Cultural image creation system based on artificial intelligence

Abstract

The invention discloses a culture image creation system based on artificial intelligence, and relates to the field of artificial intelligence, and the system comprises a data collection module which is used for obtaining culture data and user data information; the intelligent analysis module is used for analyzing the culture data, acquiring corresponding culture elements and constructing a culture database; the user analysis module is used for analyzing and processing the user data and constructing a user portrait feature database; the creation adaptation module is used for performing comparative analysis according to the culture database and the user portrait feature database to obtain a user culture adaptation element set; the creation association module is used for performing multi-level association analysis according to the user culture adaptation element set and constructing a creation association graph; the image creation module is used for performing fusion creation analysis according to the creation association graph corresponding to the user to generate fusion image data; according to the invention, the flexibility and creation efficiency in the image creation process are improved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a cultural image creation system based on artificial intelligence. Background Technology

[0002] With the development of the times, the inheritance and promotion of culture is urgent. As a direct medium of communication, images can play an important role in this regard, but traditional image creation has many limitations. With the rapid development of artificial intelligence technology in recent years, new opportunities have been brought to image creation. Artificial intelligence technology can improve creation efficiency to a certain extent, make full use of materials, and promote cultural events with more vivid and innovative image works, thereby helping to promote the dissemination and development of various excellent cultures in the new era.

[0003] A search revealed Chinese patent CN120568156A, which discloses a full-process AI video creation method and system based on diffusion-based image generation. This method relates to the field of AI video creation and includes: acquiring user-input natural language creation instructions and parsing to extract subject element datasets and visual style tag datasets; generating a sequential task sequence including script generation, storyboard design, image generation, and video compositing; generating a script framework and storyboard dataset using a large model; calculating the semantic similarity between storyboard content and subject elements and performing supplementary optimization; generating diffusion model prompts and obtaining rendering parameters to generate rendered images; compositing the video after verifying visual coverage, and adjusting based on feedback to achieve the final output. This invention can construct a complete control chain from creation guidance to output generation, meeting the customized generation needs in complex creation scenarios.

[0004] Compared with existing technologies, the Chinese patent with patent number CN120568156A can achieve seamless transfer of creative intent from text to image by constructing a full-process task sequence of natural language instruction parsing, script generation, storyboard design, image rendering and video synthesis, thereby improving creative efficiency.

[0005] However, in actual use, the aforementioned systems and methods cannot effectively combine the personalized needs of user data information with the needs of image creation events, thus affecting the flexibility of the image creation process. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies in terms of flexibility by proposing an artificial intelligence-based cultural image creation system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: An artificial intelligence-based cultural image creation system includes: The data acquisition module is used to acquire cultural data, set up intelligent detection terminals, acquire user data information through intelligent detection terminals, and perform tagging processing on user data information; The intelligent parsing module is used to parse and process cultural data to obtain corresponding cultural events and cultural elements, and to build a cultural database. The user analysis module is used to analyze and process user data information, obtain user feature elements corresponding to the corresponding user data information, and build a user profile feature database. The creation and adaptation module is used to compare and analyze the user profile feature database with the cultural database to obtain the user's cultural adaptation element set. The creation association module is used to perform multi-level association analysis on the user's cultural adaptation element set and construct the creation association graph corresponding to the user. The image creation module is used to obtain the creation association map corresponding to the user, perform fusion creation analysis on the corresponding creation association map according to the elements of the corresponding level, and generate fused image data.

[0008] The above technical solution further includes: the data acquisition module includes: The cultural data collection unit is used to set up a cultural data collection terminal and collect relevant cultural data through the cultural data collection terminal. The cultural data includes information on cultural events, cultural figures, cultural scenes, and cultural education. The user collection unit is used to set up an intelligent detection terminal and collect relevant user data information through the intelligent detection terminal. The user data information includes objective basic information of the user and subjective information entered by the user. The data processing unit marks and processes the acquired cultural data and user data information separately.

[0009] Furthermore, the intelligent parsing module includes: The event parsing unit is used to extract event features from the corresponding cultural event information within the cultural data according to the corresponding data type, perform semantic matching on the obtained event feature extraction results, and generate cultural event elements based on the semantic matching results. The character analysis unit is used to extract the character features of the corresponding cultural figures in the cultural data, perform semantic matching based on the character feature extraction results, and generate cultural figure elements. The scene parsing unit is used to extract scene detail features from the corresponding cultural scene information in the cultural data, perform semantic matching based on the feature extraction results, and generate cultural scene elements. The database construction unit sequentially classifies the obtained cultural event elements, cultural figure elements, and cultural scene elements into hierarchical categories, generating a hierarchical classification system, and constructs a cultural database based on the hierarchical classification system.

