Video generation method, device, system, computer device and storage medium

Abstract

The application discloses a video generation method. The method comprises the following steps: when receiving a personalized data acquisition request sent by a front end, acquiring a script matching rule and feature data of a user according to the request, the personalized data comprising an award obtained by the user participating in an activity and a script corresponding to the award; generating the personalized data according to the feature data and the script matching rule, and returning the personalized data to the front end; when receiving a target video description file sent by the front end, re-rendering a template video matched with the activity according to the target video description file to obtain a to-be-published video, and returning the to-be-published video to the front end. The application can generate a video in one key.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of video processing, and in particular to a video generation method and device, a computer device, and a storage medium. BACKGROUND

[0002] With the continuous increase of Internet access bandwidth and the popularity of smart terminals, video content has gradually become the main information carrier of various platforms (such as video platforms, social platforms, etc.). In the prior art, when a user wants to publish a video to a platform, the user needs to create a video first, and then can publish the created video to the platform. However, when the user creates a to-be-published video, the user needs to go through the processes of shooting, editing, and producing the video to obtain the to-be-published video, and the entire process is very cumbersome. SUMMARY

[0003] Therefore, the present application provides a video generation method, device, system, computer device, and computer readable storage medium to solve the problem that a very cumbersome process is needed to obtain a to-be-published video in the prior art.

[0004] The present application provides a video generation method, comprising:

[0005] When a personalized data acquisition request sent by a front end is received, text matching rules and feature data of a user are acquired according to the request, the personalized data comprising an award obtained by the user participating in an activity and a text corresponding to the award;

[0006] The personalized data is generated according to the feature data and the text matching rules, and the personalized data is returned to the front end;

[0007] When a target video description file sent by the front end is received, a template video matched with the activity is re-rendered according to the target video description file, a to-be-published video is obtained, and the to-be-published video is returned to the front end.

[0008] Optionally, the text matching rules are acquired according to the request, comprising:

[0009] Text matching rules matched with the activity information are acquired according to the activity information carried in the request, the activity information being used to determine an activity participated in by the user.

[0010] Optionally, the feature data comprises a plurality of pieces, the text matching rules comprise determination rules of awards and texts corresponding to each piece of feature data, and the personalized data is generated according to the feature data and the text matching rules, comprising:

[0011] It is determined according to the text matching rules whether each piece of feature data satisfies a corresponding determination rule.

[0012] If the current feature data satisfies the corresponding determination rule, an award and a script corresponding to the current feature data are obtained;

[0013] The personalized data is generated according to the awards and the scripts corresponding to all the feature data satisfying the determination rule

[0014] Optionally, the generation of the personalized data according to the awards and the scripts corresponding to all the feature data satisfying the determination rule comprises:

[0015] When the number of all the feature data satisfying the determination rule is less than a preset number, the personalized data is generated according to a preset bottom-line award and script and the awards and the scripts corresponding to all the feature data satisfying the determination rule;

[0016] When the number of all the feature data satisfying the determination rule is greater than or equal to the preset number, the preset number of feature data is selected from all the feature data satisfying the determination rule, and the personalized data is generated according to the awards and the scripts corresponding to the selected feature data.

[0017] Optionally, the selection of the preset number of feature data from all the feature data satisfying the determination rule comprises:

[0018] The preset number of feature data is selected from all the feature data satisfying the determination rule according to the priority corresponding to each feature data satisfying the determination rule.

[0019] The application further provides a video generation method, comprising:

[0020] When detecting a user-triggered active page access request, a server is requested to obtain personalized data of the user, the personalized data comprising an award obtained by the user participating in the activity and a script corresponding to the award;

[0021] The personalized data is displayed;

[0022] When detecting a video generation instruction, a video description file corresponding to a template video is obtained, the template video being a pre-created video associated with the activity;

[0023] A target video description file is generated according to the personalized data and the video description file;

[0024] The target video description file is uploaded to a server, so that the server re-renders the template video according to the target video description file to obtain the to-be-published video;

[0025] The to-be-published video returned by the server is received.

[0026] Optionally, the generating a target video description file according to the personalized data and the video description file comprises:

[0027] calling a preset video description file parsing function to parse the video description file to obtain the customized information contained in the video description file;

[0028] replacing the customized information contained in the video description file with the personalized data to obtain the target video description file.

[0029] Optionally, the method further comprises:

[0030] publishing the to-be-published video to a platform upon receiving a publishing instruction.

[0031] The application further provides a video generation device, comprising:

[0032] an acquisition module configured to acquire a script matching rule and feature data of a user according to a personalized data acquisition request sent by a front end upon receiving the request, the personalized data comprising an award obtained by the user participating in an activity and a script corresponding to the award;

[0033] a generation module configured to generate the personalized data according to the feature data and the script matching rule, and return the personalized data to the front end;

[0034] a rendering module configured to re-render a template video matched with the activity according to a target video description file sent by the front end upon receiving the target video description file, to obtain a to-be-published video, and return the to-be-published video to the front end.

