Poster generation method, electronic device, storage medium, and computer program product

Abstract

This disclosure provides a poster generation method, an electronic device, a storage medium, and a computer program product. The poster generation method includes: configuring logic chains for poster elements in a poster canvas, the logic chains being used to convert content information of the poster elements into image data of the poster elements; in response to obtaining the content information of the poster elements, triggering the corresponding logic chain for the poster element, the logic chain processing the content information into image data of the poster element; rendering the image data into an image instance displayed in the poster canvas; and generating a poster based on the image instance.

Description

Technical Field

[0001] This disclosure relates to the technical fields of data processing, and in particular to a poster generation method, electronic device, storage medium, and computer program product. Background Technology

[0002] In the field of digital media content generation, there is a demand for high-frequency, real-time, and batch content replacement of fixed-format templates. This demand typically requires dynamically updating key information elements in the template, such as the main name, numerical data, descriptive text, and greetings, while maintaining a consistent overall visual style.

[0003] However, most related technologies remain at the level of "static template replacement." Once the design is completed, the element processing logic is fixed, making it impossible to perform intelligent processing (such as image cutout and lighting effects) during generation. Furthermore, there is a lack of flexible arrangement of image and text processing workflows. Each time content is changed, manual adjustments are still required, making the process cumbersome and inefficient, severely hindering poster generation efficiency. Summary of the Invention

[0004] This disclosure provides a poster generation method, an electronic device, a storage medium, and a computer program product.

[0005] According to one aspect of this disclosure, a poster generation method is provided, comprising: configuring a logic chain for poster elements in a poster canvas, the logic chain being used to convert content information of the poster elements into image data of the poster elements; in response to obtaining the content information of the poster elements, triggering the logic chain corresponding to the poster elements, the logic chain processing the content information into image data of the poster elements; rendering the image data into an image instance displayed in the poster canvas; and generating a poster based on the poster instance.

[0006] According to one technical solution, by configuring logical chains for poster elements, the automatic conversion from content information to image instances is realized, improving the flexibility and efficiency of poster generation.

[0007] In some implementations, configuring a logic chain for poster elements in a poster canvas includes: acquiring multiple processing nodes for the poster elements, wherein each processing node is a functional unit that performs a unit processing step in the process of converting the content information into the screen data; and determining the dependencies between the processing nodes based on a first requirement tag and a second requirement tag of each processing node to form the logic chain, wherein the first requirement tag is an identifier of the input data that the processing node can process, and the second requirement tag is an identifier of the output data via the processing node, and the logic chain includes the multiple processing nodes and the dependencies between them.

[0008] According to one technical solution, by automatically constructing the dependency relationship between processing nodes based on input and output labels, the intelligent arrangement and flexible configuration of the logical chain are realized, which improves the automation and scalability of poster element visual generation.

[0009] In some implementations, configuring a logic chain for a poster element in a poster canvas includes: determining whether there is an existing logic chain applicable to the poster element; when there is an existing logic chain applicable to the poster element, using the existing logic chain as the logic chain for the poster element, wherein the logic chain is used for multiple poster elements.

[0010] According to one technical solution, by identifying and reusing existing logic chains applicable to the current poster elements, the sharing and unification of processing flows among multiple poster elements can be achieved, thereby improving configuration efficiency and visual consistency.

[0011] In some implementations, configuring logical chains for poster elements in a poster canvas includes: configuring logical chains applicable to information subjects for the poster elements, wherein the information subject is the descriptive subject of the content information associated with the poster element, and the poster element corresponds to multiple logical chains.

[0012] According to one technical solution, by configuring multiple logical chains for different information subjects for poster elements, the same element can dynamically select the optimal processing path based on the content subject (such as agent's job level, transaction amount, etc.), thereby achieving an efficient unity of personalized visual expression and intelligent generation.

[0013] In some implementations, in response to obtaining the content information of the poster element, the logic chain corresponding to the poster element is triggered, including: identifying the subject characteristics of the information subject in the content information, selecting a target logic chain suitable for the subject characteristics from the multiple logic chains bound to the poster element; and calling the target logic chain to process the content information into the screen data.

