Video generation method and electronic device

Abstract

The application provides a video generation method, comprising: determining a target video segment meeting a predetermined condition in a first video file; determining target content to be modified in first text content based on label information of the target video segment; adjusting the target content to obtain second text content; and generating a second video file from the second text content, wherein a random seed of the second video file is the same as that of the first video file. Meanwhile, the application also provides an electronic device.

Description

Technical Field

[0001] This application relates to content processing technology, and more particularly to a video generation method and electronic device. Background Technology

[0002] Currently, when adjusting text content, the usual method is to manually read the text repeatedly to adjust any content that does not meet the requirements. This method of adjusting text is highly subjective, and repeated adjustments may not necessarily yield satisfactory results. It is not only inefficient but also produces low-quality adjustments. Summary of the Invention

[0003] In view of this, embodiments of this application aim to provide a video generation method and an electronic device.

[0004] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0005] According to one aspect of this application, a video generation method is provided, comprising:

[0006] Identify the target video segment in the first video file that meets the predetermined conditions;

[0007] Based on the tag information of the target video segment, the target content to be modified is determined in the first text content;

[0008] Adjust the target content to obtain the second text content;

[0009] The second text content is used to generate a second video file, wherein the random seed of the second video file is the same as that of the first video file.

[0010] In the above scheme, determining the target content to be modified in the first text content based on the tag information of the target video segment includes:

[0011] Based on the tag information of the target video segment, search for the first target content corresponding to the target video segment in the first text content;

[0012] Extract the second target content corresponding to the target video segment from the first target content;

[0013] The second target content is determined as the target content to be modified in the first text content.

[0014] In the above scheme, before determining the target content to be modified in the first text content based on the tag information of the target video segment, the method further includes:

[0015] Based on the random seed corresponding to each video segment in the first video file, establish the correspondence between each video segment in the first video file and the target content in the first text content;

[0016] Based on the aforementioned correspondence, tag information is generated for each video segment.

[0017] In the above scheme, generating a second video file from the second text content includes:

[0018] Obtain the random seed corresponding to each video segment in the first video file;

[0019] The AIGC (Artificial Intelligence Content Creation) technology uses the random seed to generate the second video file corresponding to the second text content.

[0020] In the above scheme, before playing the first video file, the method further includes:

[0021] The first text content is used to generate the corresponding first video file using AIGC (Artificial Intelligence Generated Content) technology.

[0022] In the above scheme, before adjusting the target content, the method further includes:

[0023] The target content is displayed in the first text content using a target strategy, so that the display method of the target content is different from other content in the first text content.

[0024] In the above scheme, adjusting the target content to obtain the second text content includes:

[0025] Receive modification operations for the target content;

[0026] Based on the modification operation, the target content is modified in the first text content to obtain the second text content.

[0027] In the above scheme, determining the target video segment in the first video file that meets the predetermined conditions includes:

[0028] During the playback of the first video file, a marking instruction for the target video segment in the first video file is received;

[0029] The target video segment is marked based on the marking instruction, and the marking indicates that the target video segment meets a predetermined condition.

[0030] In the above scheme, determining the target video segment in the first video file that meets the predetermined conditions includes:

[0031] When the first video file is generated, each video segment in the first video file is filtered according to predetermined conditions to obtain target video segments that meet the predetermined conditions.

[0032] According to another aspect of this application, an electronic device is provided, comprising:

[0033] The determining unit is configured to determine a target video segment in a first video file that meets predetermined conditions; and to determine target content to be modified in a first text content based on the tag information of the target video segment.

[0034] An adjustment unit is used to adjust the target content to obtain the second text content;

[0035] The generation unit is configured to generate a second video file from the second text content, wherein the random seed of the second video file is the same as that of the first video file.

[0036] The video generation method and electronic device provided in this application convert non-intuitive text content into video files, allowing users to locate target content in the text content that does not meet predetermined conditions by watching the video. This not only improves the accuracy of locating text content, but also improves the quality and efficiency of modifying text content, enabling the text content to be modified in a better direction. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the implementation of the video generation method in this application. Figure 1 ;

[0038] Figure 2 This is a flowchart illustrating the implementation of the video generation method in this application. Figure 2 ;

[0039] Figure 3 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 1 ;

[0040] Figure 4 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 2 . Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. The steps shown in the flowcharts can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0042] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] Figure 1 This is a flowchart illustrating the implementation of the video generation method in this application. Figure 1 This method can be applied to electronic devices with displays, such as computers and mobile phones. Figure 1 As shown, it includes:

[0044] Step 101: Determine the target video segment in the first video file that meets the predetermined conditions;

[0045] In this application, the electronic device can receive a marking instruction for a target video segment in the first video file during the playback of the first video file; and mark the target video segment based on the marking instruction, wherein the marking indicates that the target video segment meets a predetermined condition.

