving the deletion request, the terminal device and / or the server may delete the second optimization suggestion according to the specific information in the request, which may involve undoing the previous editing operation, deleting the corresponding record from the database, and the like.

[0156] For example, in order to reflect the deletion operation, the human-computer interaction interface will delete the second optimization suggestion in the displayed optimization suggestion information. In this way, the optimization suggestion information that the user sees on the human-computer interaction interface will not include the deleted second optimization suggestion. Fig.11 As shown, the fourth optimization suggestion in the optimization suggestion information originally displayed on the human-computer interaction interface 1 is deleted, and the updated optimization suggestion information displayed does not include the fourth optimization suggestion.

[0157] Through the above steps, the user can easily delete any optimization suggestion on the human-computer interaction interface and view the updated optimization suggestion information in real time. The embodiment of the present application provides an effective mechanism that enables users to manage and adjust optimization suggestions as needed. At the same time, this also enhances the user's sense of control over video production, allowing users to flexibly select and delete unnecessary optimization suggestions to achieve better video effects.

[0158] In some embodiments, the method further comprises:

[0159] The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes:

[0160] In response to a request to delete the second optimization suggestion, initial optimization content corresponding to the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is deleted to obtain updated optimization suggestion information.

[0161] For example, after receiving the deletion request, the terminal device and / or server will process the deletion operation according to the specific information in the request. For the second optimization suggestion, in addition to deleting the suggestion from the displayed optimization suggestion information, the initial optimization content corresponding to the second optimization suggestion also needs to be deleted from the optimization suggestion information. This may involve undoing previous editing operations, deleting corresponding records from the database, and other processing. After deleting the second optimization suggestion and its corresponding initial optimization content, the human-computer interaction interface will update the displayed optimization suggestion information. In this way, the optimization suggestion information seen by the user on the interface will not include the deleted second optimization suggestion and its corresponding initial optimization content.

[0162] In some embodiments, the method further comprises:

[0163] A second optimized video is displayed on the human-computer interaction interface, where the second optimized video is generated by adjusting the initial video according to the updated optimization suggestion information.

[0164] The second optimized video is generated based on the updated optimization suggestion information, so that the user can intuitively see the impact of editing and deleting operations on the video.

[0165] In some embodiments, displaying the second optimized video on the human-computer interaction interface includes:

[0166] Displaying a new video generation control on the human-computer interaction interface;

[0167] Obtaining a second new video generation request generated based on a second trigger operation of the new video generation control, and sending the second new video generation request and the updated optimization suggestion information to the server, so that the server responds to the second new video generation request and adjusts the initial video according to the updated optimization suggestion information to generate a second optimized video;

[0168] The second optimized video sent by the server is obtained, and the second optimized video is displayed on the human-computer interaction interface.

[0169] For example, in order to provide a user with an opportunity to generate a new video, the human-computer interaction interface can display a new video generation control. This new video generation control can be a button, icon, or other user interface element. When the user clicks or selects it, a second trigger operation is triggered. When the user operates the new video generation control, such as clicking a button or selecting an icon, the human-computer interaction interface captures this operation and generates a second new video generation request. This request can contain specific information about the new video to be generated, such as new effects to be applied, new color adjustments, etc.

[0170] For example, Fig.11 As shown, when the user performs a second trigger operation on the new video generation control 14, the human-computer interaction interface 1 captures the second trigger operation and generates a second new video generation request.

[0171] For example, when the user triggers the second new video generation request, the human-computer interaction interface sends the second new video generation request and the updated optimization suggestion information to the server. This may involve passing the information in the request to the server, and also sending the updated optimization suggestion information to the server for processing. After receiving the second new video generation request and the updated optimization suggestion information, the server will adjust the initial video and generate a second optimized video according to the specific information in the request. This may involve applying new editing effects, adjusting colors, adding background music, and other processing. When the server completes the generation of the second optimized video, it will send the second optimized video to the terminal device. After receiving the second optimized video, the terminal device can perform corresponding processing, such as storing the second optimized video locally in the terminal device or displaying the second optimized video on the human-computer interaction interface. In order to enable the user to watch and evaluate the newly generated second optimized video, the human-computer interaction interface will display the second optimized video. The user can watch the second optimized video and evaluate its quality. The second optimized video is adjusted and generated according to the user's editing and / or deletion operations, so the second optimized video can reflect the user's needs and preferences for video production.

[0172] like Fig.12 As shown, the second optimized video V3 is displayed on the interactive information display window 12 of the human-computer interaction interface 1, wherein the second optimized video V3 is displayed on the chat information bar corresponding to the robot b in the interactive information display window 12. In addition to displaying the second optimized video V3, a check prompt message can also be displayed, for example, the check prompt message is "A new video has been generated for you, please check it."

[0173] The embodiment of the present application obtains the initial video and the corresponding video review request and sends this information to the server, so as to achieve in-depth analysis of the initial video content and obtain optimization suggestion information. This optimization suggestion information can guide the user to optimize the initial video, improve the quality of the video, and provide effective video optimization guidance.

[0174] The embodiments of the present application can provide targeted and personalized optimization suggestions based on the target purpose of the initial video. These optimization suggestions can involve target video content under the target dimension to be optimized, thereby helping users create videos that better meet their needs and expectations.

[0175] The embodiment of the present application displays the optimization suggestion information on the human-computer interaction interface, allowing users to more conveniently understand and view the optimization suggestion information, which helps users optimize the initial video more quickly and effectively, thereby improving the efficiency of video creation.

