Digital media design platform based on computer technology

Abstract

The invention relates to the technical field of digital media design, and discloses a digital media design platform based on computer technology, comprising: a creative design tool for providing various functions required by a user for digital media creation; the automatic identification and classification module is responsible for automatically identifying and classifying the uploaded media files; the resource management and material library is used for providing design resources, including vector plots, pictures, audio and video materials and templates, and supporting project creation, task allocation, progress tracking and cooperation; the self-adaptive media coding technology module is used for intelligently selecting coding formats and parameters according to factors of a target playing terminal; according to the invention, the automatic identification and classification module analyzes and identifies the features of the media file by using a deep learning technology, can identify the features of texture, color distribution, shape and the like of an image, and the features of frequency distribution, rhythm, melody and the like of audio, can process mass data, reduces the consumption of computing resources, and maintains high classification precision at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of digital media design, and in particular to a digital media design platform based on computer technology. Background Art

[0002] With the advent of the information age, the demand for digital media content in all walks of life has increased dramatically. From movies, games, advertising, education, publishing to social media, e-commerce and other fields, high-quality and diversified digital media design services are needed. The professional division of labor in the design industry has been refined and cross-border cooperation has increased, calling for a more intelligent and integrated design platform to meet the diversified creative needs and rapid iteration of product cycles; at the same time, the rapid development of computer graphics, image processing, audio processing and video coding and decoding technology has laid a solid technical foundation for the birth of digital media design platforms, especially the application of artificial intelligence technologies such as deep learning. The functions and efficiency of design tools have been greatly improved, and they can handle higher-definition and more complex media content.

[0003] After searching, the invention patent with Chinese patent number CN102143385A discloses a media playback processing method, a digital media server and a system. Compared with the prior art, the invention patent with Chinese patent number CN102143385A can realize the centralized management of various media resources, realize the free playback or transcoding of media on various home media terminals, solve the problem of inconsistent media formats supported by various types of home media terminals in the prior art, and realize the migration of media from storage devices to handheld terminals and other devices, providing great convenience for users.

[0004] However, while the digital media platform realizes the centralized management of various media resources, the media resources involve tens of thousands of images, audio or video materials, which need to be browsed, analyzed and classified one by one. The workload is huge and requires a lot of manpower investment. In addition, due to the massive data, processing massive data during classification consumes a lot of computing resources, which affects the classification performance of the platform and thus affects the classification results, resulting in a decrease in the efficiency of platform resource retrieval. Therefore, a digital media design platform based on computer technology is proposed herein. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art that when faced with massive data, the accuracy of classification will be affected and human resources will be wasted, and a digital media design platform based on computer technology is proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A digital media design platform based on computer technology, comprising:

[0008] Creative design tools: Creative design tools are the core part of the platform, providing users with various functions required for digital media creation;

[0009] Automatic identification and classification module: responsible for automatically identifying and classifying uploaded media files (images, audio, video);

[0010] Resource management and material library: Provide design resources, including vector icons, pictures, audio, video materials and templates, and support project creation, task assignment, progress tracking and collaboration;

[0011] Adaptive media coding technology module: intelligently selects the optimal coding format and parameters based on the network environment, device performance and other factors of the target playback terminal;

[0012] Output and publishing module: export design files to a user-specified location or publish directly to the target platform;

[0013] Personalized recommendation module: Provides personalized recommendation services by analyzing users' historical viewing behavior, preferences and media content characteristics;

[0014] Media copyright management and protection module: Use blockchain technology to ensure the immutability and transparency of media copyrights, and automate copyright authorization and payment processes through smart contracts;

[0015] The design file generated by the creative design tool will be passed to the automatic identification and classification module and the resource management and material library as original media data. The automatic identification and classification module will feed back the identification and classification results to the resource management and material library. The classification results are used to trigger the recommendation logic of the personalized recommendation module. The adaptive media encoding technology module obtains the media files to be encoded from the resource management and material library, performs encoding optimization according to the analysis results, and then provides the encoded files to the output and publishing module. The media copyright management and protection module interacts with the resource management and material library to ensure the accuracy and completeness of the copyright information, and interacts with the smart contract and blockchain network to realize the automatic management and protection of copyright.

[0016] The above technical solution further includes:

[0017] Furthermore, the creative design tool includes a vector graphics editor, an image processing unit, a video editing unit, and a 3D modeling and rendering unit. The vector graphics editor provides the ability to draw, edit and export vector graphics, and supports designers to create design elements such as icons and illustrations. The vector graphics editor interacts with the resource management and material library, and saves the created or edited vector graphics to the resource management and material library. At the same time, the vector graphics editor receives vector graphics from the resource management and material library for editing. The image processing unit includes image editing functions such as color adjustment, cropping, and repair, and supports RAW format to meet the needs of professional photographers and designers. The image processing unit obtains the original image file from the resource management and material library, edits it, and then saves the processed image back to the resource management and material library or directly uses it in scenes such as video editing and 3D modeling. The editing unit integrates functions such as video editing, special effects addition, and audio editing, supports multi-track editing and timeline management, facilitates the production of video works, interacts with the resource management and material library, and obtains audio and video materials for editing. The video editing unit receives the image processed by the image processing unit as the video material. After editing, the video work is saved to the resource management and material library or directly exported. The 3D modeling and rendering unit supports 3D modeling, physical engine and advanced rendering technology to realize a complete 3D design process. The 3D modeling and rendering unit obtains 3D resources such as textures and materials from the resource management and material library. The 3D modeling and rendering unit needs the image provided by the image processing unit as a texture during the modeling process. After rendering, the 3D modeling and rendering unit saves the 3D model and its rendering results to the resource management and material library or directly uses them in scenes such as video editing and display.