[0010] Furthermore, the user analysis module includes: The user feature extraction unit is used to acquire user data information, extract features from the corresponding objective basic information and subjective input information of the user data information, and obtain the corresponding objective feature data and subjective feature data. The user profile construction unit is used to traverse and analyze objective feature data and subjective feature data with corresponding cultural elements in the cultural database, obtain user feature elements corresponding to the user data information, describe the obtained user feature elements hierarchically according to the corresponding hierarchical classification system in the cultural data, and construct the user profile feature database based on the hierarchical description results.

[0011] Furthermore, the creation adaptation module includes: The factor classification unit is used to obtain the corresponding cultural element information in the cultural database for classification processing, set the objective evaluation standard and the flexible evaluation standard of the image, match the corresponding cultural element information with the objective evaluation standard and the flexible evaluation standard of the image respectively, obtain the type of the corresponding cultural element information, and mark it in the cultural database according to the obtained type. The adaptation analysis unit is used to compare and analyze the classification results of the corresponding user feature elements in the user profile feature database with the corresponding cultural element information in the cultural database, and obtain the set of user cultural adaptation elements in the cultural database to which the corresponding user feature elements belong.

[0012] Furthermore, the creation association module includes: The hierarchical association unit is used to perform multi-level association analysis on the user culture adaptation element set. It maps the cultural element information corresponding to the corresponding user feature elements in the user culture adaptation element set to the corresponding positions in the corresponding hierarchical classification system in the cultural database. Based on the mapping results, the feature association data between each user feature element in the user culture adaptation element set is obtained. The creation association unit is used to analyze and process feature association data and set up corresponding creation association maps.

[0013] Furthermore, the creation association unit includes: The creative analysis subunit is used to obtain the feature association data corresponding to each user feature element in the user cultural adaptation element set and its corresponding cultural element, and to set the creative element information corresponding to the corresponding user feature element according to the type of image objective evaluation standard and image flexible evaluation standard marker corresponding to the corresponding cultural element information. The creation integration subunit is used to progressively integrate the characteristic correlation data between various creative elements to construct a creative correlation graph.

[0014] Furthermore, the image creation module includes: The element creation unit is used to create elements based on the corresponding levels of the creative element information within the creative association map. It performs image analysis on the corresponding creative element information based on artificial intelligence algorithms and obtains the element image information corresponding to the creative element information corresponding to the corresponding user data information based on the image analysis results. The integrated creation unit acquires the element image information corresponding to the creative element information at each level within the creation association map. It then performs fusion processing according to the corresponding order of the creative element information at each level within the creation association map. Based on the corresponding time information, it acquires the level-fused image and level-compensated image corresponding to each level. Based on the time information corresponding to the level-fused image and level-compensated image, it sets corresponding sequence frames. The sequence frames are then analyzed for fusion creation according to the order of the time information to generate fused image data. This fused image data consists of images corresponding to the user data information under the corresponding cultural event information.

[0015] The present invention has the following beneficial effects: 0. In this invention, cultural data is parsed and processed to obtain cultural elements corresponding to different cultural events. In the process of constructing a cultural database, the data is parsed in layers according to different events, people and scenes to obtain the corresponding cultural elements. The cultural elements in the cultural database are then classified and labeled, which provides a foundation for creating corresponding images based on the personalized needs of user data information, thereby improving the efficiency and flexibility of the image creation process.

[0016] 1. In this invention, by analyzing and processing user data information, feature data corresponding to different user data information is obtained. A user profile feature database is constructed based on the obtained feature data. By comparing and analyzing the user profile feature database and the cultural database, a corresponding set of user cultural adaptation elements is obtained. Creative analysis is performed on the set of user cultural adaptation elements to obtain the hierarchical fusion image and hierarchical compensation image of the corresponding sequence frame. Fusion creative analysis is performed on the corresponding sequence frame to generate fusion image data, thereby satisfying the personalized needs of each user in the image creation process to a certain extent. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of a cultural image creation system based on artificial intelligence proposed in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 like Figure 1 As shown, the present invention proposes an artificial intelligence-based cultural image creation system, comprising: The data acquisition module is used to acquire cultural data, set up intelligent detection terminals, acquire user data information through intelligent detection terminals, and perform tagging processing on user data information; The intelligent parsing module is used to parse and process cultural data to obtain corresponding cultural events and cultural elements, and to build a cultural database. The user analysis module is used to analyze and process user data information, obtain user feature elements corresponding to the corresponding user data information, and build a user profile feature database. The creation and adaptation module is used to compare and analyze the user profile feature database with the cultural database to obtain the user's cultural adaptation element set. The creation association module is used to perform multi-level association analysis on the user's cultural adaptation element set and construct the creation association graph corresponding to the user. The image creation module is used to obtain the creation association map corresponding to the user, perform fusion creation analysis on the corresponding creation association map according to the elements of the corresponding level, and generate fused image data.