[0035] The application further provides a video generation device, comprising:

[0036] a first acquisition module configured to request the server to acquire personalized data of a user upon detecting an activity page access request triggered by the user, the personalized data comprising an award obtained by the user participating in the activity and a script corresponding to the award;

[0037] a display module configured to display the personalized data;

[0038] a second acquisition module configured to acquire a video description file corresponding to a template video upon detecting a video generation instruction, the template video being a video associated with the activity and pre-created;

[0039] a generation module configured to generate a target video description file according to the personalized data and the video description file;

[0040] uploading the target video description file to the server, so that the server re-renders the template video according to the target video description file to obtain the to-be-published video;

[0041] receiving the to-be-published video returned by the server.

[0042] The application further provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method when executing the computer program.

[0043] The application further provides a video generation system, comprising a front end and a server, wherein:

[0044] The front end is configured to request the server to obtain personalized data of a user when detecting an activity page access request triggered by the user, the personalized data comprising an award obtained by the user in the activity and a text corresponding to the award; display the personalized data; obtain a video description file corresponding to a template video when detecting a video generation instruction, the template video being a pre-created video associated with the activity; generate a target video description file according to the personalized data and the video description file; and upload the target video description file to the server.

[0045] The server is configured to obtain a text matching rule and feature data of a user according to a personalized data obtaining request sent by the front end when receiving the personalized data obtaining request, the personalized data comprising an award obtained by the user in the activity and a text corresponding to the award; generate the personalized data according to the feature data and the text matching rule, and return the personalized data to the front end; re-render a template video matched with the activity according to a target video description file sent by the front end when receiving the target video description file, to obtain a to-be-published video, and return the to-be-published video to the front end.

[0046] The application further provides a computer readable storage medium having a computer program stored thereon, and the computer program is executable on a processor to implement the steps of the method.

[0047] In this embodiment, when receiving the personalized data acquisition request sent by the front end, the script matching rule and the feature data of the user are acquired according to the request, the personalized data includes the prize obtained by the user participating in the activity and the script corresponding to the prize; the personalized data is generated according to the feature data and the script matching rule, and the personalized data is returned to the front end; when receiving the target video description file sent by the front end, the template video matched with the activity is re-rendered according to the target video description file, and the to-be-published video is obtained, and the to-be-published video is returned to the front end. By using the above video generation scheme, the to-be-published video can be automatically generated by one key, without going through the processes of shooting, editing and production, which is very convenient, and thus the user contribution behavior (publishing video behavior) can be greatly stimulated. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 Application environment schematic diagram of an embodiment of the video generation method of the present application;

[0049] Figure 2 Flowchart of an embodiment of the video generation method described in the present application;

[0050] Figure 3 Step refinement flowchart of generating the personalized data according to the feature data and the script matching rule in an embodiment of the present application;

[0051] Figure 4 Schematic diagram of the determination rule in an embodiment of the present application;

[0052] Figure 5 Step refinement flowchart of generating the personalized data according to the prize and the script corresponding to the prize of all the feature data satisfying the determination rule in an embodiment of the present application;

[0053] Figure 6 Flowchart of an embodiment of the video generation method described in the present application;

[0054] Figure 7 Schematic diagram of the displayed personalized data in an embodiment of the present application;

[0055] Figure 8 Step refinement flowchart of generating the target video description file according to the personalized data and the video description file in an embodiment of the present application;

[0056] Figure 9 Schematic diagram of the displayed to-be-published video in an embodiment of the present application;

[0057] Figure 10 Program module diagram of an embodiment of the video generation device described in the present application;

[0058] Figure 11 A program module diagram of an embodiment of the video generation apparatus described in the present application;

[0059] Figure 12 A hardware structure schematic diagram of a computer device for executing the video generation method provided by the embodiment of the present application. DETAILED DESCRIPTION

[0060] The advantages of the present application are further described below in conjunction with the accompanying drawings and specific embodiments.

[0061] The exemplary embodiments will be described in detail herein below with reference to the accompanying drawings. In the following description, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments are not representative of all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0062] The terms employed in the present disclosure are for the purpose of describing particular embodiments only and are not intended to limit the present disclosure. As used in the specification and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0063] It should be understood that although the terms first, second, third, etc. can be employed in this disclosure to describe various information, such information should not be limited to these terms. These terms are only used to differentiate one piece of information from another. For example, a first information can also be referred to as a second information, and similarly, a second information can also be referred to as a first information without departing from the scope of the present disclosure. Depending on the context, the word "if' as used herein can be interpreted to mean "when" or "upon" or "in response to determining."

[0064] In the description of the present application, it should be understood that the numerical reference numbers before the steps do not identify the order of execution of the steps before and after, but are only used for the convenience of describing the present application and distinguishing each step, and therefore should not be understood as limiting the present application.

[0065] An exemplary application environment of the present application is provided below. Figure 1 An application environment schematic diagram of the video generation method according to the embodiment of the present application is schematically shown.