[0018] Furthermore, the automatic identification and classification module includes a file uploading unit, a preprocessing unit, a feature extraction unit, a classification unit and a result output unit. The file uploading unit is responsible for receiving media files uploaded by users, such as images, audio, video, etc. The file uploading unit passes the uploaded files to the preprocessing unit. The preprocessing unit performs necessary preprocessing on the uploaded media files, such as format conversion, size adjustment, noise removal, etc., to ensure that the files meet the input requirements of the deep learning model. The preprocessing unit receives the files from the file uploading unit, and passes the data to the feature extraction unit after processing. The feature extraction unit uses the deep learning model to extract key features from the preprocessed media files. The feature extraction unit receives the data from the preprocessing unit, extracts the features and passes them to the classification unit. The classification unit uses a classification algorithm to classify the media files based on the extracted features. The classification unit passes the classification results to the result output unit. The result output unit displays the classification results in a user-friendly manner, such as displaying classification labels, confidence levels, etc. through an interface.

[0019] Furthermore, the resource management and material library include a material library, project management and a version control unit. The material library provides rich design resources, including vector icons, pictures, audio, video materials and templates, and supports users to search and classify so as to quickly find required materials. The project management supports project creation, task assignment, progress tracking and team collaboration to help users better manage design projects. The version control unit is responsible for automatic saving and management of design versions, including operations such as version creation, deletion, comparison and rollback. When the user makes modifications in the design, the version control unit will automatically save the current version. The user can view the historical version list through the version control unit and select the version to be rolled back for recovery. The version control unit also provides a version comparison function to help users understand the differences between different versions.

[0020] Furthermore, the material library includes a resource storage subunit, a search engine subunit and a classification management subunit. The resource storage subunit is responsible for storing all design resources, including vector icons, pictures, audio, video and other files. The search engine subunit provides a search function, allowing users to search for materials based on keywords, tags or categories. The classification management subunit is responsible for the classification management of materials to ensure that materials can be stored and displayed in order by category. Users submit search requests through the search engine subunit, and the search engine subunit retrieves qualified materials from the resource storage subunit and displays the results to users by category through the classification management subunit.

[0021] Furthermore, the project management includes a project management unit and a team collaboration unit. The project management unit is responsible for the creation, deletion, editing, task assignment and progress tracking of projects. The team collaboration unit provides communication and collaboration tools between team members, such as message notifications, task comments, etc. Users create projects and assign tasks to team members through the project management unit. The team collaboration unit is responsible for processing communication and collaboration information between team members, such as task progress updates, comments, etc., and synchronizing the communication and collaboration information between team members to the project management unit so that all members can keep abreast of project dynamics.

[0022] Furthermore, the adaptive media coding technology module includes a network environment monitoring unit, a device performance detection unit, a coding strategy decision unit, an encoder unit, and a feedback and optimization unit. The network environment monitoring unit is responsible for real-time monitoring of the network status of the target playback terminal, including key indicators such as bandwidth and delay. The device performance detection unit is responsible for detecting the hardware performance of the playback terminal, such as processor model, memory size, screen resolution, etc. The coding strategy decision unit determines the optimal coding format and parameters based on the data provided by the network environment monitoring unit and the device performance detection unit, combined with user preferences and content type. The encoder unit encodes the media content according to the instructions of the coding strategy decision unit to generate a media stream suitable for the target playback terminal. The feedback and optimization unit collects playback quality feedback (such as freeze, buffering time, etc.) from the playback terminal, as well as user usage feedback, for optimization. The network environment monitoring unit provides real-time network status data to the coding strategy decision unit as an important basis for coding strategy decision-making. The device performance detection unit provides the hardware performance data of the playback terminal to the coding strategy decision unit to help the decision unit understand the processing capability of the device. The preference information (such as image quality priority, traffic saving, etc.) input by the user through the setting interface or the playback control interface directly affects the selection of the coding strategy. The coding strategy decision unit sends the decided coding format and parameter instructions to the encoder unit for actual coding processing. The encoder unit sends the encoded media stream to the playback terminal for playback. The playback quality feedback and user usage feedback generated by the playback terminal during the playback process are collected for subsequent optimization work. The feedback and optimization unit uses the collected feedback data to optimize the coding strategy and improve the accuracy and efficiency of coding.