[0176] The optimization suggestions provided by the embodiments of the present application are based on in-depth analysis and understanding of the initial video, so these suggestions are usually more targeted and effective than simple automatic optimization algorithms. This helps to enhance the quality of videos created by users, promote the development of the entire video industry, and create more value for society.

[0177] The embodiment of the present application uses a server to analyze the initial video and generate optimization suggestions, so that even without local high-performance computing resources, users can obtain professional video optimization suggestions. This helps to achieve efficient remote collaboration, and for users without professional video production skills, it can lower the technical threshold of video production, allowing more people to participate in the process of video creation.

[0178] All of the above technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described in detail here.

[0179] The embodiment of the present application obtains the initial video and the video review request corresponding to the initial video through the human-computer interaction interface; sends the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request, and obtains optimization suggestion information for the initial video, the optimization suggestion information includes optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video; obtains the optimization suggestion information for the initial video sent by the server, and displays the optimization suggestion information for the initial video on the human-computer interaction interface. The embodiment of the present application can provide effective optimization suggestion information for the initial video created by the user, so as to guide the user to create a better quality video, thereby improving the efficiency and quality of video creation.

[0180] See also Fig.13, Fig.13 The second flow chart of the video processing method provided in the embodiment of the present application is as follows. The method can be applied to Figure 1 The server 20 shown. The method includes the following steps 210 to 230:

[0181] Step 210: Receive an initial video sent by a terminal device and a video review request corresponding to the initial video.

[0182] For example, after the terminal device obtains the initial video and the video review request corresponding to the initial video through the human-computer interaction interface, it sends the initial video and the video review request to the server, and then the server receives the initial video and the video review request corresponding to the initial video sent by the terminal device.

[0183] Step 220, in response to the video review request, analyze the video content of the initial video to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video.

[0184] For example, the server analyzes the video content of the initial video in response to the video review request and obtains optimization suggestion information for the initial video. The server analyzes the content of the initial video according to preset review rules and algorithms. For example, the server analyzes the content of the initial video according to a generative model that has been trained to provide video optimization functions. During the analysis process, the server considers multiple aspects of the video, such as content, theme, form, type, and purpose, and generates optimization suggestion information based on the analysis results.

[0185] The optimization suggestion information is optimization suggestions for the initial video, including optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video. These optimization suggestions may include optimization suggestions for video editing, special effects, color, sound effects, shooting methods, etc., as well as suggestions and guidance for video content to help users better express the theme and intention of the video.

[0186] For example, you can determine personalized optimization suggestions based on the target purpose of the initial video. For example, for food purposes, the focus is on the production steps; for travel purposes, the focus is on must-see places and travel routes, etc.

[0187] For example, the optimization suggestion information may include adjustment suggestions for the order of video shooting scenes, the words, the content of the scenes shot, the choice of background music, the speed of oral broadcast, and whether to use artificial intelligence (AI) dubbing. The generative model can give optimization suggestions based on the theme and intention of the video and present each optimization suggestion in a structured form. The optimization suggestion information can also give the reasons for the modification of the modification opinions in the optimization suggestions, such as how to modify the picture to be more attractive, how to design the words to be more easy to understand, which music selection will be more suitable, whether the oral broadcast speed is moderate, too slow or too fast, and in what scenarios AI dubbing is more suitable than user self-dubbing. Subsequently, optimized videos can also be generated based on the optimization suggestion information. For example, special effects and background music matching can be intelligently added to the optimized video, such as mask effects, appearance effects, transition effects, and special effects music at key nodes, such as danger sounds and camera sounds to enhance the video.

[0188] In some embodiments, analyzing the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video includes:

[0189] In response to the video review request, analyzing the video content of the initial video to determine the target use of the initial video;

[0190] Determining, according to the target purpose, a plurality of candidate dimensions to be processed corresponding to the initial video, wherein different purposes correspond to different candidate dimensions to be processed;

[0191] Obtaining video content in each of the multiple candidate dimensions in the initial video;

[0192] According to the optimization reference information corresponding to each candidate dimension among the multiple candidate dimensions, semantic analysis is performed on the video content under each candidate dimension to determine whether the video content under each candidate dimension needs to be optimized;

[0193] For the target video content under the determined target dimension to be optimized, optimization suggestions for the target video content are determined according to the optimization reference information corresponding to the target dimension to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video contents.

[0194] For example, first, after receiving a video review request, the server will conduct an in-depth analysis of the content of the initial video. This analysis may include a comprehensive understanding of the video's metadata, content, audio, subtitles, and other information to clarify the main target use of the video. For example, the target use of the video may be for entertainment, education, advertising, or news reporting.

[0195] Then, based on the target purpose of the initial video obtained through preliminary analysis, multiple candidate dimensions of the video content that need to be processed are determined. These candidate dimensions are usually differentiated and selected according to different purposes. For example, for news reporting videos, fact checking, verification, and interpretation may be required; while for entertainment videos, more attention may be paid to whether the content is interesting and attractive.

[0196] Then, the specific content of each candidate dimension is extracted from the initial video, which may involve a specific segment, audio, subtitle, etc. of the video, so as to obtain the video content under each candidate dimension of the multiple candidate dimensions in the initial video.

[0197] Then, based on the optimization reference information of each candidate dimension, natural language processing and machine learning technologies are used to conduct in-depth semantic analysis of the video content under the candidate dimension. This can help the system understand the meaning of the video content and determine whether the video content under each candidate dimension needs to be optimized.