[0046] Here, the marking instruction includes, but is not limited to, receiving a pause instruction or search instruction (such as the name of a specific object or the name of a specific scene) from the user during the playback of the first video file.

[0047] In this application, the electronic device can also, when generating the first video file, filter each video segment in the first video file according to predetermined conditions to obtain a target video segment that meets the predetermined conditions.

[0048] Here, the predetermined conditions include, but are not limited to, logical conditions between video segments in the video, and violation conditions of video segments in the video.

[0049] In this application, before determining the target video segment in the first video file that meets the predetermined conditions, the electronic device can also determine the first text content and generate the first video file from the first text content.

[0050] Here, the electronic device can determine the first text content based on the user's input command or based on the text access time.

[0051] For example, the text content that was most recently opened can be identified as the first text content.

[0052] In this application, when the electronic device generates a first video file from the first text content, it can utilize Artificial Intelligence Generated Content (AIGC) technology to generate the first video file from the first text content. Alternatively, it can utilize Chat Generative Pre-trained Transformer (Chat GPT) technology to generate the first video file from the first text content.

[0053] Step 102: Based on the tag information of the target video segment, determine the target content to be modified in the first text content;

[0054] Here, each video segment in the first video file corresponds to a random seed, and the random seed for each video segment is different. Based on the random seed corresponding to each video segment in the first video file, the electronic device can establish a correspondence between each video segment in the first video file and the target content in the first text content; based on the correspondence, it can generate tag information for each video segment.

[0055] Here, the tag information can indicate which video segment in the video corresponds to which part of the text content.

[0056] In this application, the electronic device can search for the first target content corresponding to the target video segment in the first text content based on the tag information of the target video segment; then extract the second target content corresponding to the target video segment from the first target content; and determine the second target content as the target content to be modified in the first text content.

[0057] Here, the first target content corresponding to the target video segment may include several paragraphs, and only a few sentences in these paragraphs may be truly related to the target video segment. In order to reduce computational costs, in one implementation example of this application, the electronic device can generate keywords based on the target video segment and extract keywords from the first target content to obtain the second target content.

[0058] Step 103: Adjust the target content to obtain the second text content;

[0059] In this application, the electronic device can receive modification operations on the target content; based on the modification operations, it modifies the target content in the first text content to obtain the second text content.

[0060] Here, the modification operations include, but are not limited to, adjusting the text position of the target content within the first text content; re-editing the text content of the target content; and modifying the text logic within the target content.

[0061] In this application, before adjusting the target content, the electronic device can also display the target content in the first text content through a target strategy, so that the display method of the target content is different from other content in the first text content.

[0062] Here, the electronic device can adjust the brightness value of the target content to make its display brightness higher than that of other content in the first text content. For example, it can highlight the target content.

[0063] Here, the electronic device can also adjust the display frequency of the target content to make it appear more frequently than other content in the first text content. For example, it can make the target content appear to jump around.

[0064] Here, the electronic device can also adjust the font parameters of the target content to make the font parameters of the target content larger than those of other content in the first text content. For example, it can make the target content bolder and larger.

[0065] Step 104: Generate a second video file from the second text content, wherein the random seed of the second video file is the same as that of the first video file.

[0066] In this application, the electronic device can obtain a random seed corresponding to each video segment in the first video file; and use AIGC technology or Chat GPT technology to generate the corresponding second video file from the second text content using the random seed. This ensures that the generated video file contains identical content for all video segments except for the modified target video segment.

[0067] This application generates video files from non-intuitive text content, and uses these video files to effectively locate the target content to be modified within the text. This not only improves the accuracy and speed of locating the target content within the text, but also enhances the quality and efficiency of text content modification, leading to a more optimized approach to text content revision. Furthermore, there are no restrictions on the users; they can be either the creators of the text content or reviewers unrelated to the text content.

[0068] Figure 2This is a flowchart illustrating the implementation of the video generation method in this application. Figure 2 ,like Figure 2 As shown, the method includes:

[0069] Step 201: Determine the text content;

[0070] Here, users can write relevant texts according to a plan and obtain text content. These users include, but are not limited to, screenwriters, teachers, and writers.

[0071] Step 202: Input the text content into the AIGC model, and use the AIGC model to generate a video file from the text content.

[0072] Here, during the video generation process, each video segment in the video file can be associated with its corresponding content in the text. That is, which parts of the text content generated the corresponding video segments in the video file, denoted as L.

[0073] Step 203: Determine whether the video file meets the predetermined conditions.

[0074] Here, during the playback of a video file, users can intuitively determine whether the logical structure and / or core content between each video segment in the video file meet the predetermined conditions by watching the video. They can also input instructions to the electronic device, which can then determine whether the video file meets the predetermined conditions based on the instructions.