[0023] Furthermore, the output and publishing module includes a format conversion unit, a template management unit, an automatic adjustment unit, a user authentication unit, a publishing interface unit, a publishing configuration unit and a user interface unit. The format conversion unit is responsible for converting the design work from the internal format to the export format selected by the user. The template management unit stores and manages preset templates and sizes for different social media platforms. The automatic adjustment unit automatically adjusts the layout and size of the design work according to the template and size selected by the user. The user authentication unit processes the user's login and authorization to ensure that the user has the right to publish content to the target platform. The publishing interface unit is connected to the API interface of each target platform (such as WordPress, Facebook, Twitter, etc.) to realize the one-click publishing function. Yes, the publishing configuration unit allows the user to configure detailed parameters of the publication, such as title, description, tags, etc. The user interface unit provides a user interface, including an interface for selecting the export format and configuring the export options, an interface for selecting the template and viewing the adjustment effect, and an interface for configuring the publishing parameters and initiating a publishing request. After the user selects the export format through the interface, the user interface unit passes the user's selection to the format conversion unit for processing. After the user selects the template and size through the interface, the user interface unit passes the selection result to the template management unit and the automatic adjustment unit to automatically adjust the design work. After the user configures the publishing parameters through the interface and initiates a publishing request, the user interface unit passes the configuration information to the publishing configuration unit and triggers the publishing interface unit to perform the actual publishing operation.

[0024] Furthermore, the personalized recommendation module includes a user behavior data collection unit, a user portrait construction unit, a content feature extraction unit, a recommendation algorithm unit, a recommendation result display unit and a feedback and optimization unit. The user behavior data collection unit is responsible for collecting user behavior data, including historical viewing records, click behaviors, dwell time, rating feedback and other data. The user portrait construction unit constructs a user portrait based on the user behavior data, including the user's interest preferences, viewing habits, etc. The content feature extraction unit analyzes the content features of media resources, such as the theme, tag, duration, cast, director, etc. of the video; the genre, rhythm, emotion, etc. of the audio; the keywords, subject classification, etc. of the article. The recommendation algorithm unit uses collaborative filtering combined with user portraits and content features to calculate the user's preference for unwatched resources and generate a recommendation list. The recommendation result display unit is responsible for presenting the recommendation list generated by the recommendation algorithm unit in a user-friendly format. The recommendation results are displayed on the front-end interface in various ways, such as sorting by interest, displaying by category, etc. The feedback and optimization unit collects user feedback on the recommendation results (such as clicks, viewing time, ratings, skips, etc.) for optimizing the recommendation algorithm and the user portrait model to improve the accuracy of the recommendation. The user behavior data acquisition unit transmits the collected user behavior data to the user portrait construction unit. The content feature extraction unit transmits the analyzed media resource content feature data to the recommendation algorithm unit. The recommendation algorithm unit simultaneously receives the user portrait data constructed by the user portrait construction unit and the content feature data extracted by the content feature extraction unit, performs matching and calculation, and generates a recommendation list. The recommendation algorithm unit transmits the generated recommendation list to the recommendation result display unit, which is responsible for displaying it to the user on the front-end interface. The user feedback on the recommendation results (such as clicks, viewing time, etc.) is collected by the recommendation result display unit and then transmitted to the feedback and optimization unit.

[0025] Furthermore, the media copyright management and protection module includes a copyright registration unit, a smart contract unit, a copyright monitoring unit, a user management unit and a blockchain network unit. The copyright registration unit is responsible for receiving and processing copyright registration requests, writing the digital fingerprint and related information of the work into the blockchain, and generating a unique copyright identifier. The smart contract unit writes and deploys smart contracts to realize the automated processing of copyright authorization. The smart contract automatically executes the authorization and payment process according to preset conditions to ensure the accuracy and efficiency of the transaction. The copyright monitoring unit uses blockchain technology and network monitoring tools to monitor copyright infringement on the network. Once infringement is found, the copyright monitoring unit provides evidence and notifies the copyright holder. The user management unit manages copyright creation. The identities and permissions of various users such as authors, copyright holders, and copyright buyers ensure that users can safely and legally use the various functions provided by the system. The blockchain network unit provides the operating environment and infrastructure support of the blockchain network, including the deployment of blockchain nodes, the implementation of consensus algorithms, data storage and verification, etc. The copyright registration unit writes the digital fingerprint and related information of the work into the blockchain, and performs distributed storage and verification through the blockchain network unit. The smart contract unit writes and deploys smart contracts to the blockchain network unit, and the blockchain network unit is responsible for the execution and verification of smart contracts. After the copyright monitoring unit detects infringement, it queries the relevant copyright information through the blockchain network unit and notifies the user management unit to deal with the infringing user.

[0026] The present invention has the following beneficial effects:

[0027] 1. In the present invention, the automatic recognition and classification module uses deep learning technology to analyze and identify the characteristics of media files. It can recognize the texture, color distribution, shape and other characteristics of images, as well as the frequency distribution, rhythm, melody and other characteristics of audio. It can process massive data, reduce the consumption of computing resources, and maintain high classification accuracy.

[0028] 2. In the present invention, the adaptive media coding technology module can intelligently select the optimal coding format and parameters according to the network environment and device performance of the target playback terminal. The module can improve the playback quality and fluency of the media content, especially in the case of an unstable network environment, and provide a better user experience.