[0198] Then, for the target video content under the target dimensions that are determined to be optimized, the server will make specific optimization suggestions based on the relevant optimization reference information. These optimization suggestions may include modifying video clips, adding subtitles, replacing background music, using AI dubbing, etc. These optimization steps will be performed for specific target dimensions, and different target dimensions will correspond to different optimization suggestions and target video content.

[0199] In step 220, the video content can be automatically analyzed and understood, and whether optimization is required can be determined based on set standards, which can not only improve the efficiency of video review, but also provide more accurate and objective review results.

[0200] Step 230: Send optimization suggestion information for the initial video to the terminal device, so that the terminal device displays the optimization suggestion information for the initial video on a human-computer interaction interface.

[0201] For example, the optimization suggestion information can be obtained and displayed through data transmission between the server and the human-computer interaction interface on the terminal device. For example, the server can send the optimization suggestion information to the human-computer interaction interface on the terminal device in the form of a data stream, and then display the optimization suggestion information to the user based on the human-computer interaction interface.

[0202] In some embodiments, the optimization suggestion information further includes initial optimized content corresponding to the target video content generated based on the optimization suggestion for the target video content;

[0203] The sending the optimization suggestion information for the initial video to the terminal device so that the terminal device displays the optimization suggestion information for the initial video on a human-computer interaction interface includes:

[0204] Optimization suggestion information for the initial video is sent to the terminal device, so that the terminal device displays optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video on the human-computer interaction interface, and displays the initial optimized content corresponding to the target video content.

[0205] For example, the optimization suggestion information not only includes optimization suggestions for the target video content itself, but may also include initial optimization content generated based on the optimization suggestions for the target video content. It is understandable that the optimization suggestion information may include specific modification suggestions, as well as preliminary optimization results for these modification suggestions. Among them, when displaying the optimization suggestion information on the human-computer interaction interface, in addition to displaying the optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video, the initial optimization content corresponding to the target video content should also be displayed. In this way, users can more intuitively understand the specific implementation effects of the optimization suggestions, and thus better understand and apply these optimization suggestions.

[0206] After determining the target video content that needs to be optimized, the system will automatically generate initial optimized content for the target video content based on the optimization suggestions for the target video content. These initial optimized contents may include modified video clips, new background music, subtitles, etc. These initial optimized contents will be sent to the terminal device together with the optimization suggestions for the target video content.

[0207] Then, the server will send optimization suggestion information including optimization suggestions corresponding to the target use of the initial video and the corresponding initial optimization content to the terminal device. These optimization suggestion information will be displayed on the human-computer interaction interface. The user of the terminal device, such as a video editor or reviewer, can optimize the video according to these suggestions.

[0208] In some embodiments, the method further comprises:

[0209] Acquire a first new video generation request generated by a first trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device;

[0210] In response to the first new video generation request, adjusting the initial video according to the optimization suggestion information to generate a first optimized video;

[0211] The first optimized video is sent to the terminal device so that the terminal device displays the first optimized video on the human-computer interaction interface.

[0212] For example, when a user of a terminal device (such as a computer, a mobile phone, etc.) performs human-computer interaction, he may see some new video generation controls, such as buttons, sliders, etc., on the human-computer interaction interface. When the user operates these controls, such as clicking a button, sliding a slider, etc., these operations will generate a first new video generation request. The terminal device will send the first new video generation request to the server, and the server will receive the first new video generation request.

[0213] Then, after receiving the first new video generation request, the server will adjust the initial video according to the previously determined optimization suggestion information. This adjustment process may include modifying the content, editing, special effects, etc. of the video to meet the requirements of each optimization suggestion. After the adjustment, the server will generate a first optimized video, which is the first optimized version of the initial video.

[0214] Then, the server sends the first optimized video to the terminal device. The first optimized video will be displayed on the human-computer interaction interface of the terminal device. The user can watch the first optimized video on the human-computer interaction interface and further edit or share the first optimized video. In some embodiments, the method further includes:

[0215] Obtaining the edited first optimization suggestion sent by the terminal device, wherein the edited first optimization suggestion is generated by the terminal device in response to an edit request for the first optimization suggestion, wherein the edit request for the first optimization suggestion is generated by the terminal device based on a triggering operation of an edit control corresponding to the selected first optimization suggestion and input edit content, wherein an edit control corresponding to each of the optimization suggestions is displayed on a human-computer interaction interface of the terminal device for selection;

[0216] generating new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion;

[0217] Send new optimization content corresponding to the edited first optimization suggestion to the terminal device, so that the terminal device replaces the initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface with the new optimization content corresponding to the edited first optimization suggestion, so as to obtain updated optimization suggestion information.

[0218] First, the edited first optimization suggestion sent by the terminal device is obtained. On the terminal device, the user may perform an editing operation on the first optimization suggestion. This editing operation may be based on a triggering operation of an editing control corresponding to the first optimization suggestion, such as clicking a button, sliding a slider, etc., and input editing content. These editing operations will generate an edited first optimization suggestion, and the edited first optimization suggestion will be sent to the server.

[0219] Then, based on the edited first optimization suggestion, new optimization content corresponding to the edited first optimization suggestion is generated. After receiving the edited first optimization suggestion, the server generates new optimization content based on the suggestion. This process may include further modification or adjustment of the content, editing, special effects, etc. of the video to meet the user's editing needs.

[0220] Then, the server will send the new optimization content corresponding to the edited first optimization suggestion to the terminal device. This new content will be displayed on the human-computer interaction interface of the terminal device. The user can view the new optimization content on the interface and further edit or share the new optimization content. Among them, on the human-computer interaction interface, the user can see the initial optimization suggestion information, including the first optimization suggestion and its corresponding initial optimization content. When the server sends the new optimization content to the terminal device, the initial optimization content corresponding to the first optimization suggestion displayed on the human-computer interaction interface will be replaced by the new optimization content, thereby obtaining the updated optimization suggestion information.