[0014] According to one technical solution, by dynamically selecting the optimal logical chain based on the characteristics of the information subject, intelligent adaptation and personalized rendering of content to image are achieved, thereby improving the accuracy and visual expressiveness of poster generation.

[0015] In some implementations, invoking the target logic chain to process the content information into the screen data includes: in the target logic chain, invoking at least one processing node with the content information as a first demand tag to process the content information, obtaining output data of each processing node regarding the content information and an identifier of the output data; and determining at least one other processing node with the identifier of the output data as a first demand tag, and controlling the at least one other processing node to process the corresponding output data to obtain new output data and an identifier of the new output data, until the new output data is the screen data.

[0016] According to one technical solution, an automated chaining and data flow of processing nodes is achieved through a hierarchical dependency execution mechanism based on input and output tags, ensuring that content information is efficiently and orderly transformed into final screen data, thereby improving the intelligence and reliability of the logic chain execution.

[0017] In some implementations, the method further includes: determining the layout information of the poster element, the layout information including the position information, layer, and style information of the poster element in the poster canvas.

[0018] According to one technical solution, by pre-determining the layout information of poster elements, including their position, hierarchy, and style attributes on the canvas, precise control of element layout and standardization of visual presentation are achieved, providing a basic guarantee for the orderly rendering of subsequent image instances and the aesthetics and consistency of the overall poster.

[0019] According to one aspect of this disclosure, an electronic device is provided, comprising: a memory storing execution instructions; and a processor executing the execution instructions stored in the memory, causing the processor to perform a poster generation method according to any embodiment of this disclosure.

[0020] According to one aspect of this disclosure, a readable storage medium is provided that stores executable instructions, which, when executed by a processor, implement the poster generation method according to any embodiment of this disclosure.

[0021] According to one aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the poster generation method described in any embodiment of this disclosure. Attached Figure Description

[0022] The accompanying drawings illustrate exemplary embodiments of the present disclosure and, together with the description thereof, serve to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification.

[0023] Figure 1 This is a schematic diagram illustrating an application scenario of the poster generation method according to the embodiments of this disclosure.

[0024] Figure 2 This is a flowchart of a poster generation method according to an embodiment of the present disclosure.

[0025] Figure 3 This is a flowchart of the logic chain configuration process according to the embodiments of this disclosure.

[0026] Figure 4 This is a flowchart of the poster generation process according to an embodiment of the present disclosure.

[0027] Figure 5 This is a schematic diagram of a logic chain according to an embodiment of the present disclosure.

[0028] Figure 6 This is a schematic block diagram of the poster generation apparatus according to an embodiment of the present disclosure.

[0029] Figure 7 This is a block diagram illustrating the structure of an electronic device according to one embodiment of the present disclosure. Detailed Implementation

[0030] The present disclosure will now be described in further detail with reference to the accompanying drawings and examples. It should be understood that the specific examples described herein are for illustrative purposes only and are not intended to limit the scope of the disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the accompanying drawings.

[0031] It should be noted that, where there is no conflict, the embodiments and features described in this disclosure can be combined with each other. The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0032] In real estate brokerage, e-commerce operations, and advertising, large-scale personalized poster generation has become a crucial part of daily operations. Take the "closing success announcement" in the real estate brokerage industry as an example: after each transaction, a customized poster needs to be quickly released for team motivation and brand exposure. While these posters have a uniform layout, they involve numerous dynamic variables—such as the agent's name, avatar, transaction amount, property information, location, and congratulatory messages—and subtle style differences may be required for different time periods, different stores, and even different individuals. Therefore, there is an urgent need for an automated generation mechanism that can maintain brand visual consistency while efficiently supporting batch content replacement and personalized adjustments.