[0020] As described above, this invention analyzes and processes cultural data to obtain cultural elements related to events, figures, and scenes corresponding to the cultural data. A cultural database is then established based on these cultural elements, and these elements are marked. Furthermore, by analyzing and processing the acquired user data, a corresponding user profile feature database is constructed. This database is then adapted to the corresponding cultural database. Multi-level association analysis is performed based on the obtained user cultural adaptation element set to construct a corresponding creative association graph. Finally, fused image data is generated based on this creative association graph. This approach improves the flexibility of the image creation process to a certain extent, thereby enhancing the cultural impression on the user.

[0021] In specific implementation, the data acquisition module includes: A cultural data collection unit is used to set up a cultural data collection terminal to collect relevant cultural data. This cultural data includes information on cultural events, cultural figures, cultural scenes, and cultural education. Taking the Yimeng Mountain Red Culture event during the revolutionary war period as an example, the data includes: Information on cultural events includes the Battle of Menglianggu, the Six Sisters of Yimeng, and the breakout battle of Daqingshan. Information on cultural figures includes basic identity data (such as Red Sister Ming Deying, Luo Binghui, etc.), core profiles, image materials, and records of core deeds of the figures. Cultural scene information includes core scene records corresponding to cultural event information and cultural figure information (e.g., the battlefield site of the Menglianggu Campaign, the former headquarters of the Yimeng Revolutionary Base, the Yimeng Six Sisters' Support Production Courtyard, etc.), spatial structure records (e.g., architectural layout, terrain features, environmental details, etc.), scene function records (e.g., operating room, pharmacy, ward, support production courtyard, etc.), and scene atmosphere element records (e.g., visual atmosphere, auditory atmosphere, tactile atmosphere, and other related descriptive materials). Cultural and educational information includes information on core educational themes, etc. The user data collection unit is used to set up an intelligent detection terminal and collect relevant user data information through the intelligent detection terminal. The user data information includes objective basic information of the user and subjective input information of the user, wherein: User objective basic information includes gender, physical appearance, and photos; User-submitted information includes descriptions of needs, preferences, personal information, and feedback / suggestions. The data processing unit marks and processes the acquired cultural data and user data information separately. It should be further explained that, in the specific implementation process, when the data processing unit marks the obtained cultural data and user data information respectively, it marks the event type corresponding to the corresponding cultural data and the user account corresponding to the corresponding user data information, which facilitates the subsequent analysis and processing by the intelligent parsing module and the user analysis module, thereby improving the efficiency of the data analysis process.

[0022] In specific implementation, the intelligent parsing module includes: The event parsing unit is used to extract event features from the corresponding cultural event information within the cultural data according to the corresponding data type, perform semantic matching on the obtained event feature extraction results, and generate cultural event elements based on the semantic matching results. That is, it analyzes and processes cultural event information of the same type according to the labeling results of the corresponding event type, and generates cultural event elements based on the corresponding semantic matching results within the artificial intelligence algorithm. The generated cultural event elements include corresponding event type elements, event process elements, event association elements, etc. The character analysis unit is used to extract the character features of the corresponding cultural figures in the cultural data, perform semantic matching based on the character feature extraction results, and generate cultural figure elements, including identity and image elements, behavioral and deed elements, etc. The scene parsing unit is used to extract scene detail features from the corresponding cultural scene information in the cultural data, perform semantic matching based on the feature extraction results, and generate cultural scene elements, including spatial functional elements, era and regional elements, and atmosphere and sensory elements, etc. The database construction unit sequentially classifies the obtained cultural event elements, cultural figure elements, and cultural scene elements into hierarchical categories, generating a hierarchical classification system, and constructs a cultural database based on the hierarchical classification system. It should be further explained that, in the specific implementation process, during the construction of the cultural database, multiple first-level levels are set according to the event types corresponding to the cultural event elements. Multiple second-level levels are then set according to the cultural figures involved in each event type of the first-level level. Multiple third-level levels are then set according to the cultural scene elements corresponding to the cultural figures in each second-level level. The second and third levels are then sorted according to the event process elements corresponding to the respective cultural event elements. Based on the sorting results of each level, a corresponding hierarchical classification system is generated. The cultural database is constructed based on this hierarchical classification system, enabling the classification and processing of relevant video creation materials, thereby improving the efficiency of the video creation process.