[0075] Here, if the video file meets the predetermined conditions, proceed to step 204; if the video file does not meet the predetermined conditions, proceed to step 207.

[0076] Step 204: Mark the target video segments in the video file that meet the predetermined conditions;

[0077] Here, when a user is watching a video file, if they feel that a certain video segment does not meet their requirements, they input a marking command into the electronic device. The electronic device then marks that segment of the video file according to the marking command. Simultaneously, it marks in L which sentences generated that video segment.

[0078] Step 205: Highlight the target content corresponding to the target video clip in the text content so that the target content is displayed differently from other content in the text content.

[0079] Step 206: Adjust the highlighted target content to obtain the text content again;

[0080] Here, users can re-edit the highlighted target content or adjust the segment position of the target content within the video file.

[0081] Here, after adjusting the text content, the electronic device can also regenerate the video file from the adjusted text content, that is, repeat steps 201-206 until the final generated text content meets the requirements.

[0082] Here, the electronic device uses the same random seed each time it generates a video file, so that the content of other video segments is the same in each generated video file, except for the target video segment that is modified.

[0083] Step 207, End.

[0084] The video generation method provided in this application is a way to convert non-intuitive text content into video files, allowing users to locate target content in the text content that does not meet predetermined conditions by watching the video. This not only improves the accuracy of locating text content, but also improves the quality and efficiency of modifying text content, enabling the text content to be modified in a better direction.

[0085] Figure 3 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 1 ,like Figure 3 As shown, the electronic device includes:

[0086] The determining unit 301 is used to determine a target video segment in a first video file that meets predetermined conditions; and to determine the target content to be modified in the first text content based on the tag information of the target video segment.

[0087] Adjustment unit 302 is used to adjust the target content to obtain the second text content;

[0088] The generation unit 303 is used to generate a second video file from the second text content, wherein the random seed of the second video file is the same as that of the first video file.

[0089] In a preferred embodiment, the electronic device further includes:

[0090] The lookup unit 304 is used to look up the first target content corresponding to the target video segment in the first text content based on the tag information of the target video segment;

[0091] Extraction unit 305 is used to extract second target content corresponding to the target video segment from the first target content;

[0092] The determining unit 301 is specifically used to determine the second target content as the target content to be modified in the first text content.

[0093] In a preferred embodiment, the electronic device further includes:

[0094] Establishment unit 306 is used to establish a correspondence between each video segment in the first video file and the target content in the first text content based on the random seed corresponding to each video segment in the first video file.

[0095] The generation unit 303 is specifically used to generate tag information for each video segment based on the correspondence.

[0096] In a preferred embodiment, the electronic device further includes:

[0097] Acquisition unit 307 is used to acquire a random seed corresponding to each video segment in the first video file;

[0098] The generation unit 303 is specifically used to generate the second video file corresponding to the second text content using the random seed through AIGC (Artificial Intelligence Content Creation) technology.

[0099] In the preferred embodiment, the generation unit 303 is further configured to use AIGC (Artificial Intelligence Content Creation) technology to generate the first video file corresponding to the first text content.

[0100] In a preferred embodiment, the electronic device further includes:

[0101] Display unit 308 is used to display the target content in the first text content through a target strategy, so that the display method of the target content is different from other content in the first text content.

[0102] In a preferred embodiment, the electronic device further includes:

[0103] The receiving unit 309 is used to receive modification operations on the target content;

[0104] The adjustment unit 302 is specifically used to modify the target content in the first text content based on the modification operation to obtain the second text content.

[0105] In a preferred embodiment, the receiving unit 309 is further configured to receive a marking instruction for a target video segment in the first video file during the playback of the first video file;

[0106] In a preferred embodiment, the electronic device further includes:

[0107] The marking unit 310 is used to mark the target video segment based on the marking instruction, wherein the marking indicates that the target video segment meets a predetermined condition.

[0108] In a preferred embodiment, the electronic device further includes:

[0109] The filtering unit 311 is used to filter each video segment in the first video file according to predetermined conditions when the first video file is generated, so as to obtain a target video segment that meets the predetermined conditions.

[0110] It should be noted that the electronic device provided in the above embodiments is only illustrated by the division of the above program modules when generating video. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the electronic device provided in the above embodiments and the video generation method embodiments provided above belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0111] This application also provides an electronic device, which includes: a processor and a memory for storing a computer program capable of running on the processor.

[0112] When the processor runs the computer program, it executes any one of the method steps in the video generation method described above.

[0113] Figure 4 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 2 Electronic device 400 can be a mobile phone, computer, digital broadcasting terminal, information transceiver, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc. Figure 4 The illustrated electronic device 400 includes at least one processor 401, a memory 402, at least one network interface 404, and a user interface 403. The various components in the electronic device 400 are coupled together via a bus system 405. It is understood that the bus system 405 is used to implement communication between these components. In addition to a data bus, the bus system 405 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 4 The general designated all buses as Bus System 405.