[0033] Traditional design processes relying on repetitive manual operations can no longer meet the demands of high-frequency, ever-changing, and real-time dissemination. Upgrading from "static templates" to "intelligent generation" has become crucial for improving operational efficiency and organizational collaboration. However, related technical solutions generally suffer from a disconnect between design and generation. Most tools only support simple text and image placeholder replacement, filling pre-defined text fields or image areas with content, lacking dynamic control over image processing logic. The processing flow lacks programmability; users cannot customize chained instructions such as "cut out the image → adjust colors → add borders → overlay text shadows," requiring manual intervention for each content change, severely limiting automation and scalability. This static and rigid production model is costly and slow to respond to diverse business needs, failing to support the modern operational pursuit of both agility and personalization.

[0034] Therefore, this disclosure proposes a poster generation method.

[0035] Figure 1 This is a schematic diagram illustrating an application scenario of the poster generation method according to embodiments of this disclosure. For example... Figure 1 As shown, this application scenario may include a server 100 and a terminal device 200. The server 100 and the terminal device 200 can interact with each other via a network connection. The server 100 can be a cloud server or a physical server, and the terminal device 200 can be a smart device such as a computer, mobile phone, or tablet. The server 100 can receive requests from the terminal device 200 and run the poster generation method disclosed herein.

[0036] Figure 2 This is a flowchart of a poster generation method according to an embodiment of this disclosure. Figure 2 As shown, this disclosure proposes a poster generation method M200, which realizes the automatic conversion from content information to image instance by configuring a logic chain for poster elements, thereby improving the flexibility and efficiency of poster generation.

[0037] Step S210: Configure the logic chain for the poster elements in the poster canvas.

[0038] The Poster Canvas is a visual design interface used to hold and arrange all poster elements and their logical chains. It provides a visual operating environment for posters, offering designers configuration windows for text, images, and other poster elements during the configuration phase. Designers can configure layout information and bind logical chains for each element. During the generation phase, the Poster Canvas triggers the logical chains of each poster element to process the input content and generate visual instances that conform to design specifications, thus achieving personalized, automated, and stylistically consistent posters.

[0039] Poster elements are the basic building blocks of a poster canvas, serving as containers for carrying and presenting visual instances. Poster elements define the visual form (such as images and text) and layout position of specific areas within the poster canvas, ensuring accurate display of the visual instances generated from content information processed through logical chains during the rendering phase, guaranteeing a precise match between content and design structure.

[0040] The poster design canvas includes a dedicated window for configuring the layout and logical chain of poster elements. The layout configuration window allows users to set detailed information about the position, hierarchy, and style of poster elements. Position information not only clarifies the horizontal and vertical coordinates of the elements on the canvas but also implicitly defines their size. Hierarchy settings determine the order in which elements are displayed, ensuring a clear and orderly visual hierarchy. Style information covers aspects from color to shape, giving each element a unique appearance. The logical chain configuration window provides the ability to customize the behavior logic of poster elements, allowing elements to dynamically change their state or content based on specific conditions or user interaction. This customization capability greatly expands the expressiveness and interactivity of posters, enabling each poster to convey rich information.

[0041] The logical chain consists of multiple ordered, interconnected processing nodes. Its function is to intelligently convert raw, non-standardized content information into visual data that can be recognized by the rendering module. Content information typically refers to raw data input by the designer or business system, such as text in natural language (e.g., congratulations to Mr. Zhang for closing an 8 million yuan deal on a property in a certain community), unprocessed raw image files (e.g., a profile picture taken by a real estate agent), or structured fields (e.g., transaction amount, property address, etc.). This type of information itself lacks visual expressiveness and cannot be directly parsed and displayed by the poster canvas rendering module. It also often does not meet the design requirements of the final visual in terms of style, format, and layout.

[0042] The original content is processed layer by layer through various processing nodes in the logical chain. These processing nodes can be font matching nodes, intelligent image cutout nodes, lighting enhancement nodes, size adaptation nodes, and special effects overlay nodes, etc. For example, the logical chain for a "broker avatar" element can execute the following steps in sequence: stylization node → background removal node → border style addition node, etc., ultimately outputting a standardized avatar image data that conforms to the broker role. This image data is in a structured image format, which can not only be directly called by the rendering module, but also ensures consistent, high-quality visual effects across different terminals and scenarios.