[0221] The above embodiment describes how the server obtains and responds to the editing request of the terminal device, generates new optimized content based on the request, and then sends the new optimized content to the terminal device for display. This process can help users edit and optimize videos more carefully and see the optimization results in real time.

[0222] In some embodiments, the method further comprises:

[0223] Obtaining a second new video generation request generated by a second trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device, and obtaining the updated optimization suggestion information;

[0224] In response to the second new video generation request, adjusting the initial video according to the updated optimization suggestion information to generate a second optimized video;

[0225] The second optimized video is sent to the terminal device so that the terminal device displays the second optimized video on the human-computer interaction interface.

[0226] For example, on the terminal device, the user may edit the first optimization suggestion and then trigger the second trigger operation of the new video generation control again, such as clicking the new video generation control again after generating the updated optimization suggestion information, thereby generating a second new video generation request. At the same time, the user may also perform other editing or optimization operations on the initial video, resulting in changes to the updated optimization suggestion information. These changes will be sent to the server as new data.

[0227] After receiving the second new video generation request and the updated optimization suggestion information, the server will adjust the initial video according to the new optimization suggestion information. This process may include further modification or adjustment of the video content, editing, special effects, etc. to meet the user's new needs. After the adjustment, the system will generate a new second optimized video.

[0228] The server will send the second optimized video to the terminal device. The second optimized video will be displayed on the human-computer interaction interface of the terminal device. The user can watch this new second optimized video on the interface and further edit or share it.

[0229] The above embodiment describes how the server obtains and responds to the second new video generation request of the terminal device, adjusts the initial video based on the updated optimization suggestion information, and then sends the adjusted second optimized video to the terminal device for display. This process can help users to continuously edit and optimize videos according to their changing needs. In some embodiments, the updated optimization suggestion information also includes updated optimization suggestion information obtained by deleting the second optimization suggestion in the optimization suggestion information in response to a deletion request for the second optimization suggestion; the deletion request for the second optimization suggestion is generated based on the triggering operation of the deletion control corresponding to the selected second optimization suggestion, wherein a deletion control corresponding to each optimization suggestion is displayed on the human-computer interaction interface of the terminal device for selection.

[0230] For example, the updated optimization suggestion information may also include the processing result of the deletion request for the second optimization suggestion. This deletion request may be selected by the user of the terminal device according to the user's specific needs. Specifically, when the user is not satisfied with the second optimization suggestion or believes that it no longer meets the user's needs, the user can select the corresponding deletion control to perform an operation, such as clicking a "delete" button or selecting an "undo" option. This operation will generate a deletion request for the second optimization suggestion, which will be sent to the server.

[0231] Then, after receiving the deletion request of the second optimization suggestion, the server will delete it from the optimization suggestion information, thereby obtaining updated optimization suggestion information. This process may involve deleting the initial optimization content corresponding to the second optimization suggestion from the content displayed on the human-computer interaction interface, so as to provide the latest and most accurate optimization suggestion information to the user.

[0232] It should be noted that for each optimization suggestion, there may be a corresponding delete control for the user to select. These delete controls are displayed on the human-computer interaction interface and correspond to each optimization suggestion one by one. The user can select the corresponding delete control as needed to delete the optimization suggestion that the user no longer needs.

[0233] In this way, the server can dynamically update the optimization recommendation information according to the user's needs, thereby ensuring that the provided recommendations are the most accurate and useful. At the same time, it also enables users to more conveniently manage and edit their video content to achieve better video quality and effects.

[0234] All of the above technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described in detail here.

[0235] The embodiment of the present application receives an initial video sent by a terminal device and a video review request corresponding to the initial video; analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, the optimization suggestion information including optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video; sends the optimization suggestion information for the initial video to the terminal device, so that the terminal device displays the optimization suggestion information for the initial video on the human-computer interaction interface. The embodiment of the present application can provide effective optimization suggestion information for the initial video created by the user to guide the user to create a better quality video, thereby improving the efficiency and quality of video creation.

[0236] In order to better implement the video processing method of the embodiment of the present application, the embodiment of the present application also provides a video processing device. Fig.14 , Fig.14 The first structural diagram of the video processing device provided in the embodiment of the present application. The video processing device 300 may include:

[0237] An acquisition unit 310 is used to acquire an initial video and a video review request corresponding to the initial video through a human-computer interaction interface;

[0238] A first sending unit 320 is configured to send the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to a target purpose of the initial video;

[0239] The display unit 330 is used to obtain the optimization suggestion information for the initial video sent by the server, and display the optimization suggestion information for the initial video on the human-computer interaction interface.

[0240] In some embodiments, the first sending unit 320 is used to: send the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request, determines the target purpose of the initial video, and determines multiple candidate dimensions to be processed corresponding to the initial video according to the target purpose, wherein different purposes correspond to different candidate dimensions to be processed; so that the server obtains the video content under each of the multiple candidate dimensions in the initial video, and performs semantic analysis on the video content under each candidate dimension according to the optimization reference information corresponding to each of the multiple candidate dimensions, and determines whether the video content under each candidate dimension needs to be optimized; so that the server determines optimization suggestions for the target video content under the target dimension that needs to be optimized according to the optimization reference information corresponding to the target dimension that needs to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video content.