[0029] 3. In the present invention, the media copyright management and protection module uses blockchain technology to ensure the immutability and transparency of media copyrights. The smart contract unit realizes the automated processing of copyright authorization, improves the efficiency and accuracy of copyright transactions and management, and the copyright monitoring unit can monitor copyright infringements on the network in real time, providing timely protection for copyright holders. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a system block diagram of a digital media design platform based on computer technology proposed by the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] See also Figure 1 As shown, the present invention is a digital media design platform based on computer technology, comprising:

[0033] Creative design tools: Creative design tools are the core part of the platform, providing users with various functions required for digital media creation;

[0034] Automatic identification and classification module: responsible for automatically identifying and classifying uploaded media files (images, audio, video);

[0035] Resource management and material library: Provide design resources, including vector icons, pictures, audio, video materials and templates, and support project creation, task assignment, progress tracking and collaboration;

[0036] Adaptive media coding technology module: intelligently selects the optimal coding format and parameters based on the network environment, device performance and other factors of the target playback terminal;

[0037] Output and publishing module: export design files to a user-specified location or publish directly to the target platform;

[0038] Personalized recommendation module: Provides personalized recommendation services by analyzing users' historical viewing behavior, preferences and media content characteristics;

[0039] Media copyright management and protection module: Use blockchain technology to ensure the immutability and transparency of media copyrights, and automate copyright authorization and payment processes through smart contracts;

[0040] The design files generated by the creative design tool will be passed to the automatic identification and classification module and the resource management and material library as original media data. The automatic identification and classification module will feed back the identification and classification results to the resource management and material library. The classification results are used to trigger the recommendation logic of the personalized recommendation module. The adaptive media coding technology module obtains the media files to be encoded from the resource management and material library, optimizes the encoding according to the analysis results, and then provides the encoded files to the output and publishing module. The media copyright management and protection module interacts with the resource management and material library to ensure the accuracy and completeness of the copyright information, and interacts with the smart contract and blockchain network to realize the automated management and protection of copyright.

[0041] The working principle of an information-based campus innovation and entrepreneurship practice ecosystem proposed by the present invention is that after the user completes the creation of the work in the creative design tool, the work is saved to the resource management and material library, and then these works are identified and classified by the automatic recognition and classification module for subsequent material retrieval and personalized recommendation. The media files uploaded by the user are first received by the file upload unit, and the preprocessing unit performs necessary format conversion, size adjustment and other processing on the file to adapt to the subsequent feature extraction. The feature extraction unit uses a deep learning model to extract key features of the media file, such as color, shape, texture, etc. The classification unit uses a classification algorithm based on the extracted features to automatically classify the media file, such as image, audio, video, etc. The result output unit displays the classification results in a user-friendly manner, such as displaying classification labels, confidence levels, etc. through an interface;

[0042] The material library stores a wealth of design resources, such as vector icons, pictures, audio, video materials and templates. The resource storage subunit is responsible for storing all design resources. The search engine subunit provides a search function, allowing users to search for materials based on keywords, tags or categories. The classification management subunit is responsible for the classification management of materials, ensuring that the materials can be stored and displayed in order by category.

[0043] The network environment monitoring unit monitors the network status of the target playback terminal in real time, such as bandwidth, delay and other key indicators. The device performance detection unit is responsible for detecting the hardware performance of the playback terminal, such as processor model, memory size, screen resolution, etc. The encoding strategy decision unit determines the optimal encoding format and parameters based on the data provided by the network environment monitoring unit and the device performance detection unit, combined with user preferences and content type. The encoder unit encodes the media content according to the instructions of the encoding strategy decision unit to generate a media stream suitable for the target playback terminal. The feedback and optimization unit collects playback quality feedback from the playback terminal and user usage feedback for optimizing encoding strategies and parameters;

[0044] The output and publishing module can publish with one click. The format conversion unit is responsible for converting the design work from the internal format to the export format selected by the user. The template management unit stores and manages the preset templates and sizes for different social media platforms. The automatic adjustment unit automatically adjusts the layout and size of the design work according to the template and size selected by the user.

[0045] The user authentication unit processes the user's login and authorization to ensure that the user has the right to publish content to the target platform. The publishing interface unit connects with the API interface of each target platform to realize the one-click publishing function. The publishing configuration unit allows the user to configure the detailed parameters of the publication, such as title, description, tags, etc. The user interface unit provides a user interface, including an interface for selecting the export format and configuring the export options, an interface for selecting the template and viewing the adjustment effect, and an interface for configuring the publishing parameters and initiating the publishing request;

[0046] The user behavior data collection unit is responsible for collecting user behavior data, including historical viewing records, click behaviors, dwell time, rating feedback and other data. The user portrait construction unit constructs user portraits based on user behavior data, including user interest preferences, viewing habits, etc. The content feature extraction unit analyzes the content features of media resources, such as the theme, tag, duration, cast, director, etc. of the video; the genre, rhythm, emotion, etc. of the audio; the keywords and subject classification of the article, etc. The recommendation algorithm unit uses collaborative filtering combined with user portraits and content features to calculate the user's preference for unwatched resources and generate a recommendation list. The recommendation result display unit is responsible for displaying the recommendation list generated by the recommendation algorithm unit on the front-end interface in a user-friendly manner, such as sorting by interest, displaying by category, etc. The feedback and optimization unit collects user feedback on the recommendation results, which is used to optimize the recommendation algorithm and user portrait model to improve the accuracy of the recommendation.

[0047] Application of blockchain technology in media copyright management and protection module: The copyright registration unit is responsible for receiving and processing copyright registration requests, writing the digital fingerprint and related information of the work into the blockchain, and generating a unique copyright identifier. The smart contract unit writes and deploys smart contracts to realize the automated processing of copyright authorization. The copyright monitoring unit uses blockchain technology and network monitoring tools to monitor copyright infringement on the network. The user management unit manages the identities and permissions of various users such as copyright creators, copyright holders, and copyright buyers. The blockchain network unit provides the operating environment and infrastructure support for the blockchain network.