[0043] Therefore, the logic chain essentially constructs an automated production line from "information content" to "image data", realizing the deep integration of content understanding, intelligent processing and design rules, making poster generation truly flexible, intelligent and programmable.

[0044] In step S220, in response to obtaining the content information of the poster element, the logic chain corresponding to the poster element is triggered, and the logic chain processes the content information into the image data of the poster element.

[0045] Specifically, the process involves identifying the subject characteristics of the information in the content information, selecting a target logic chain suitable for the subject characteristics from multiple logic chains bound to the poster elements, and then calling the target logic chain to process the content information into image data. More specifically, within the target logic chain, at least one processing node with the content information as the first requirement tag is called to process the content information, obtaining the output data of each processing node regarding the content information and the identifier of the output data; and determining at least one other processing node with the identifier of the output data as the first requirement tag, and controlling the other at least one processing node to process the corresponding output data to obtain the identifier of the new output data, until the new output data is the image data.

[0046] Each poster element predefines its service field names during the design phase, such as "Agent Name," "Transaction Amount," "Agent Avatar," and "Order Opening Time." These fields clearly define the types of content it can process and display. During the actual generation process, the input content information is typically organized in "field-value" pairs, for example: {"name": "Zhang Wei", "amount": "8 million", "avatar": "zhangwei.jpg"}. When a field name in a piece of content matches a field name supported by a poster element, it is determined that the content should be filled into the corresponding poster element, thus establishing a mapping relationship between content and poster elements.

[0047] Furthermore, considering that the same type of poster element may require different visual styles or processing methods under different subject characteristics—for example, the avatar display for ordinary transactions and million-dollar deals need different special effects, and the avatar display style or stickers used for management agents and ordinary agents may differ—multiple logical chains are allowed for a single poster element. Each logical chain represents a processing path for a specific information subject. It should be noted that the information subject is the descriptive subject of the content information, and the subject characteristics can be the transaction amount, job level, etc., without restriction. Therefore, after the content information is filled into the element, the system will determine which logical chain should be used as the target logical chain based on the subject characteristics of the content information (such as whether the transaction amount exceeds the threshold, whether the agent is a management agent, whether the region is a key real estate project, etc.).

[0048] This target logic chain consists of a series of ordered processing nodes, with clear dependencies between each node, forming an executable processing pipeline. For example, for the profile picture element of a real estate agent who has achieved a "multi-million dollar luxury home sale," the following logic chain might be selected: image high-definition enhancement node, intelligent character cutout node, adding gold border and halo effects node, etc. Finally, the output is structured image data that can be recognized by the rendering module, ensuring that the output image data not only accurately expresses the original content, but also fully reflects the preset design intent.

[0049] This disclosure achieves a leap from static template filling to semantic awareness and context-adaptive intelligent visual generation through a mechanism of field matching and content-driven logical chain selection. This enables posters to maintain a unified overall style while automatically generating the most expressive and personalized presentation based on different content.

[0050] Step S230: Render the image data into an image instance displayed on the poster canvas.

[0051] A visual instance is a visual unit within the poster canvas. It's the final form of the image data generated through logical chaining of content information and rendered on the poster canvas. Each visual instance corresponds to a specific poster element's representation driven by specific content and meets the layout requirements of that element. For example, it might be text with specified font, color, shadow, and typography style; or a portrait that has been cut out, decorated with borders, and enhanced with lighting and shadow. Visual instances not only contain pixel or vector graphics data but also embed layout information such as position, hierarchy, and style, ensuring precise integration into the overall poster composition.

[0052] In step S240, a poster is generated based on the image instance.

[0053] Based on the poster elements present in the poster canvas, a corresponding number of image instances will be generated. These image instances are rendered in the designated area of ​​the poster canvas according to the layout information of the relevant poster elements. Multiple image instances are combined and superimposed to form a visual poster with a unified style and complete structure.