[0023] In practical implementation, the user analysis module includes: The user feature extraction unit is used to acquire user data information, and to extract features from the corresponding objective basic information and subjective input information of the user data information to obtain the corresponding objective feature data and subjective feature data, wherein: Objective feature data includes corresponding identity recognition feature data, including gender features, facial features, etc.; Subjective feature data is obtained by analyzing and processing the corresponding user cultural input information using natural language processing algorithms in artificial intelligence technology, including demand and preference features, feedback and evaluation features, etc. The user profile construction unit is used to traverse and analyze objective feature data and subjective feature data with corresponding cultural elements in the cultural database, obtain user feature elements corresponding to the corresponding user data information, describe the obtained user feature elements hierarchically according to the corresponding hierarchical classification system in the cultural data, and construct the user profile feature database based on the hierarchical description results. It should be further explained that, in the specific implementation process, when constructing the user profile feature database, the first priority is to compare and analyze the corresponding subjective feature data with the corresponding cultural event elements in the cultural database to obtain the first level. Based on the first level, the corresponding second and third levels of cultural elements are obtained based on the objective and subjective feature data corresponding to the user data information. In this process, the feature data corresponding to the user data information is marked as the user discrete feature set, and the corresponding cultural element dataset is set according to the corresponding hierarchical classification system in the cultural database. The user discrete feature set A and the cultural element dataset B are analyzed based on the Jaccard similarity coefficient. Obtain the corresponding overlap data; Based on the overlap data, the corresponding feature data and cultural elements in the corresponding user discrete feature set and cultural element dataset are compared and analyzed to obtain the corresponding comparison similarity. Based on historical comparative analysis data, a comparison similarity threshold is set, and the corresponding comparison similarity is compared and analyzed with the comparison similarity threshold. Feature data and cultural element information with a comparison similarity greater than or equal to the comparison similarity threshold are all marked as user feature elements. A corresponding user profile feature database is set according to the corresponding hierarchical classification system.

[0024] In specific implementation, the creation adaptation module includes: The factor classification unit is used to obtain the corresponding cultural element information in the cultural database for classification processing, set the objective evaluation standard and the flexible evaluation standard of the image, match the corresponding cultural element information with the objective evaluation standard and the flexible evaluation standard of the image respectively, obtain the type of the corresponding cultural element information, and mark it in the cultural database according to the obtained type. It should be further explained that, in the process of classifying and processing cultural element information, the objective evaluation criteria and flexible evaluation criteria for images are set based on the cultural data corresponding to the corresponding cultural element information in the cultural database. Statistical analysis is performed on the cultural data corresponding to the corresponding cultural element information to obtain the corresponding consistency information. Objective evaluation criteria are then set. If the consistency information is greater than or equal to the objective evaluation criteria, it is marked as image objective evaluation standard data; if the consistency information is less than the objective evaluation criteria, it is marked as image flexible evaluation standard data. Among these, the cultural elements corresponding to the image objective evaluation criteria are immutable data (e.g., behavioral and historical elements), while the cultural elements corresponding to the image flexible evaluation standard data are modifiable data (e.g., character identity and image elements). The adaptation analysis unit is used to compare and analyze the classification results of the corresponding user feature elements in the user profile feature database with the corresponding cultural element information in the cultural database, and obtain the set of user cultural adaptation elements in the cultural database to which the corresponding user feature elements belong.