[0241] In some embodiments, the optimization suggestion information further includes initial optimized content corresponding to the target video content generated based on the optimization suggestion for the target video content;

[0242] When the display unit 330 displays the optimization suggestion information for the initial video on the human-computer interaction interface, it is used to: display on the human-computer interaction interface the optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video, and display the initial optimization content corresponding to the target video content.

[0243] In some embodiments, the display unit 330 is further used to: display a first optimized video on the human-computer interaction interface, where the first optimized video is generated by adjusting the initial video according to the optimization suggestion information.

[0244] In some embodiments, the display unit 330 is further used to display a new video generation control on the human-computer interaction interface;

[0245] The acquisition unit 310 is further configured to acquire a first new video generation request generated based on a first trigger operation of the new video generation control;

[0246] The first sending unit 320 is further configured to send the first new video generation request to the server, so that the server adjusts the initial video according to the optimization suggestion information in response to the first new video generation request to generate a first optimized video;

[0247] The display unit 330 is further used to obtain the first optimized video sent by the server and display the first optimized video on the human-computer interaction interface.

[0248] In some embodiments, the display unit 330 is further used to display an editing control corresponding to each optimization suggestion on the human-computer interaction interface;

[0249] The acquisition unit 310 is further configured to acquire an edit request for generating the first optimization suggestion based on a trigger operation of an edit control corresponding to the selected first optimization suggestion and input edit content, and generate an edited first optimization suggestion in response to the edit request for the first optimization suggestion;

[0250] The display unit 330 is further configured to replace the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface with the edited first optimization suggestion to obtain updated optimization suggestion information.

[0251] In some embodiments, the first sending unit 320 is further configured to send the edited first optimization suggestion to the server, so that the server generates new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion;

[0252] The acquisition unit 310 is further configured to acquire new optimization content corresponding to the edited first optimization suggestion sent by the server;

[0253] The display unit 330 is further used to replace the initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface with the new optimization content corresponding to the edited first optimization suggestion to obtain updated optimization suggestion information.

[0254] In some embodiments, the display unit 330 is further configured to display a cancel control corresponding to the edited first optimization suggestion on the human-computer interaction interface;

[0255] The acquisition unit 310 is further configured to acquire a cancellation request for generating the edited first optimization suggestion based on the triggering operation of the cancel control, and cancel the edited first optimization suggestion in response to the cancellation request;

[0256] The display unit 330 is further configured to restore the edited first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface as the first optimization suggestion.

[0257] In some embodiments, the display unit 330 is further configured to display a deletion control corresponding to each optimization suggestion on the human-computer interaction interface;

[0258] The acquisition unit 310 is further configured to acquire a deletion request for the second optimization suggestion generated based on a trigger operation of a deletion control corresponding to the selected second optimization suggestion;

[0259] The display unit 330 is further configured to delete the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface in response to a request to delete the second optimization suggestion, so as to obtain updated optimization suggestion information.

[0260] In some embodiments, the display unit 330 is further used to delete the initial optimization content corresponding to the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface in response to a deletion request of the second optimization suggestion, so as to obtain updated optimization suggestion information.

[0261] In some embodiments, the display unit 330 is further used to: display a second optimized video on the human-computer interaction interface, where the second optimized video is generated by adjusting the initial video according to the updated optimization suggestion information.

[0262] In some embodiments, the display unit 330 is further used to display a new video generation control on the human-computer interaction interface;

[0263] The acquisition unit 310 is further configured to acquire a second new video generation request generated based on a second trigger operation of the new video generation control;

[0264] The first sending unit 320 is further configured to send the second new video generation request and the updated optimization suggestion information to the server, so that the server responds to the second new video generation request and adjusts the initial video according to the updated optimization suggestion information to generate a second optimized video;

[0265] The display unit 330 is further used to obtain the second optimized video sent by the server and display the second optimized video on the human-computer interaction interface.

[0266] The present application embodiment also provides another video processing device. Fig.15 , Fig.15 A second structural diagram of a video processing device provided in an embodiment of the present application. The video processing device 400 may include:

[0267] The receiving unit 410 is configured to receive an initial video sent by a terminal device and a video review request corresponding to the initial video;

[0268] The processing unit 420 is configured to analyze the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under target dimensions to be optimized corresponding to the target purpose of the initial video;

[0269] The second sending unit 430 is used to send optimization suggestion information for the initial video to the terminal device, so that the terminal device displays the optimization suggestion information for the initial video on the human-computer interaction interface.

[0270] In some embodiments, the processing unit 420 is used to: analyze the video content of the initial video in response to the video review request to determine the target purpose of the initial video; determine multiple candidate dimensions to be processed corresponding to the initial video according to the target purpose, wherein different purposes correspond to different candidate dimensions to be processed; obtain the video content under each of the multiple candidate dimensions in the initial video; perform semantic analysis on the video content under each candidate dimension according to the optimization reference information corresponding to each of the multiple candidate dimensions, and determine whether the video content under each candidate dimension needs to be optimized; for the target video content under the target dimension that needs to be optimized, determine optimization suggestions for the target video content according to the optimization reference information corresponding to the target dimension that needs to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video content.

[0271] In some embodiments, the optimization suggestion information further includes initial optimized content corresponding to the target video content generated based on the optimization suggestion for the target video content;

[0272] The second sending unit 430 is used to send optimization suggestion information for the initial video to the terminal device, so that the terminal device displays optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video on the human-computer interaction interface, and displays the initial optimized content corresponding to the target video content.