[0054] This technical solution achieves intelligent and automated transformation from content to visuals by constructing a fusion poster generation system of "canvas + chain-like logical arrangement". At the design level, it supports configuring independent and reusable logical chains for each poster element. Dependencies between processing nodes are automatically established through first and second requirement tags, and the target logical chain is dynamically selected based on the characteristics of the information subject, ensuring the accuracy and personalization of content processing. At the generation level, the system efficiently renders the image data based on layout information, forming image instances with clear structure and unified style, and supports parallel processing to improve execution efficiency. The overall solution breaks through the limitations of traditional static templates, realizing intelligent processing, flexible arrangement, and batch generation of poster elements, significantly improving operational efficiency, visual expressiveness, and system scalability. It is suitable for automated production of personalized posters in various scenarios such as order announcements and operational activities.

[0055] Figure 3 This is a flowchart of the logic chain configuration process according to an embodiment of this disclosure. The following is in conjunction with... Figure 3 The configuration process of the logical chain is explained.

[0056] In step 301, a logic chain configuration window is set for the poster canvas.

[0057] The logic chain configuration window is the core interface for human-computer interaction, allowing designers to define individual logic chains for each poster element (such as text boxes, image areas, decorative graphics, etc.) in the canvas within a visual editing environment. Through this window, users can intuitively drag, arrange, and connect various processing nodes to build complete logic chains for specific poster elements. Each logic chain represents the transformation path from raw content information (such as agent name, transaction amount, and profile picture) to the final renderable screen data.

[0058] Furthermore, the logic chain configuration window supports a multi-chain management mechanism, meaning that the same poster element can be bound to multiple logic chains, and the optimal processing path is dynamically selected based on the main characteristics of the information subject (such as transaction amount range, job level, etc.). During the configuration process, the execution effect of the logic chain can be previewed in real time to ensure that the design intent is accurately implemented. This step upgrades traditional static design to "programmable visual generation," achieving a deep integration of design rules and business logic, and laying a flexible and controllable technical foundation for subsequent automated, batch, and personalized poster generation.

[0059] In step 302, it is determined whether there is an existing logical chain applicable to the poster element.

[0060] The logic chain is reusable, allowing designers to efficiently share and flexibly call existing logic chains among different poster elements. Reuse methods mainly include two scenarios: direct use and nested application.

[0061] In the "direct use" scenario, assuming that poster element A has been configured with a logical chain a, if poster element B needs to perform the exact same processing steps, the entire logical chain a can be directly assigned to element B without having to repeatedly build the node sequence, thus achieving rapid deployment and style consistency.

[0062] In nested scenarios, logic chain 'a' can be integrated and used as part of a larger logic chain. For example, when a designer creates a new logic chain 'b' for poster element B, they can embed the existing logic chain 'a' as a composite node within it, serving as a step in its processing flow. This structured reuse approach not only improves development efficiency but also enhances the modularity and maintainability of the logic chains.

[0063] Once generated, logical chains are typically persistently stored in a logical chain database. This mechanism allows designers to directly access existing logical chains from the database and apply them to new poster elements during subsequent poster design processes, eliminating the need for repeated dragging, connecting, and parameter configuration of nodes. Whether fully reusing mature chains or fine-tuning and optimizing existing logical chains, this significantly reduces operational complexity and improves configuration efficiency. Furthermore, centralized storage of logical chains facilitates unified design standards and experience accumulation across teams, further enhancing the intelligence and standardization of poster element configuration and comprehensively accelerating the automated poster generation process.

[0064] When there is no existing logical chain in the logical chain database that is suitable for the current poster element, proceed to step 303 to obtain the processing node of each poster element, as well as the first requirement label and the second requirement label of the processing node.

[0065] The acquisition of processing nodes can be determined by the designer through dragging and dropping in the logic chain configuration window. Of course, other more convenient ways to hit processing nodes also fall within the scope of protection of this disclosure, and will not be listed here.