[0025] In practice, the creation association module includes: The hierarchical association unit is used to perform multi-level association analysis on the user culture adaptation element set. It maps the cultural element information corresponding to the corresponding user feature elements in the user culture adaptation element set to the corresponding positions in the hierarchical progressive classification system in the cultural database. It obtains the position information of the corresponding user feature elements in each user culture adaptation element set. Based on the position information of each user feature element, it obtains the association between other cultural elements in the cultural database and the user feature elements corresponding to the user data information in the image creation process at each level. It sets feature association data according to the association relationship between the corresponding event process elements and other cultural elements. The feature association data is the image creation relationship between the event process elements corresponding to the corresponding user feature elements and other cultural elements, including three types: synchronous appearance, delayed appearance, and no appearance. The creation association unit is used to analyze and process feature association data and set up corresponding creation association maps, including: The creative analysis subunit is used to acquire the feature association data corresponding to each user feature element in the user cultural adaptation element set, as well as its corresponding cultural element. Based on the type of image objective evaluation standard and image flexible evaluation standard markers corresponding to the corresponding cultural element information, the creative element information corresponding to the user feature element is set, where: If the feature association data corresponding to the corresponding user feature element appears synchronously or delayed, then obtain the tag type corresponding to its cultural element information. If it is an image elasticity evaluation standard, then set the corresponding cultural element information as creative element information based on the user feature element. If it is an image objective evaluation standard, then do not set the corresponding cultural element information as creative element information. The creation integration subunit is used to progressively integrate the characteristic correlation data between various creative element information to construct a creative correlation graph. It should be further explained that, in the specific implementation process, during the construction of the creative association graph, process nodes and branch nodes are set according to the corresponding event process elements. The cultural element information set in the corresponding process nodes is sorted according to the feature association data, and the corresponding cultural element information is marked according to whether it involves creative element information. According to the corresponding element type and the event sequence in the process node, the corresponding branch nodes are set respectively. By progressively integrating the event nodes and branch nodes, the content in the corresponding nodes is sorted vertically and horizontally, that is, vertically according to the order of appearance, and horizontally according to the connection of each element, to generate the creative association graph, which can improve the efficiency and flexibility of the video creation process to a certain extent.

[0026] In practice, the image creation module includes: The element creation unit is used to create elements based on the corresponding levels of the creative element information within the creative association map. It performs image analysis on the corresponding creative element information based on artificial intelligence algorithms and obtains the element image information corresponding to the creative element information corresponding to the corresponding user data information based on the image analysis results. It should be further explained that, in the specific implementation process, during the creation of the element image information, the user feature data corresponding to the corresponding creative element information is obtained, and the AI ​​generation technology performs image processing on the corresponding creative element information based on the corresponding user feature data to obtain the corresponding creative element information to generate replacement image elements related to the user data information, and marks them as the element image information corresponding to the corresponding creative element information. The integrated creation unit acquires the element image information corresponding to the creative element information at each level within the creation association map, performs fusion processing according to the corresponding order of the creative element information at each level within the creation association map, acquires the level fused image and level compensation image corresponding to each level according to the corresponding time information, sets the corresponding sequence frames according to the time information corresponding to the level fused image and level compensation image, performs integrated creation analysis on each sequence frame according to the order of time information, and generates integrated image data. The integrated image data is the image corresponding to the corresponding user data information under the corresponding cultural event information. It should be further explained that, in the specific implementation process, the relevant element image information is integrated. Based on the sorting results of relevant cultural elements within the creation association graph, the image information of each element is integrated using an AI video generation model. "Static elements + action instructions" are set according to the relevant cultural element information. Data generation is performed on the information of each cultural element within the creation association graph using the AI ​​video generation model. The resulting layered fused image and layered compensated image are obtained at each level. The generated sequence frames are then fused and analyzed sequentially according to the connection order of the corresponding nodes within the creation association graph to generate fused image data. In this process, relevant cultural image data can be flexibly generated according to the needs of user data information to the greatest extent, thereby improving users' impression of culture and enhancing the publicity and educational effects of cultural events to a certain extent.

[0027] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cultural image creation system based on artificial intelligence, characterized in that, include: The data acquisition module is used to acquire cultural data, set up intelligent detection terminals, acquire user data information through intelligent detection terminals, and perform tagging processing on user data information; The intelligent parsing module is used to parse and process cultural data to obtain corresponding cultural events and cultural elements, and to build a cultural database. The user analysis module is used to analyze and process user data information, obtain user feature elements corresponding to the corresponding user data information, and build a user profile feature database. The creation and adaptation module is used to compare and analyze the user profile feature database with the cultural database to obtain the user's cultural adaptation element set. The creation association module is used to perform multi-level association analysis on the user's cultural adaptation element set and construct the creation association graph corresponding to the user. The image creation module is used to obtain the creation association map corresponding to the user, perform fusion creation analysis on the corresponding creation association map according to the elements of the corresponding level, and generate fused image data.