[0273] In some embodiments, the receiving unit 410 is further used to obtain a first new video generation request generated by a first trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device;

[0274] The processing unit 420 is further configured to, in response to the first new video generation request, adjust the initial video according to the optimization suggestion information to generate a first optimized video;

[0275] The second sending unit 430 is further used to send the first optimized video to the terminal device, so that the terminal device displays the first optimized video on the human-computer interaction interface.

[0276] In some embodiments, the receiving unit 410 is further used to obtain the edited first optimization suggestion sent by the terminal device, wherein the edited first optimization suggestion is generated by the terminal device in response to an edit request of the first optimization suggestion, and the edit request of the first optimization suggestion is generated by the terminal device based on a triggering operation of an edit control corresponding to the selected first optimization suggestion and input edit content, wherein an edit control corresponding to each of the optimization suggestions is displayed on the human-computer interaction interface of the terminal device for selection;

[0277] The processing unit 420 is further configured to generate new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion;

[0278] The second sending unit 430 is also used to send new optimization content corresponding to the edited first optimization suggestion to the terminal device, so that the terminal device replaces the initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface with the new optimization content corresponding to the edited first optimization suggestion, so as to obtain updated optimization suggestion information.

[0279] In some embodiments, the receiving unit 410 is further used to obtain a second new video generation request generated by a second trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device, and to obtain the updated optimization suggestion information;

[0280] The processing unit 420 is further configured to, in response to the second new video generation request, adjust the initial video according to the updated optimization suggestion information to generate a second optimized video;

[0281] The second sending unit 430 is further used to send the second optimized video to the terminal device, so that the terminal device displays the second optimized video on the human-computer interaction interface.

[0282] In some embodiments, the updated optimization suggestion information also includes updated optimization suggestion information obtained after deleting the second optimization suggestion in the optimization suggestion information in response to a deletion request for the second optimization suggestion; the deletion request for the second optimization suggestion is generated based on a triggering operation of a deletion control corresponding to the selected second optimization suggestion, wherein a deletion control corresponding to each optimization suggestion is displayed on the human-computer interaction interface of the terminal device for selection.

[0283] Each unit in the above video processing device can be implemented in whole or in part by software, hardware or a combination thereof. Each unit can be embedded in or independent of a processor in a terminal device in the form of hardware, or can be stored in a memory in a terminal device in the form of software, so that the processor can call and execute the corresponding operations of each unit.

[0284] The video processing device 300 may be integrated in a terminal device that has a storage device and a processor installed therein and has computing capabilities, or the video processing device 300 is the terminal device.

[0285] The video processing device 400 may be integrated into a server having a storage device and a processor installed therein and having computing capabilities, or the video processing device 400 may be the server.

[0286] In some embodiments, the present application further provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0287] In some embodiments, Fig.16 As shown, Fig.16Another structural diagram of a computer device provided in an embodiment of the present application, the computer device 500 also includes a processor 501 having one or more processing cores, a memory 320 having one or more computer-readable storage media, and a computer program stored in the memory 320 and executable on the processor. The processor 501 is electrically connected to the memory 320. Those skilled in the art will appreciate that the computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown, or combine certain components, or arrange components differently.

[0288] The processor 501 is the control center of the computer device 500. It uses various interfaces and lines to connect the various parts of the entire computer device 500, executes various functions of the computer device 500 and processes data by running or loading software programs and / or modules stored in the memory 320, and calling data stored in the memory 320, thereby monitoring the computer device 500 as a whole.

[0289] Optionally, the computer device 500 can be a terminal device, and the processor 503 can call the software program and modules stored in the memory 502 to perform the following operations: obtain the initial video and the video review request corresponding to the initial video through the human-computer interaction interface; send the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, and the optimization suggestion information includes optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video; obtain the optimization suggestion information for the initial video sent by the server, and display the optimization suggestion information for the initial video on the human-computer interaction interface.

[0290] Optionally, the computer device 500 can be a server, and the processor 503 can call the software program and modules stored in the memory 502 to perform the following operations: receiving an initial video sent by a terminal device and a video review request corresponding to the initial video; analyzing the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to the target purpose of the initial video; and sending the optimization suggestion information for the initial video to the terminal device so that the terminal device displays the optimization suggestion information for the initial video on the human-computer interaction interface.

[0291] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0292] In some embodiments, Fig.16 As shown, the computer device 500 further includes: a radio frequency circuit 506, an audio circuit 507 and a power supply 508. The processor 501 is electrically connected to the memory 320, the feedback module 502, the sensor 503, the radio frequency circuit 506, the audio circuit 507 and the power supply 508 respectively. Those skilled in the art can understand that Fig.16 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0293] The radio frequency circuit 506 may be used to send and receive radio frequency signals, so as to establish wireless communication with a network device or other computer devices through wireless communication, and to send and receive signals between the network device or other computer devices.

[0294] The audio circuit 507 can be used to provide an audio interface between the user and the computer device through a speaker and a microphone. The audio circuit 507 can transmit the electrical signal converted from the received audio data to the speaker, which is converted into a sound signal for output; on the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit 507 and converted into audio data, and then the audio data is output to the processor 501 for processing, and then sent to another computer device through the radio frequency circuit 506, or the audio data is output to the memory for further processing. The audio circuit 507 may also include an earphone jack to provide communication between an external headset and the computer device.

[0295] The power supply 508 is used to supply power to various components of the computer device 500 .

[0296] although Fig.16 Not shown, the computer device 500 may also include a camera, a wireless fidelity module, a Bluetooth module, an input module, etc., which will not be described in detail here.