[0048] In one embodiment, for the above-mentioned creative design tool, the creative design tool includes a vector graphics editor, an image processing unit, a video editing unit, and a 3D modeling and rendering unit. The vector graphics editor provides the ability to draw, edit and export vector graphics, and supports designers to create design elements such as icons and illustrations. The vector graphics editor interacts with the resource management and material library, and saves the created or edited vector graphics to the resource management and material library. At the same time, the vector graphics editor receives vector graphics from the resource management and material library for editing. The image processing unit includes image editing functions such as color adjustment, cropping, and repair, and supports RAW format to meet the needs of professional photographers and designers. The image processing unit obtains the original image file from the resource management and material library, edits it, and then saves the processed image back to the resource management and material library or directly uses it for video editing and 3D modeling. The video editing unit integrates functions such as video editing, special effects adding, and audio editing, supports multi-track editing and timeline management, and is convenient for making video works. It interacts with the resource management and material library to obtain audio and video materials for editing. The video editing unit receives the images processed by the image processing unit as video materials. After editing, the video works are saved to the resource management and material library or exported directly. The 3D modeling and rendering unit supports 3D modeling, physical engine and advanced rendering technology to realize a complete 3D design process. The 3D modeling and rendering unit obtains 3D resources such as textures and materials from the resource management and material library. The 3D modeling and rendering unit needs the images provided by the image processing unit as textures during the modeling process. After rendering is completed, the 3D modeling and rendering unit saves the 3D model and its rendering results to the resource management and material library or directly uses them in scenes such as video editing and display.

[0049] In one embodiment, for the above-mentioned automatic identification and classification module, the automatic identification and classification module includes a file upload unit, a preprocessing unit, a feature extraction unit, a classification unit and a result output unit. The file upload unit is responsible for receiving media files uploaded by users, such as images, audio, video, etc. The file upload unit passes the uploaded files to the preprocessing unit. The preprocessing unit performs necessary preprocessing on the uploaded media files, such as format conversion, size adjustment, noise removal, etc., to ensure that the files meet the input requirements of the deep learning model. The preprocessing unit receives the files from the file upload unit, and passes the data to the feature extraction unit after processing. The feature extraction unit uses the deep learning model to extract key features from the preprocessed media files. The feature extraction unit receives the data from the preprocessing unit, extracts the features and passes them to the classification unit. The classification unit uses a classification algorithm to classify the media files based on the extracted features. The classification unit passes the classification results to the result output unit. The result output unit displays the classification results in a user-friendly manner, such as displaying classification labels, confidence levels, etc. through an interface.

[0050] In one embodiment, for the above-mentioned resource management and material library, the resource management and material library include a material library, project management and a version control unit. The material library provides rich design resources, including vector icons, pictures, audio, video materials and templates, and supports users to search and classify so as to quickly find required materials. Project management supports project creation, task assignment, progress tracking and team collaboration to help users better manage design projects. The version control unit is responsible for automatic saving and management of design versions, including version creation, deletion, comparison and rollback operations. When the user makes modifications in the design, the version control unit will automatically save the current version. The user can view the historical version list through the version control unit and select the version that needs to be rolled back for recovery. The version control unit also provides a version comparison function to help users understand the differences between different versions.

[0051] In one embodiment, for the above-mentioned material library, the material library includes a resource storage subunit, a search engine subunit and a classification management subunit. The resource storage subunit is responsible for storing all design resources, including vector icons, pictures, audio, video and other files. The search engine subunit provides a search function, allowing users to search for materials based on keywords, tags or categories. The classification management subunit is responsible for the classification management of materials to ensure that the materials can be stored and displayed in order by category. Users submit search requests through the search engine subunit, and the search engine subunit retrieves qualified materials from the resource storage subunit and displays the results to users by category through the classification management subunit.

[0052] In one embodiment, for the above-mentioned project management, the project management includes a project management unit and a team collaboration unit. The project management unit is responsible for the creation, deletion, editing, task assignment and progress tracking of projects. The team collaboration unit provides communication and collaboration tools between team members, such as message notifications, task comments, etc. Users create projects and assign tasks to team members through the project management unit. The team collaboration unit is responsible for processing communication and collaboration information between team members, such as task progress updates, comments, etc., and synchronizing the communication and collaboration information between team members to the project management unit so that all members can keep abreast of project dynamics.