[0114] The user interface 403 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0115] It is understood that memory 402 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 402 described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0116] In this embodiment, the memory 402 is used to store various types of data to support the operation of the electronic device 400. Examples of such data include: any computer program used to operate on the electronic device 400, such as the operating system 4021 and application program 4022; contact data; phonebook data; messages; pictures; audio, etc. The operating system 4021 includes various system programs, such as the framework layer, core library layer, driver layer, etc., used to implement various basic services and handle hardware-based tasks. The application program 4022 may include various applications, such as a media player, browser, etc., used to implement various application services. Programs implementing the methods of this embodiment may be included in the application program 4022.

[0117] The methods disclosed in the embodiments of this application can be applied to processor 401, or implemented by processor 401. Processor 401 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 401 or by instructions in the form of software. The processor 401 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 401 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 402. Processor 401 reads the information in memory 402 and combines its hardware to complete the steps of the aforementioned method.

[0118] In an exemplary embodiment, the electronic device 400 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0119] In an exemplary embodiment, this application also provides a computer-readable storage medium, such as a memory 402 including a computer program, which can be executed by a processor 801 of an electronic device 400 to complete the steps described in the aforementioned method. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM; it may also be various devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0120] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs any of the method steps in the above-described processing method.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0122] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0123] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0124] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0125] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0126] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A video generation method based on AIGC (Artificial Intelligence Generated Content) technology, comprising: Identify the target video segment in the first video file that meets the predetermined conditions; The first video file was generated based on the first text content; Based on the tag information of the target video segment, the target content to be modified is determined in the first text content; Based on the modification operation, the target content is modified in the first text content to obtain the second text content; The second text content is used to generate a second video file, wherein the random seed of the second video file is the same as that of the first video file; The step of determining the target video segment in the first video file that meets the predetermined conditions includes: During the playback of the first video file, a marking instruction for the target video segment in the first video file is received; The target video segment is marked based on the marking instruction, and the marking indicates that the target video segment meets the predetermined conditions; the predetermined conditions include at least: logical conditions between video segments in the first video file, or violation conditions of video segments in the first video file.

2. The method according to claim 1, wherein, The step of determining the target content to be modified in the first text content based on the tag information of the target video segment includes: Based on the tag information of the target video segment, search for the first target content corresponding to the target video segment in the first text content; Extract the second target content corresponding to the target video segment from the first target content; The second target content is determined as the target content to be modified in the first text content.

3. The method according to claim 1 or 2, wherein, Before determining the target content to be modified in the first text content based on the tag information of the target video segment, the method further includes: Based on the random seed corresponding to each video segment in the first video file, establish the correspondence between each video segment in the first video file and the target content in the first text content; Based on the aforementioned correspondence, tag information is generated for each video segment.

4. The method according to claim 1, wherein, The step of generating a second video file from the second text content includes: Obtain the random seed corresponding to each video segment in the first video file; The AIGC (Artificial Intelligence Content Creation) technology uses the random seed to generate the second video file corresponding to the second text content.

5. The method according to claim 1, wherein, Before determining the target video segment in the first video file that meets the predetermined conditions, the method further includes: The first text content is used to generate the corresponding first video file using AIGC (Artificial Intelligence Generated Content) technology.

6. The method according to claim 1, wherein, Before modifying the target content in the first text content based on the modification operation, the method further includes: The target content is displayed in the first text content using a target strategy, so that the display method of the target content is different from other content in the first text content.

7. The method according to claim 1, wherein, Before modifying the target content in the first text content based on the modification operation to obtain the second text content, the method further includes: Receive the modification operation for the target content.

8. The method according to claim 1, wherein, The determination of the target video segment in the first video file that meets the predetermined conditions includes: When the first video file is generated, each video segment in the first video file is filtered according to predetermined conditions to obtain target video segments that meet the predetermined conditions.

9. An electronic device, comprising: The determining unit is used to receive a marking instruction for a target video segment in the first video file during the playback of the first video file. The target video segment is marked based on the marking instruction, and the marking indicates that the target video segment meets a predetermined condition; The predetermined conditions include at least: logical conditions between video segments in the first video file, or violation conditions of video segments in the first video file; the first video file is generated based on first text content; and the method for determining the target content to be modified in the first text content based on the tag information of the target video segment. An adjustment unit is used to modify the target content in the first text content based on a modification operation to obtain the second text content; The generation unit is used to generate a second video file from the second text content, wherein the random seed of the second video file is the same as that of the first video file; the video file is generated based on AIGC (Artificial Intelligence Generated Content) technology.

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