[0066] In an exemplary embodiment, the system of the application environment can include a user terminal 10, a backend server 20. Wherein the user terminal 10 and the backend server 20 are connected through a wireless or wired network. The user terminal 10 is deployed with a front-end client, which can be a web client, an APP client, a webpage client, etc. The backend server 20 can be a rack server, a blade server, a tower server or a cabinet server (including a standalone server, or a server cluster composed of multiple servers), etc. The backend server 20 is deployed with a backend server. The network can include various network devices, such as routers, switches, multiplexers, hubs, modems, bridges, repeaters, firewalls and / or proxy devices, etc. The network can also include physical links, such as coaxial cable links, twisted pair cable links, optical fiber links and combinations thereof and / or the like.

[0067] In the following, several embodiments will be provided under the above exemplary application environment to illustrate the video generation scheme in the present application.

[0068] Referring to Figure 2 which is a flowchart of a video generation method according to an embodiment of the present application. It can be understood that the flowchart in the method embodiment is not used to limit the order of execution steps. The video generation method can be applied in the backend server, and the method will be described below with the backend server as the execution subject. As can be seen from the figure, the video generation method provided in the embodiment includes:

[0069] Step S21, when receiving the personalized data acquisition request sent by the front end, acquiring the script matching rule and the characteristic data of the user according to the request, the personalized data including the prize obtained by the user participating in the activity and the script corresponding to the prize.

[0070] Specifically, when the user participates in the activity provided by the activity operator on the platform, the user can send a personalized data acquisition request through the front end to acquire the personalized data of the user, that is, to acquire the prize obtained by the user participating in the activity and the script corresponding to the prize. Wherein, the prize refers to the evaluation given to the user after the user participates in the activity, for example, the prize can be "note passer", "famous music critic", "original power", etc.

[0071] Wherein, the script matching rule is a rule pre-set by the activity operator for judging the prize obtained by the user participating in the activity and the script corresponding to the prize. In the embodiment, the operator can configure different script matching rules for different activities. For example, activity A configures script matching rule a, and activity B configures script matching rule b.

[0072] The feature data is used as comparison index data of each prize. For example, for prize 1, the corresponding comparison index data is the number of videos published by the user on the platform within a week; for prize 2, the corresponding comparison index data is the number of plays of the videos published by the user on the platform within a week.

[0073] In a specific embodiment, when the personalized data acquisition request sent by the front end is received, a feature data request is sent to a server storing user feature data. After receiving the request, the server storing user feature data searches for feature data associated with the identification information for identifying the user identity carried in the request, and returns the searched feature data. In addition, when the personalized data acquisition request sent by the front end is received, a script matching rule request is also sent to a server storing script matching rules. After receiving the request, the server storing script matching rules searches for script matching rules matching the activity information carried in the request, and returns the searched script matching rules.

[0074] In an exemplary embodiment, the script matching rules are acquired according to the request, including acquiring script matching rules matching the activity information carried in the request, the activity information being used to determine the activity participated in by the user.

[0075] Specifically, when the activity participated in by the user is activity a, the activity information indicating that the activity participated in by the user is activity a, such as "a", is carried in the request. After receiving the request containing "a", the back-end server acquires script matching rules matching the "a" from the corresponding server, for example, the acquired script matching rules are script matching rule a.

[0076] In step S21, the personalized data is generated according to the feature data and the script matching rules, and the personalized data is returned to the front end.

[0077] Specifically, after the feature data of the user and the script matching rules are acquired, each prize corresponding to each feature data and the script corresponding to the prize can be determined according to the determination rules of each feature data corresponding to the script matching rules. Finally, the personalized data is generated according to all the obtained prizes and the scripts corresponding to the prizes.

[0078] After the personalized data of the user is generated, the personalized data is returned to the front end, so that the personalized data can be displayed in the front end, so that the user can intuitively understand the prizes and scripts obtained by participating in the activity.

[0079] In an exemplary embodiment, the characteristic data comprises a plurality of characteristic data, the script matching rule comprises a judging rule corresponding to each characteristic data and a prize corresponding to the characteristic data, and the generating the personalized data according to the characteristic data and the script matching rule comprises: Figure 3

[0080] Step S30, judging whether each characteristic data satisfies the judging rule corresponding to the characteristic data according to the script matching rule.

[0081] Specifically, after obtaining each characteristic data, the judging rule corresponding to each characteristic data can be used to judge whether the corresponding characteristic data satisfies the judging rule. For example, the judging rule corresponding to the characteristic data a is judging rule A, and judging rule A is used to judge whether the characteristic data a satisfies judging rule A. Similarly, assuming that the judging rule corresponding to the characteristic data b is judging rule B, judging rule B is used to judge whether the characteristic data b satisfies judging rule B.

[0082] In an exemplary embodiment, when judging whether the corresponding characteristic data satisfies the judging rule, the characteristic data is compared with a threshold index corresponding to the characteristic data in the judging rule. If the characteristic data is greater than or equal to the corresponding threshold index, it can be judged that the characteristic data satisfies the judging rule. For example, for the characteristic data of the number of plays of the video published by the user on the platform within a week, if the threshold index contained in the judging rule is 20, only when the number of plays of the video published by the user on the platform within a week is greater than or equal to 20, it can be judged that the judging rule is satisfied. When the number of plays of the video published by the user on the platform within a week is less than 20, it can be judged that the judging rule is not satisfied.