[0053] In one embodiment, for the above-mentioned adaptive media coding technology module, the adaptive media coding technology module includes a network environment monitoring unit, a device performance detection unit, a coding strategy decision unit, an encoder unit, and a feedback and optimization unit. The network environment monitoring unit is responsible for real-time monitoring of the network status of the target playback terminal, including key indicators such as bandwidth and delay. The device performance detection unit is responsible for detecting the hardware performance of the playback terminal, such as processor model, memory size, screen resolution, etc. The coding strategy decision unit decides the optimal coding format and parameters based on the data provided by the network environment monitoring unit and the device performance detection unit, combined with user preferences and content type. The encoder unit encodes the media content according to the instructions of the coding strategy decision unit to generate a media stream suitable for the target playback terminal. The feedback and optimization unit collects playback quality feedback (such as freeze, buffering time, etc.) from the playback terminal, and User usage feedback is used to optimize encoding strategies and parameters. The network environment monitoring unit provides real-time network status data to the encoding strategy decision unit as an important basis for encoding strategy decisions. The device performance detection unit provides the encoding strategy decision unit with the hardware performance data of the playback terminal to help the decision unit understand the processing capabilities of the device. The preference information (such as image quality priority, traffic saving, etc.) entered by the user through the setting interface or the playback control interface directly affects the selection of the encoding strategy. The encoding strategy decision unit sends the decided encoding format and parameter instructions to the encoder unit for actual encoding processing. The encoder unit sends the encoded media stream to the playback terminal for playback. The playback quality feedback and user usage feedback generated by the playback terminal during the playback process are collected for subsequent optimization work. The feedback and optimization unit uses the collected feedback data to optimize the encoding strategy and improve the accuracy and efficiency of encoding.

[0054] In one embodiment, for the above-mentioned output and publishing module, the output and publishing module includes a format conversion unit, a template management unit, an automatic adjustment unit, a user authentication unit, a publishing interface unit, a publishing configuration unit and a user interface unit. The format conversion unit is responsible for converting the design work from the internal format to the export format selected by the user. The template management unit stores and manages preset templates and sizes for different social media platforms. The automatic adjustment unit automatically adjusts the layout and size of the design work according to the template and size selected by the user. The user authentication unit handles the user's login and authorization to ensure that the user has the right to publish content to the target platform. The publishing interface unit is connected to the API interface of each target platform (such as WordPress, Facebook, Twitter, etc.) , realizing the one-key publishing function, the publishing configuration unit allows the user to configure the detailed parameters of the publishing, such as title, description, tags, etc. The user interface unit provides a user interface, including an interface for selecting the export format and configuring the export options, an interface for selecting the template and viewing the adjustment effect, and an interface for configuring the publishing parameters and initiating the publishing request. After the user selects the export format through the interface, the user interface unit passes the user's selection to the format conversion unit for processing. After the user selects the template and size through the interface, the user interface unit passes the selection result to the template management unit and the automatic adjustment unit to automatically adjust the design work. After the user configures the publishing parameters through the interface and initiates the publishing request, the user interface unit passes the configuration information to the publishing configuration unit and triggers the publishing interface unit to perform the actual publishing operation.

[0055] In one embodiment, for the above-mentioned personalized recommendation module, the personalized recommendation module includes a user behavior data collection unit, a user portrait construction unit, a content feature extraction unit, a recommendation algorithm unit, a recommendation result display unit and a feedback and optimization unit. The user behavior data collection unit is responsible for collecting user behavior data, including historical viewing records, click behaviors, dwell time, rating feedback and other data. The user portrait construction unit constructs a user portrait based on the user behavior data, including the user's interest preferences, viewing habits, etc. The content feature extraction unit analyzes the content features of media resources, such as the theme, tag, duration, cast, director, etc. of the video; the genre, rhythm, emotion, etc. of the audio; the keywords, subject classification, etc. of the article; the recommendation algorithm unit uses collaborative filtering combined with user portraits and content features to calculate the user's preference for unwatched resources and generate a recommendation list; the recommendation result display unit is responsible for presenting the recommendations generated by the recommendation algorithm unit to the user. The list is displayed on the front-end interface in a user-friendly manner, such as sorting by interest, displaying by category, etc. The feedback and optimization unit collects user feedback on the recommendation results (such as clicks, viewing time, ratings, skips, etc.) to optimize the recommendation algorithm and user portrait model and improve the accuracy of recommendations. The user behavior data collection unit passes the collected user behavior data to the user portrait construction unit. The content feature extraction unit passes the analyzed media resource content feature data to the recommendation algorithm unit. The recommendation algorithm unit simultaneously receives the user portrait data constructed by the user portrait construction unit and the content feature data extracted by the content feature extraction unit, performs matching and calculation, and generates a recommendation list. The recommendation algorithm unit passes the generated recommendation list to the recommendation result display unit, which is responsible for displaying it to the user on the front-end interface. User feedback on the recommendation results (such as clicks, viewing time, etc.) is collected by the recommendation result display unit and then passed to the feedback and optimization unit.

[0056] In one embodiment, for the above-mentioned media copyright management and protection module, the media copyright management and protection module includes a copyright registration unit, a smart contract unit, a copyright monitoring unit, a user management unit and a blockchain network unit. The copyright registration unit is responsible for receiving and processing copyright registration requests, writing the digital fingerprint and related information of the work into the blockchain, and generating a unique copyright identifier. The smart contract unit writes and deploys smart contracts to realize the automated processing of copyright authorization. The smart contract automatically executes the authorization and payment process according to preset conditions to ensure the accuracy and efficiency of the transaction. The copyright monitoring unit uses blockchain technology and network monitoring tools to monitor copyright infringement on the network. Once an infringement is found, the copyright monitoring unit provides evidence and notifies the copyright holder. The user management The management unit manages the identities and permissions of various users, such as copyright creators, copyright holders, and copyright buyers, to ensure that users can safely and legally use the various functions provided by the system. The blockchain network unit provides the operating environment and infrastructure support for the blockchain network, including the deployment of blockchain nodes, the implementation of consensus algorithms, the storage and verification of data, etc. The copyright registration unit writes the digital fingerprint and related information of the work into the blockchain, and performs distributed storage and verification through the blockchain network unit. The smart contract unit writes and deploys smart contracts to the blockchain network unit, and the blockchain network unit is responsible for the execution and verification of smart contracts. After the copyright monitoring unit detects infringement, it queries the relevant copyright information through the blockchain network unit and notifies the user management unit to deal with the infringing user.