[0297] In some embodiments, the present application further provides a computer-readable storage medium for storing a computer program. The computer-readable storage medium can be applied to a terminal device or a server, and the computer program enables the terminal device or the server to execute the corresponding process in the video processing method in the embodiment of the present application, which will not be described here for the sake of brevity.

[0298] In some embodiments, the present application further provides a computer program product, which includes a computer program, and the computer program is stored in a computer-readable storage medium. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the corresponding process in the video processing method in the embodiment of the present application, which will not be described here for the sake of brevity.

[0299] The present application also provides a computer program, which includes a computer program, and the computer program is stored in a computer-readable storage medium. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the corresponding process in the video processing method in the embodiment of the present application, which will not be described in detail for the sake of brevity.

[0300] It should be understood that the processor of the embodiment of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by the hardware integrated logic circuit or software instructions in the processor. The above processor can be a general processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor are combined and performed. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, and other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0301] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0302] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0303] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0304] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0305] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0306] In addition, each functional unit in the embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0307] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks or optical disks.

[0308] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A video processing method, characterized in that: The method comprises: Obtaining an initial video and a video review request corresponding to the initial video through a human-computer interaction interface; Sending the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under target dimensions to be optimized corresponding to the target purpose of the initial video; The optimization suggestion information for the initial video sent by the server is obtained, and the optimization suggestion information for the initial video is displayed on the human-computer interaction interface.

2. The video processing method according to claim 1, characterized in that: The sending the initial video and the video review request to the server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, includes: Sending the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request, determines the target purpose of the initial video, and determines a plurality of candidate dimensions to be processed corresponding to the initial video according to the target purpose, wherein different purposes correspond to different candidate dimensions to be processed; The server obtains the video content under each of the multiple candidate dimensions in the initial video, and performs semantic analysis on the video content under each candidate dimension according to the optimization reference information corresponding to each of the multiple candidate dimensions, and determines whether the video content under each candidate dimension needs to be optimized; The server determines optimization suggestions for the target video content under the target dimension to be optimized according to the optimization reference information corresponding to the target dimension to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video contents.

3. The video processing method according to claim 2, characterized in that: The optimization suggestion information also includes initial optimization content corresponding to the target video content generated based on the optimization suggestion for the target video content; The displaying of optimization suggestion information for the initial video on the human-computer interaction interface includes: On the human-computer interaction interface, optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video are displayed, and initial optimization content corresponding to the target video content is displayed.

4. The video processing method according to any one of claims 1 to 3, characterized in that: The method further comprises: A first optimized video is displayed on the human-computer interaction interface, where the first optimized video is generated by adjusting the initial video according to the optimization suggestion information.

5. The video processing method according to claim 4, characterized in that: The displaying of the first optimized video on the human-computer interaction interface includes: Displaying a new video generation control on the human-computer interaction interface; Obtaining a first new video generation request generated based on a first trigger operation of the new video generation control, and sending the first new video generation request to the server, so that the server adjusts the initial video according to the optimization suggestion information in response to the first new video generation request to generate a first optimized video; The first optimized video sent by the server is obtained, and the first optimized video is displayed on the human-computer interaction interface.

6. The video processing method according to claim 3, characterized in that: The method further comprises: Displaying an editing control corresponding to each of the optimization suggestions on the human-computer interaction interface; Obtaining an edit request for generating the first optimization suggestion based on a trigger operation of an edit control corresponding to the selected first optimization suggestion and input edit content; In response to the edit request of the first optimization suggestion, generating an edited first optimization suggestion; The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes: The first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is replaced with the edited first optimization suggestion to obtain updated optimization suggestion information.

7. The video processing method according to claim 6, characterized in that: The method further comprises: Sending the edited first optimization suggestion to the server, so that the server generates new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion; Acquire new optimization content corresponding to the edited first optimization suggestion sent by the server; The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes: The initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is replaced with the new optimization content corresponding to the edited first optimization suggestion to obtain updated optimization suggestion information.

8. The video processing method according to claim 6, characterized in that: The method further comprises: Displaying a cancel control corresponding to the edited first optimization suggestion on the human-computer interaction interface; Obtaining a cancellation request for generating the edited first optimization suggestion based on the triggering operation of the cancel control; In response to the cancellation request, canceling the edited first optimization suggestion; The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes: The edited first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is restored as the first optimization suggestion.

9. The video processing method according to claim 3, characterized in that: The method further comprises: Displaying a deletion control corresponding to each of the optimization suggestions on the human-computer interaction interface; Obtaining a deletion request for the second optimization suggestion generated based on a triggering operation of a deletion control corresponding to the selected second optimization suggestion; The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes: In response to a request to delete the second optimization suggestion, the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is deleted to obtain updated optimization suggestion information.

10. The video processing method according to claim 9, characterized in that: The method further comprises: The displaying of optimization suggestion information for the initial video on the human-computer interaction interface further includes: In response to a request to delete the second optimization suggestion, initial optimization content corresponding to the second optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface is deleted to obtain updated optimization suggestion information.

11. The video processing method according to any one of claims 6 to 10, characterized in that: The method further comprises: A second optimized video is displayed on the human-computer interaction interface, where the second optimized video is generated by adjusting the initial video according to the updated optimization suggestion information.

12. The video processing method according to claim 11, characterized in that: The displaying of the second optimized video on the human-computer interaction interface includes: Displaying a new video generation control on the human-computer interaction interface; Obtaining a second new video generation request generated based on a second trigger operation of the new video generation control, and sending the second new video generation request and the updated optimization suggestion information to the server, so that the server responds to the second new video generation request and adjusts the initial video according to the updated optimization suggestion information to generate a second optimized video; The second optimized video sent by the server is obtained, and the second optimized video is displayed on the human-computer interaction interface.