[0083] Step S31, if the current characteristic data satisfies the corresponding judging rule, the prize and the script corresponding to the current characteristic data are obtained.

[0084] Specifically, if the current characteristic data satisfies the corresponding judging rule, it can be judged that the user can obtain the prize corresponding to the current characteristic data and the script corresponding to the prize.

[0085] In an exemplary embodiment, if a certain judging rule is set as shown in Figure 4 When the characteristic data satisfies the judging rule, the prize obtained is "note passer", and the script obtained is "you like to contribute to the music teaching secondary partition".

[0086] Step S32, generating the personalized data according to the prize and the script corresponding to all characteristic data satisfying the judging rule.

[0087] ​Specifically, after all the feature data satisfy the judgment, the awards and the scripts corresponding to all the feature data satisfying the judgment rule are used to generate the personalized data.

[0088] In an exemplary embodiment, referring to Figure 5 , the generating the personalized data according to the awards and the scripts corresponding to all the feature data satisfying the judgment rule comprises:

[0089] In step S50, when the number of all the feature data satisfying the judgment rule is less than the preset number, the personalized data is generated according to the preset default awards and scripts and the awards and the scripts corresponding to all the feature data satisfying the judgment rule.

[0090] In step S51, when the number of all the feature data satisfying the judgment rule is greater than or equal to the preset number, the preset number of feature data is selected from all the feature data satisfying the judgment rule, and the personalized data is generated according to the awards and the scripts corresponding to the selected feature data.

[0091] Specifically, in order to avoid too many personalized data being generated, after all the feature data satisfying the judgment rule are obtained, it can be determined whether the number of all the feature data satisfying the judgment rule is less than a preset number. When the number of the feature data satisfying the judgment rule is less than the preset number, the personalized data is generated according to the preset default awards and scripts and the awards and the scripts corresponding to all the feature data satisfying the judgment rule, so that the generated personalized data contains the preset number of awards and scripts. When the number of all the feature data satisfying the judgment rule is greater than or equal to the preset number, the preset number of feature data is selected from all the feature data satisfying the judgment rule, and then the personalized data is generated according to the awards and the scripts corresponding to the selected feature data.

[0092] It should be noted that the default awards and scripts are pre-designed template awards and scripts. There are multiple groups of default awards and scripts. When the number of the feature data satisfying the judgment rule is less than the preset number, the same number of groups of default awards and scripts as the difference between the preset number and the number of the feature data satisfying the judgment rule is randomly selected from the default awards and scripts, and then the personalized data is generated according to the selected default awards and scripts and the awards and the scripts corresponding to all the feature data satisfying the judgment rule.

[0093] The preset number is pre-set, and its value can be set and adjusted according to actual conditions, which is not limited in the present embodiment.

[0094] In an exemplary embodiment, when the preset number of feature data is selected from all feature data satisfying the judgment rule, the preset number of feature data can be selected from all feature data satisfying the judgment rule according to the priority corresponding to each feature data satisfying the judgment rule, that is, the preset number of feature data is selected from all feature data satisfying the judgment rule in a manner from high to low priority.

[0095] It should be noted that when there are multiple feature data with the same priority in the feature data meeting the screening condition in the screening process, one feature data can be randomly selected from the multiple feature data with the same priority as the feature data meeting the condition.

[0096] It can be understood that in order to screen the feature data according to the priority of each feature data, the priority of each feature data needs to be configured when the judgment rule is configured.

[0097] Step S22, when receiving the target video description file sent by the front end, re-rendering the template video matched with the activity according to the target video description file to obtain a to-be-published video, and returning the to-be-published video to the front end.

[0098] Specifically, after the front end obtains the personalized data of the user, the front end displays the personalized data so that the user can intuitively understand the awards and scripts obtained by the user participating in the activity. After the front end displays the personalized data of the user, the user can trigger a video generation instruction through the page displayed by the front end. When the front end receives the video generation instruction, the front end obtains a video description file corresponding to the template video, then generates a target video description file according to the personalized data and the video description file, and uploads the target video description file to the back-end server after generating the target video description file, so that the back-end server can re-render the template video matched with the activity according to the target video description file to obtain a to-be-published video, and return the to-be-published video to the front end when receiving the target video description file sent by the front end.

[0099] The template video is created by an operator in advance, the template video can be composed of a plurality of segmented videos which need to be transitioned, and in some segmented videos, content which needs to show user customized information is configured with a template subtitle or a template picture for facilitating later replacement. After the operator completes creation of the template video, a video description file is generated to describe composition of the template video. In an embodiment, the video description file can include materials used by the template video, video tracks, audio tracks, subtitle information, and content of user customized information and specific position information of the content in the template video. The target video description file is generated according to user personalized data and the video description file. Specifically, the target video description file is obtained by replacing the personalized data in the video description file.

[0100] In the embodiment, after the to-be-published video is rendered, the to-be-published video is returned to the front end, so that the user can play or publish the video through the front end.

[0101] In an embodiment, in the process of rendering the video, in order to upload the to-be-published video to the content server in time, the rendering progress of the video is acquired in real time or at a fixed time, when the rendering progress is rendered, the content server is requested to store the video address of the to-be-published video, and after the video address is obtained, the to-be-published video can be uploaded to the content server according to the video address.