[0057] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital media design platform based on computer technology, characterized in that: include: Creative design tools: provide users with various functions required for digital media creation; Automatic identification and classification module: responsible for automatically identifying and classifying uploaded media files; Resource management and material library: Provide design resources, including vector icons, pictures, audio, video materials and templates, and support project creation, task assignment, progress tracking and collaboration; Adaptive media coding technology module: intelligently selects coding formats and parameters based on the target playback terminal; Output and publishing module: export design files to a user-specified location or publish directly to the target platform; Personalized recommendation module: Provides personalized recommendation services by analyzing users' historical viewing behavior, preferences and media content characteristics; Media copyright management and protection module: Use blockchain technology to ensure the immutability and transparency of media copyrights, and automate copyright authorization and payment processes through smart contracts; The design file generated by the creative design tool will be passed to the automatic identification and classification module and the resource management and material library as original media data. The automatic identification and classification module will feed back the identification and classification results to the resource management and material library. The classification results are used to trigger the recommendation logic of the personalized recommendation module. The adaptive media encoding technology module obtains the media files to be encoded from the resource management and material library, performs encoding optimization according to the analysis results, and then provides the encoded files to the output and publishing module. The media copyright management and protection module interacts with the resource management and material library.

2. A computer technology-based digital media design platform according to claim 1, characterized in that: The creative design tool includes a vector graphics editor, an image processing unit, a video editing unit, and a 3D modeling and rendering unit. The vector graphics editor provides the ability to draw, edit, and export vector graphics. The vector graphics editor interacts with the resource management and material library to save the created or edited vector graphics to the resource management and material library. At the same time, the vector graphics editor receives vector graphics from the resource management and material library for editing. The image processing unit includes an image editing function. The image processing unit obtains the original image file from the resource management and material library, edits it, and then saves the processed image back to the resource management and material library. The video editing unit interacts with the resource management and material library to obtain audio and video materials for editing. The video editing unit receives the image processed by the image processing unit as the video material. After the editing is completed, the video work is saved to the resource management and material library or directly exported. The 3D modeling and rendering unit supports 3D modeling, physical engine and advanced rendering technology. The 3D modeling and rendering unit obtains 3D resources from the resource management and material library. The 3D modeling and rendering unit needs the image provided by the image processing unit as a texture during the modeling process. After the rendering is completed, the 3D modeling and rendering unit saves the 3D model and its rendering result to the resource management and material library.

3. A computer technology-based digital media design platform according to claim 1, characterized in that: The automatic identification and classification module includes a file uploading unit, a preprocessing unit, a feature extraction unit, a classification unit and a result output unit. The file uploading unit is responsible for receiving media files uploaded by users. The file uploading unit passes the uploaded files to the preprocessing unit. The preprocessing unit preprocesses the uploaded media files. The preprocessing unit receives files from the file uploading unit and passes the data to the feature extraction unit after processing. The feature extraction unit uses a deep learning model to extract key features from the preprocessed media files. The feature extraction unit receives data from the preprocessing unit and passes it to the classification unit after extracting features. The classification unit classifies the media files based on the extracted features using a classification algorithm. The classification unit passes the classification results to the result output unit, and the result output unit displays the classification results.

4. A computer technology-based digital media design platform according to claim 1, characterized in that: The resource management and material library include a material library, project management and a version control unit. The material library provides design resources, including vector icons, pictures, audio, video materials and templates. The project management supports project creation, task assignment, progress tracking and team collaboration. The version control unit is responsible for the automatic saving and management of design versions. When the user makes modifications in the design, the version control unit will automatically save the current version. The user can view the historical version list through the version control unit and select the version that needs to be rolled back for recovery.

5. A computer technology-based digital media design platform according to claim 4, characterized in that: The material library includes a resource storage subunit, a search engine subunit and a classification management subunit. The resource storage subunit is responsible for storing all design resources. The search engine subunit provides a search function, allowing users to find materials based on keywords, tags or categories. The classification management subunit is responsible for the classification management of materials. Users submit search requests through the search engine subunit. The search engine subunit retrieves qualified materials from the resource storage subunit and displays the results to users by category through the classification management subunit.

6. A computer technology-based digital media design platform according to claim 4, characterized in that: The project management includes a project management unit and a team collaboration unit. The project management unit is responsible for creating, deleting, editing, task assignment and progress tracking of projects. The team collaboration unit provides communication and collaboration tools between team members. Users create projects and assign tasks to team members through the project management unit. The team collaboration unit is responsible for processing communication and collaboration information between team members and synchronizing the communication and collaboration information between team members to the project management unit.