13. A video processing method, characterized in that: The method comprises: Receiving an initial video sent by a terminal device and a video review request corresponding to the initial video; In response to the video review request, analyzing the video content of the initial video to obtain optimization suggestion information for the initial video, the optimization suggestion information including optimization suggestions for target video content under target dimensions to be optimized corresponding to the target purpose of the initial video; Sending optimization suggestion information for the initial video to the terminal device so that the terminal device displays the optimization suggestion information for the initial video on a human-computer interaction interface.

14. The video processing method according to claim 13, characterized in that: The step of analyzing the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video includes: In response to the video review request, analyzing the video content of the initial video to determine the target use of the initial video; Determining, according to the target purpose, a plurality of candidate dimensions to be processed corresponding to the initial video, wherein different purposes correspond to different candidate dimensions to be processed; Obtaining video content in each of the multiple candidate dimensions in the initial video; According to the optimization reference information corresponding to each candidate dimension among the multiple candidate dimensions, semantic analysis is performed on the video content under each candidate dimension to determine whether the video content under each candidate dimension needs to be optimized; For the target video content under the determined target dimension to be optimized, optimization suggestions for the target video content are determined according to the optimization reference information corresponding to the target dimension to be optimized, wherein the target dimension is at least one of the multiple candidate dimensions, and different target dimensions correspond to different target video contents.

15. The video processing method according to claim 14, characterized in that: The optimization suggestion information also includes initial optimization content corresponding to the target video content generated based on the optimization suggestion for the target video content; The sending the optimization suggestion information for the initial video to the terminal device so that the terminal device displays the optimization suggestion information for the initial video on a human-computer interaction interface includes: Optimization suggestion information for the initial video is sent to the terminal device, so that the terminal device displays optimization suggestions for the target video content under the target dimension to be optimized corresponding to the target purpose of the initial video on the human-computer interaction interface, and displays the initial optimized content corresponding to the target video content.

16. The video processing method according to any one of claims 13 to 15, characterized in that: The method further comprises: Acquire a first new video generation request generated by a first trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device; In response to the first new video generation request, adjusting the initial video according to the optimization suggestion information to generate a first optimized video; The first optimized video is sent to the terminal device so that the terminal device displays the first optimized video on the human-computer interaction interface.

17. The video processing method according to claim 15, characterized in that: The method further comprises: Obtaining the edited first optimization suggestion sent by the terminal device, wherein the edited first optimization suggestion is generated by the terminal device in response to an edit request for the first optimization suggestion, wherein the edit request for the first optimization suggestion is generated by the terminal device based on a triggering operation of an edit control corresponding to the selected first optimization suggestion and input edit content, wherein an edit control corresponding to each of the optimization suggestions is displayed on a human-computer interaction interface of the terminal device for selection; generating new optimization content corresponding to the edited first optimization suggestion based on the edited first optimization suggestion; Send new optimization content corresponding to the edited first optimization suggestion to the terminal device, so that the terminal device replaces the initial optimization content corresponding to the first optimization suggestion in the optimization suggestion information displayed on the human-computer interaction interface with the new optimization content corresponding to the edited first optimization suggestion, so as to obtain updated optimization suggestion information.

18. The video processing method according to claim 17, characterized in that: The method further comprises: Obtaining a second new video generation request generated by a second trigger operation of a new video generation control displayed on the human-computer interaction interface and sent by the terminal device, and obtaining the updated optimization suggestion information; In response to the second new video generation request, adjusting the initial video according to the updated optimization suggestion information to generate a second optimized video; The second optimized video is sent to the terminal device so that the terminal device displays the second optimized video on the human-computer interaction interface.

19. The video processing method according to claim 18, characterized in that: The updated optimization suggestion information also includes updated optimization suggestion information obtained by deleting the second optimization suggestion in the optimization suggestion information in response to a request to delete the second optimization suggestion; The request to delete the second optimization suggestion is generated based on a triggering operation of a deletion control corresponding to the selected second optimization suggestion, wherein a deletion control corresponding to each of the optimization suggestions is displayed on the human-computer interaction interface of the terminal device for selection.

20. A video processing device, characterized in that: The device comprises: An acquisition unit, configured to acquire an initial video and a video review request corresponding to the initial video through a human-computer interaction interface; A first sending unit is used to send the initial video and the video review request to a server, so that the server analyzes the video content of the initial video in response to the video review request to obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to a target purpose of the initial video; A display unit is used to obtain the optimization suggestion information for the initial video sent by the server, and display the optimization suggestion information for the initial video on the human-computer interaction interface.

21. A video processing device, characterized in that: The device comprises: A receiving unit, configured to receive an initial video sent by a terminal device and a video review request corresponding to the initial video; A processing unit, configured to analyze the video content of the initial video in response to the video review request, and obtain optimization suggestion information for the initial video, wherein the optimization suggestion information includes optimization suggestions for target video content under a target dimension to be optimized corresponding to a target purpose of the initial video; The second sending unit is used to send optimization suggestion information for the initial video to the terminal device, so that the terminal device displays the optimization suggestion information for the initial video on the human-computer interaction interface.

22. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the video processing method according to any one of claims 1 to 12 or the video processing method according to any one of claims 13 to 19.

23. A computer device, characterized in that: The computer device includes a processor and a memory, wherein a computer program is stored in the memory, and the processor is used to execute the video processing method described in any one of claims 1 to 12 or the video processing method described in any one of claims 13 to 19 by calling the computer program stored in the memory.

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