[0102] It should be noted that the content server described above is a server for storing to-be-published videos of each user.

[0103] In the embodiment, when the personalized data acquisition request sent by the front end is received, the script matching rule and the characteristic data of the user are acquired according to the request, the personalized data includes an award obtained by the user participating in an activity and a script corresponding to the award; the personalized data is generated according to the characteristic data and the script matching rule, and the personalized data is returned to the front end; when the target video description file sent by the front end is received, the template video matched with the activity is re-rendered according to the target video description file, to obtain a to-be-published video, and the to-be-published video is returned to the front end. Using the above video generation scheme, the to-be-published video can be automatically generated by “one key”, without going through the processes of shooting, editing and production, which is very convenient, and can greatly encourage the user to contribute (publish the video).

[0104] Referring to Figure 6Fig. 1 is a flowchart of a video generation method according to an embodiment of the present application. It can be understood that the flowchart in the embodiment of the method is not used to limit the order of execution steps. The video generation method can be applied in the front end, and the method will be described below with the front end as the execution subject. As can be seen from the figure, the video generation method provided in the embodiment includes the following steps.

[0105] Step S60, when detecting a user triggered activity page access request, requesting a server to obtain personalized data of the user, the personalized data including an award obtained by the user participating in the activity and a text corresponding to the award.

[0106] Specifically, there are many ways for the user to trigger the activity page access request, such as clicking a preset control in the front-end interface, or triggering the activity page access request by voice, gesture, etc. Or by scanning the two-dimensional code of the activity through the third-party terminal device to trigger the activity page access request.

[0107] In the embodiment, after the front end detects the user triggered activity page access request, the server is requested to obtain the personalized data of the user.

[0108] The way in which the server generates personalized data has been described in detail in the above embodiment, and will not be described again in this embodiment.

[0109] Step S61, displaying the personalized data.

[0110] Specifically, after the front end obtains the personalized data of the user from the server, the personalized data is displayed in the front-end interface, so that the user can know the award obtained by the user and the text. In a specific implementation, the displayed personalized data is as shown in Figure 7 The "B station's pride" in Figure 7 is the award obtained by the user, and "your identity is the UP host that B station is most proud of" is the text corresponding to the award.

[0111] Step S62, when detecting a video generation instruction, obtaining a video description file corresponding to a template video, the template video being a pre-created video associated with the activity.

[0112] Specifically, after the personalized data of the user is displayed, the user can choose whether to generate a video according to the personalized data of the user, and when the user wants to generate, the user can trigger a video generation instruction.

[0113] In a specific implementation, the user can trigger the video generation instruction in the front-end interface by clicking a preset control, voice or gesture, etc.

[0114] When the video generation instruction is detected, a video description file corresponding to the template video is acquired. The video description file can be pre-stored in the memory of the terminal device where the front end is deployed, or can be acquired from the back-end server. In a specific embodiment, when the video description file is acquired from the back-end server, in order to facilitate acquisition, a mapping relationship between each project ID and the file address of the video description file corresponding to different activities can be pre-configured in the front end, so that the front end can acquire the file address of the video description file according to the different project ID selected by the user, and then acquire the video description file according to the file address.

[0115] The template video is a video associated with an activity pre-created by an operator. For different activities, the operator can create different template videos. The video description file is a file for describing the template video. The video description file can include the content of the material, video track, audio track, subtitle information, and user-defined information used by the template video, and the specific position information of the content in the template video.

[0116] Step S63: generating a target video description file according to the personalized data and the video description file.

[0117] Specifically, after obtaining the personalized data and the video description file, the target video description file can be generated by replacing the corresponding content in the video description file with the personalized data.

[0118] In an exemplary embodiment, referring to Figure 8 Generating a target video description file according to the personalized data and the video description file includes:

[0119] Step S80: calling a preset video description file parsing function to parse the video description file to obtain the user-defined information contained in the video description file.

[0120] Specifically, by pre-setting the video description file parsing function, when the target video description file needs to be generated, the video description file parsing function can be called to parse the video description file, so as to obtain the user-defined information contained in the video description file.

[0121] Step S81: replacing the user-defined information contained in the video description file with the personalized data to obtain the target video description file.

[0122] Specifically, in the process of custom information replacement, a function can also be preset to replace the personalized data with the custom information contained in the video description file, so as to obtain the target video description file. In another embodiment, the personalized data can also be directly replaced with the custom information contained in the video description file by the video description file parsing function, so as to obtain the target video description file.

[0123] In step S64, the target video description file is uploaded to the server, so that the server re-renders the template video according to the target video description file to obtain the to-be-published video.

[0124] Specifically, after the target video description file is generated, the target video description file is uploaded to the server, so that more powerful resources in the server can be used to quickly generate the to-be-published video.

[0125] It can be understood that in an embodiment, the to-be-published video can also be directly re-rendered by the front end according to the target video description file.

[0126] In step S65, the to-be-published video returned by the server is received.