7. The computer-based digital media design platform according to claim 1, characterized in that: The adaptive media coding technology module includes a network environment monitoring unit, a device performance detection unit, a coding strategy decision unit, an encoder unit and a feedback and optimization unit. The network environment monitoring unit is responsible for real-time monitoring of the network status of the target playback terminal. The device performance detection unit is responsible for detecting the hardware performance of the playback terminal. The coding strategy decision unit determines the optimal coding format and parameters based on the data provided by the network environment monitoring unit and the device performance detection unit, combined with user preferences and content types. The encoder unit encodes the media content according to the instructions of the coding strategy decision unit to generate a media stream suitable for the target playback terminal. The feedback and optimization unit collects playback quality feedback from the playback terminal and user usage feedback for optimizing the coding strategy and parameters. The network environment monitoring unit provides real-time network status data to the encoding strategy decision unit as a basis for encoding strategy decision. The device performance detection unit provides the encoding strategy decision unit with hardware performance data of the playback terminal to help the decision unit understand the processing capability of the device. The preference information input by the user through the setting interface or the playback control interface directly affects the selection of the encoding strategy. The encoding strategy decision unit sends the decided encoding format and parameter instructions to the encoder unit for actual encoding processing. The encoder unit sends the encoded media stream to the playback terminal for playback. The playback quality feedback and user usage feedback generated by the playback terminal during the playback process are collected for subsequent optimization work. The feedback and optimization unit uses the collected feedback data to optimize the encoding strategy.

8. The computer-based digital media design platform according to claim 1, characterized in that: The output and publishing module includes a format conversion unit, a template management unit, an automatic adjustment unit, a user authentication unit, a publishing interface unit, a publishing configuration unit and a user interface unit. The format conversion unit is responsible for converting the design work from the internal format to the export format selected by the user. The template management unit stores and manages preset templates and sizes for different social media platforms. The automatic adjustment unit automatically adjusts the layout and size of the design work according to the template and size selected by the user. The user authentication unit processes the login and authorization of the user. The publishing interface unit is connected to the API interface of each target platform to realize the one-key publishing function. The publishing configuration unit allows the user to configure the detailed parameters of the publication. The user interface unit provides a user interface, including an interface for selecting the export format and configuring the export options, an interface for selecting the template and viewing the adjustment effect, and an interface for configuring the publishing parameters and initiating the publishing request. After the user selects the export format through the interface, the user interface unit passes the user's selection to the format conversion unit for processing. After the user selects the template and size through the interface, the user interface unit passes the selection result to the template management unit and the automatic adjustment unit. After the user configures the publishing parameters through the interface and initiates the publishing request, the user interface unit passes the configuration information to the publishing configuration unit and triggers the publishing interface unit to perform the actual publishing operation.

9. The computer-based digital media design platform according to claim 1, characterized in that: The personalized recommendation module includes a user behavior data collection unit, a user portrait construction unit, a content feature extraction unit, a recommendation algorithm unit, a recommendation result display unit, and a feedback and optimization unit. The user behavior data collection unit is responsible for collecting user behavior data, the user portrait construction unit constructs a user portrait based on the user behavior data, the content feature extraction unit analyzes the content features of media resources, the recommendation algorithm unit uses collaborative filtering to combine user portraits and content features, calculates the user's preference for unwatched resources, and generates a recommendation list, the recommendation result display unit is responsible for displaying the recommendation list generated by the recommendation algorithm unit on the front-end interface in a user-friendly manner, and the feedback and optimization unit is responsible for displaying the recommendation list generated by the recommendation algorithm unit on the front-end interface in a user-friendly manner. The optimization unit collects user feedback on the recommendation results for optimizing the recommendation algorithm and the user portrait model. The user behavior data collection unit passes the collected user behavior data to the user portrait construction unit. The content feature extraction unit passes the analyzed media resource content feature data to the recommendation algorithm unit. The recommendation algorithm unit simultaneously receives the user portrait data constructed by the user portrait construction unit and the content feature data extracted by the content feature extraction unit, performs matching and calculation, and generates a recommendation list. The recommendation algorithm unit passes the generated recommendation list to the recommendation result display unit. The user feedback on the recommendation results is collected by the recommendation result display unit and then passed to the feedback and optimization unit.

10. The computer-based digital media design platform according to claim 1, characterized in that: The media copyright management and protection module includes a copyright registration unit, a smart contract unit, a copyright monitoring unit, a user management unit and a blockchain network unit. The copyright registration unit is responsible for receiving and processing copyright registration requests, writing the digital fingerprint and related information of the work into the blockchain, and generating a unique copyright identifier. The smart contract unit writes and deploys smart contracts to realize the automated processing of copyright authorization. The smart contract automatically executes the authorization and payment process according to preset conditions. The copyright monitoring unit uses blockchain technology and network monitoring tools to monitor copyright infringement on the network. Once an infringement is found, the copyright monitoring unit provides evidence and notifies the copyright holder. The user management unit manages the identity and authority of various users. The blockchain network unit provides the operating environment and infrastructure support of the blockchain network. The copyright registration unit writes the digital fingerprint and related information of the work into the blockchain, and performs distributed storage and verification through the blockchain network unit. The smart contract unit writes and deploys smart contracts to the blockchain network unit, and the blockchain network unit is responsible for the execution and verification of the smart contracts. After the copyright monitoring unit detects the infringement, it queries the relevant copyright information through the blockchain network unit and notifies the user management unit to handle the infringing user.

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