2. The cultural image creation system based on artificial intelligence according to claim 1, characterized in that, The data acquisition module includes: The cultural data collection unit is used to set up a cultural data collection terminal and collect relevant cultural data through the cultural data collection terminal. The cultural data includes information on cultural events, cultural figures, cultural scenes, and cultural education. The user collection unit is used to set up an intelligent detection terminal and collect relevant user data information through the intelligent detection terminal. The user data information includes objective basic information of the user and subjective information entered by the user. The data processing unit marks and processes the acquired cultural data and user data information separately.

3. The cultural image creation system based on artificial intelligence according to claim 2, characterized in that, The intelligent parsing module includes: The event parsing unit is used to extract event features from the corresponding cultural event information within the cultural data according to the corresponding data type, perform semantic matching on the obtained event feature extraction results, and generate cultural event elements based on the semantic matching results. The character analysis unit is used to extract the character features of the corresponding cultural figures in the cultural data, perform semantic matching based on the character feature extraction results, and generate cultural figure elements. The scene parsing unit is used to extract scene detail features from the corresponding cultural scene information in the cultural data, perform semantic matching based on the feature extraction results, and generate cultural scene elements. The database construction unit sequentially classifies the obtained cultural event elements, cultural figure elements, and cultural scene elements into hierarchical categories, generating a hierarchical classification system, and constructs a cultural database based on the hierarchical classification system.

4. The cultural image creation system based on artificial intelligence according to claim 3, characterized in that, The user analysis module includes: The user feature extraction unit is used to acquire user data information, extract features from the corresponding objective basic information and subjective input information of the user data information, and obtain the corresponding objective feature data and subjective feature data. The user profile construction unit is used to traverse and analyze objective feature data and subjective feature data with corresponding cultural elements in the cultural database, obtain user feature elements corresponding to the user data information, describe the obtained user feature elements hierarchically according to the corresponding hierarchical classification system in the cultural data, and construct the user profile feature database based on the hierarchical description results.

5. The cultural image creation system based on artificial intelligence according to claim 4, characterized in that, The creation adaptation module includes: The factor classification unit is used to obtain the corresponding cultural element information in the cultural database for classification processing, set the objective evaluation standard and the flexible evaluation standard of the image, match the corresponding cultural element information with the objective evaluation standard and the flexible evaluation standard of the image respectively, obtain the type of the corresponding cultural element information, and mark it in the cultural database according to the obtained type. The adaptation analysis unit is used to compare and analyze the classification results of the corresponding user feature elements in the user profile feature database with the corresponding cultural element information in the cultural database, and obtain the set of user cultural adaptation elements in the cultural database to which the corresponding user feature elements belong.

6. The cultural image creation system based on artificial intelligence according to claim 5, characterized in that, The creation association module includes: The hierarchical association unit is used to perform multi-level association analysis on the user culture adaptation element set. It maps the cultural element information corresponding to the corresponding user feature elements in the user culture adaptation element set to the corresponding positions in the corresponding hierarchical classification system in the cultural database. Based on the mapping results, the feature association data between each user feature element in the user culture adaptation element set is obtained. The creation association unit is used to analyze and process feature association data and set up corresponding creation association maps.

7. The cultural image creation system based on artificial intelligence according to claim 6, characterized in that, The creation-related unit includes: The creative analysis subunit is used to obtain the feature association data corresponding to each user feature element in the user cultural adaptation element set and its corresponding cultural element, and to set the creative element information corresponding to the corresponding user feature element according to the type of image objective evaluation standard and image flexible evaluation standard marker corresponding to the corresponding cultural element information. The creation integration subunit is used to progressively integrate the characteristic correlation data between various creative elements to construct a creative correlation graph.

8. The cultural image creation system based on artificial intelligence according to claim 7, characterized in that, The image creation module includes: The element creation unit is used to create elements based on the corresponding levels of the creative element information within the creative association map. It performs image analysis on the corresponding creative element information based on artificial intelligence algorithms and obtains the element image information corresponding to the creative element information corresponding to the corresponding user data information based on the image analysis results. The integrated creation unit acquires the element image information corresponding to the creative element information at each level within the creation association map. It then performs fusion processing according to the corresponding order of the creative element information at each level within the creation association map. Based on the corresponding time information, it acquires the level-fused image and level-compensated image corresponding to each level. Based on the time information corresponding to the level-fused image and level-compensated image, it sets corresponding sequence frames. The sequence frames are then analyzed for fusion creation according to the order of the time information to generate fused image data. This fused image data consists of images corresponding to the user data information under the corresponding cultural event information.

Images