[0127] Specifically, after the to-be-published video is generated, the server returns the to-be-published video to the front end, so that the front end can display the to-be-published video. In a specific embodiment, the to-be-published video received by the front end is as shown in FIG. 8. Figure 9

[0128] In an exemplary embodiment, the method further comprises:

[0129] When the publishing instruction is received, the to-be-published video is published on the platform.

[0130] Specifically, after the to-be-published video is received by the front end, the user can publish the video on the platform, so that the user and other users can watch the video on the platform. Specifically, the user can publish the video on the platform by triggering a video publishing instruction. In a specific embodiment, the user can trigger the video publishing instruction by clicking the “share video” control in FIG. 8, so as to realize the publishing of the video. Figure 9

[0131] In this embodiment, when the publishing instruction is received, the front end calls an interface for video publishing in the platform to transmit address information of the video into the platform, so as to realize the publishing of the video on the platform.

[0132] ​​In an embodiment, after a user posts a video on a platform, in order to make the video content compliant, the platform can review the video posted by the user through artificial or automatic identification technology, and after the video is not compliant, the video is taken down from the platform.

[0133] The embodiment detects a user triggered activity page access request, requests a server to obtain personalized data of the user, the personalized data including an award obtained by the user participating in the activity and a text corresponding to the award, displays the personalized data, detects a video generation instruction, obtains a video description file corresponding to a template video, the template video being a pre-created video associated with the activity, generates a target video description file according to the personalized data and the video description file, uploads the target video description file to the server, so that the server re-renders the template video according to the target video description file to obtain the to-be-posted video, and receives the to-be-posted video returned by the server. In this way, a video can be generated by one key, so that more ordinary users have the opportunity to become up masters (people who upload video and audio files on a video website, forum or ftp site).

[0134] Referring to Figure 10 FIG. 1 is a program module diagram of an embodiment of a video generation apparatus 100 according to the present application.

[0135] In the embodiment, the video generation apparatus 100 includes a series of computer program instructions stored on a memory, which can realize the photographing function of each embodiment of the present application when executed by a processor. In some embodiments, based on the specific operations realized by each part of the computer program instructions, the video generation apparatus 100 can be divided into one or more modules, and the specific modules that can be divided are as follows:

[0136] The obtaining module 101 is configured to, when receiving a personalized data obtaining request sent by a front end, obtain a text matching rule and feature data of a user according to the request, the personalized data including an award obtained by the user participating in an activity and a text corresponding to the award.

[0137] The generating module 102 is configured to generate the personalized data according to the feature data and the text matching rule, and return the personalized data to the front end.

[0138] The rendering module 103 is configured to, when receiving a target video description file sent by the front end, re-render a template video matched with the activity according to the target video description file to obtain a to-be-posted video, and return the to-be-posted video to the front end.

[0139] In an exemplary embodiment, the obtaining module 101 is further configured to obtain a script matching rule matched with the activity information according to the activity information carried in the request, the activity information being used to determine an activity participated by the user.

[0140] In an exemplary embodiment, the feature data comprises a plurality of pieces, the script matching rule comprises a judging rule of a prize and a script corresponding to each piece of feature data, and the generating module 102 is further configured to judge whether each piece of feature data satisfies the corresponding judging rule according to the script matching rule, obtain the prize and the script corresponding to the current piece of feature data if the current piece of feature data satisfies the corresponding judging rule, and generate the personalized data according to the prize and the script corresponding to all pieces of feature data satisfying the judging rule.

[0141] In an exemplary embodiment, the generating module 102 is further configured to generate the personalized data according to a preset bottom prize and script and the prize and the script corresponding to all pieces of feature data satisfying the judging rule when the number of all pieces of feature data satisfying the judging rule is less than a preset number, and select the preset number of pieces of feature data from all pieces of feature data satisfying the judging rule and generate the personalized data according to the prize and the script corresponding to the selected pieces of feature data when the number of all pieces of feature data satisfying the judging rule is greater than or equal to the preset number.

[0142] In an exemplary embodiment, the generating module 102 is further configured to select the preset number of pieces of feature data from all pieces of feature data satisfying the judging rule according to a priority corresponding to each piece of feature data satisfying the judging rule.

[0143] Referring to Figure 11 FIG. 1 shows a program module diagram of an embodiment of a video generation apparatus 110 according to the present application.

[0144] In the embodiment, the video generation apparatus 110 comprises a series of computer program instructions stored on a memory, and when the computer program instructions are executed by a processor, the shooting function of each embodiment of the present application can be realized. In some embodiments, based on the specific operation realized by each part of the computer program instructions, the video generation apparatus 110 can be divided into one or more modules, and the specific modules that can be divided are as follows:

[0145] The first obtaining module 111 is configured to request the server to obtain the personalized data of the user when detecting an activity page access request triggered by the user, the personalized data comprising a prize obtained by the user participating in the activity and a script corresponding to the prize.

[0146] The display module 112 is configured to display the personalized data.

[0147] The second acquisition module 113 is configured to acquire a video description file corresponding to a template video when a video generation instruction is detected, the template video being a pre-created video associated with the activity;

[0148] The generation module 114 is configured to generate a target video description file according to the personalized data and the video description file;

[0149] The uploading module 115 is configured to upload the target video description file to a server, so that the server re-renders the template video according to the target video description file to obtain the to-be-published video;

[0150] The receiving module 116 is configured to receive the to-be-published video returned by the server.

[0151] In an exemplary embodiment, the generation module 114 is further configured to call a preset video description file parsing function to parse the video description file to obtain custom information contained in the video description file; and replace the custom information contained in the video description file with the personalized data to obtain the target video description file.

[0152] In an exemplary embodiment, the video generation apparatus 110 further comprises a publishing module.

[0153] The publishing module is configured to publish the to-be-published video to a platform when a publishing instruction is received.

[0154] Figure 12 A hardware architecture schematic diagram of a computer device 12 suitable for implementing the video generation method according to an embodiment of the present application is schematically shown. In this embodiment, the computer device 12 is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions. For example, it can be a tablet computer, a notebook computer, a desktop computer, a rack-mounted server, a blade server, a tower server or a cabinet server (including a standalone server or a server cluster composed of multiple servers), etc. As shown in the figure, the computer device 12 at least includes but is not limited to a memory 120, a processor 121 and a network interface 122 which are communicatively connected through a system bus. Among them: Figure 12

[0155] ​The memory 120 includes at least one type of computer-readable storage media, which can be volatile or non-volatile, and specifically includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 120 can be an internal storage module of the computer device 12, such as a hard disk or a memory of the computer device 12. In other embodiments, the memory 120 can also be an external storage device of the computer device 12, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 12. Of course, the memory 120 can include both the internal storage module and the external storage device of the computer device 12. In this embodiment, the memory 120 is generally used to store an operating system and various application software installed on the computer device 12, such as program codes of the video generation method, etc. In addition, the memory 120 can also be used to temporarily store various data that have been output or will be output.

[0156] The processor 121 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other shooting chip in some embodiments. The processor 121 is generally used to control the overall operation of the computer device 12, such as performing control and processing related to data interaction or communication of the computer device 12, etc. In this embodiment, the processor 121 is used to run program codes or process data stored in the memory 120.

[0157] The network interface 122 can include a wireless network interface or a wired network interface, which is generally used to establish a communication link between the computer device 12 and other computer devices. For example, the network interface 122 is used to connect the computer device 12 with an external terminal through a network, establish a data transmission channel and a communication link between the computer device 12 and the external terminal, and the like. The network can be an Intranet, the Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth, Wi-Fi, and the like wireless or wired network.

[0158] It should be noted that, Figure 12 Only the computer device with components 120-122 is shown, but it should be understood that all the shown components are not required to be implemented, and more or fewer components can be alternatively implemented.

[0159] In the embodiment, the video generation method stored in the memory 120 can be divided into one or more program modules and executed by one or more processors (the processor 121 in the embodiment) to complete the present application.

[0160] The embodiment of the present application provides a video generation system, comprising: a front end and a server, wherein:

[0161] The front end is configured to request the server to obtain personalized data of a user when detecting an activity page access request triggered by the user, the personalized data comprising an award obtained by the user in the activity and a text corresponding to the award; display the personalized data; obtain a video description file corresponding to a template video when detecting a video generation instruction, the template video being a video associated with the activity and pre-created; generate a target video description file according to the personalized data and the video description file; and upload the target video description file to the server.

[0162] The server is configured to, when receiving the personalized data acquisition request sent by the front end, acquire the script matching rule and the feature data of the user according to the request, the personalized data including the prize obtained by the user participating in the activity and the script corresponding to the prize; generate the personalized data according to the feature data and the script matching rule, and return the personalized data to the front end; when receiving the target video description file sent by the front end, re-render the template video matched with the activity according to the target video description file to obtain a to-be-published video, and return the to-be-published video to the front end.

[0163] The embodiment of the present application provides a computer readable storage medium, the computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement the steps of the video generation method in the embodiment.

[0164] In the embodiment, the computer readable storage medium includes a flash memory, a hard disk, a multimedia card, a card type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read only memory (ROM), an electrically erasable programmable read only memory (EEPROM), a programmable read only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the computer readable storage medium can be an internal storage unit of a computer device, for example, a hard disk or a memory of the computer device. In other embodiments, the computer readable storage medium can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Of course, the computer readable storage medium can also include both the internal storage unit and the external storage device of the computer device. In the embodiment, the computer readable storage medium is usually used to store the operating system and various application software installed on the computer device, for example, the program code of the video generation method in the embodiment, etc. In addition, the computer readable storage medium can also be used to temporarily store various data that have been output or will be output.

[0165] The device embodiments described above are only schematic, wherein the units shown as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or distributed on at least two network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application. Those skilled in the art can understand and implement without creative labor.

[0166] Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiment methods. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM), etc.

[0167] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A video generation method, characterized in that, include: When a personalized data acquisition request is received from the front end, the copy matching rules and user feature data are obtained according to the request. The personalized data includes the awards that the user has won in the activity and the copy corresponding to the awards. The personalized data is generated based on the feature data and the copy matching rules, and the personalized data is returned to the front end; Upon receiving the target video description file sent by the front end, the template video matching the activity is re-rendered according to the target video description file to obtain the video to be published, and the video to be published is returned to the front end; the target video description file is generated based on the user's personalized data and the video description file; the video description file includes the content of the materials used in the template video, video track, audio track, subtitle information, user-defined information and / or the specific location information of the content in the template video.

2. The video generation method according to claim 1, characterized in that, The step of obtaining the copy matching rules according to the request includes: Based on the activity information carried in the request, obtain the copy matching rules that match the activity information, which is used to determine the activity the user is participating in.

3. The video generation method according to claim 1 or 2, characterized in that, The feature data includes multiple entries, and the copywriting matching rules include the award and copywriting judgment rules corresponding to each feature data. Generating the personalized data based on the feature data and the copywriting matching rules includes: Based on the text matching rules, determine whether each feature data satisfies the corresponding judgment rule; If the current feature data meets the corresponding judgment rule, then obtain the award and copy corresponding to the current feature data; The personalized data is generated based on the awards and accompanying text corresponding to all feature data that meet the judgment rules.

4. The video generation method according to claim 3, characterized in that, The process of generating the personalized data based on the awards and text corresponding to all feature data that satisfy the judgment rules includes: When the number of all feature data that meet the judgment rules is less than the preset number, the personalized data is generated based on the preset backup awards and copywriting, as well as the awards and copywriting corresponding to all feature data that meet the judgment rules. When the number of feature data that meets the judgment rule is greater than or equal to the preset number, the preset number of feature data is selected from all feature data that meets the judgment rule, and the personalized data is generated based on the awards and text corresponding to the selected feature data.

5. The video generation method according to claim 4, characterized in that, The step of selecting the preset number of feature data from all feature data that satisfy the determination rule includes: The preset number of feature data are selected from all feature data that satisfy the determination rule based on the priority of each feature data that satisfies the determination rule.

6. A video generation method, characterized in that, include: When a user-triggered access request to an activity page is detected, the system requests the server to obtain the user's personalized data, which includes the awards the user won in the activity and the corresponding text for those awards. Display the personalized data; When a video generation instruction is detected, a video description file corresponding to a template video is obtained, wherein the template video is a pre-created video associated with the activity; Generate a target video description file based on the personalized data and the video description file; The target video description file is uploaded to the server so that the server can re-render the template video based on the target video description file to obtain the video to be published. Receive the video to be published returned by the server.

7. The video generation method according to claim 6, characterized in that, The step of generating the target video description file based on the personalized data and the video description file includes: The video description file is parsed by calling a preset video description file parsing function to obtain the custom information contained in the video description file; The target video description file is obtained by replacing the custom information contained in the video description file with the personalized data.

8. The video generation method according to claim 6 or 7, characterized in that, The method further includes: Upon receiving the publishing instruction, the video to be published is published to the platform.

9. A video generation apparatus, characterized in that, include: The acquisition module is used to acquire copy matching rules and user feature data according to the request when receiving a personalized data acquisition request sent by the front end. The personalized data includes the awards won by the user in participating in the activity and the copy corresponding to the awards. The generation module is used to generate the personalized data based on the feature data and the copy matching rules, and return the personalized data to the front end; The rendering module is used to, upon receiving the target video description file sent by the front end, re-render the template video matching the activity according to the target video description file to obtain the video to be published, and return the video to be published to the front end; the target video description file is generated based on the user's personalized data and the video description file; the video description file includes the content of the materials used in the template video, video track, audio track, subtitle information, user-defined information and / or the specific location information of the content in the template video.

10. A video generation apparatus, characterized in that, include: The first acquisition module is used to request the user's personalized data from the server when a user-triggered access request to the activity page is detected. The personalized data includes the awards the user has won in the activity and the corresponding text of the awards. The display module is used to display the personalized data; The second acquisition module is used to acquire a video description file corresponding to the template video when a video generation instruction is detected, wherein the template video is a pre-created video associated with the activity; The generation module is used to generate a target video description file based on the personalized data and the video description file; The upload module is used to upload the target video description file to the server, so that the server can re-render the template video according to the target video description file to obtain the video to be published; The receiving module is used to receive the video to be published returned by the server.

11. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method according to any one of claims 1 to 8.

12. A video generation system, characterized in that, include: Front-end and server-side, including: The front-end is configured to, upon detecting a user-triggered access request to an activity page, request the server to obtain the user's personalized data, including awards the user has won in the activity and corresponding text descriptions; display the personalized data; upon detecting a video generation instruction, obtain a video description file corresponding to a template video, wherein the template video is a pre-created video associated with the activity; generate a target video description file based on the personalized data and the video description file; and upload the target video description file to the server. The server is configured to, upon receiving a personalized data acquisition request from the front end, acquire copywriting matching rules and user feature data according to the request, wherein the personalized data includes awards won by the user in participating in activities and the corresponding copywriting; generate the personalized data according to the feature data and the copywriting matching rules, and return the personalized data to the front end; and upon receiving a target video description file from the front end, re-render a template video matching the activity according to the target video description file to obtain a video to be published, and return the video to be published to the front end.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

14. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

Images