[0066] The first requirement label identifies the input data that a processing node can receive and process, while the second requirement label identifies the output data after processing. In other words, each processing node explicitly declares its "input capabilities" and "output capabilities" during design: what kind of data it can process (recorded by the first requirement label) and what form of result it can generate after processing (recorded by the second requirement label). These labels are essentially a structured description of the node's functional semantics, usually defined based on the field names or semantic categories of the data. For example, if the input of processing node 1 is "original human image" and the output is "cut-out image," its first requirement label is "original human image," and its second requirement label is "cut-out image." Processing node 2, on the other hand, needs "cut-out image" as input to generate an "enlarged image," so its first requirement label is "cut-out image." Since the input label of node 2 matches the output label of node 1, the dependency between the two can be automatically inferred, ensuring that node 1 executes before node 2 during the execution of the logical chain, forming the correct processing sequence.

[0067] This tag-based dependency recognition mechanism not only enables automatic connection and workflow orchestration between processing nodes, but also supports intelligent system recommendations and error checking. For example, when dragging and dropping nodes to build a logical chain, it can automatically recommend subsequent nodes that can be connected based on the currently available output tags; at the same time, if there is a mismatch in input tags (such as attempting to connect a node whose output is "text content" to a node that requires "image data"), it can immediately prompt incompatibility errors to avoid workflow configuration mistakes. In addition, this mechanism also provides basic support for the modular reuse and cross-scenario migration of logical chains—as long as the tags of the preceding and following stages match, processing modules in different business scenarios can be flexibly combined.

[0068] In step 304, the relationships between the processing nodes in the poster elements are determined based on the requirement tags, forming a logical chain.

[0069] Based on the first and second requirement tags carried by each processing node, the data dependencies between them are analyzed and determined, thereby constructing a complete logical chain with a reasonable structure and orderly execution. Specifically, the set of processing nodes currently configured for the poster element is traversed, and the possibility of data flow is determined by comparing whether the output tag of the previous node matches the input tag of the next node. For example, if the output tag of the "image cutout" node is "cutout image", and the input tag of the subsequent "image zoom-in" node is also "cutout image", then the connection between the two can be automatically established, forming a "cutout → zoom-in" processing flow.

[0070] In a logical chain, multiple parallel processing branches can exist. These branches may share the same input source—for example, all using the "original human image" as input data—and then perform different image processing operations, such as one branch performing intelligent image matting and background blurring, while another branch performs facial beautification and color enhancement. Finally, the results of these independently processed images are superimposed or blended at a subsequent fusion node (such as the "image compositing" node) to generate the final target image data. This parallel structure not only improves processing efficiency but also supports multi-dimensional and multi-style visual interpretations of the same content.

[0071] When executing this logical chain, if there is no direct label dependency between multiple processing nodes (i.e., the input label of one node does not depend on the output label of another node), but they all depend on the same original content input (e.g., they all depend on the "original image of a person"), then these nodes can be determined to have data-level independence and meet the conditions for parallel execution. In this case, multiple processing threads or task queues can be scheduled to run these nodes without prior or subsequent dependencies simultaneously, making full use of computing resources and significantly reducing the overall processing time.

[0072] Furthermore, by analyzing the primary requirement tags and the state of the dependent data at each node, an execution graph can be dynamically constructed, automatically identifying parallelizable branch paths and distributing tasks and aggregating results at runtime. This intelligent scheduling mechanism, based on content dependency rather than solely on tag matching, not only enhances the execution flexibility of the logical chain but also enables complex image processing workflows to achieve higher performance and response speed while maintaining semantic correctness, providing strong support for large-scale, real-time automatic poster generation.

[0073] When an existing logical chain exists, or after a logical chain is constructed based on steps 303 and 304, step 305 is executed to establish a connection between the information subject and the logical chain, forming a logical chain topology diagram about the poster information.

[0074] A logical chain topology diagram is a structured data model used to record and manage multiple logical chains associated with a poster element and their mapping relationships with different information subjects. Specifically, it not only stores the processing node sequence, first requirement label, second requirement label, and execution flow of each logical chain, but also clarifies the subject characteristics of the information subject to which each logical chain applies, thereby achieving an intelligent switching mechanism of "content-driven visuals." For example, for the avatar element in a "broker's successful sale announcement," the system can configure multiple logical chains: a standard version for general transactions, an advanced version for large transactions, and a newcomer-exclusive version for first-time sales, etc. The logical chain topology diagram records the correspondence rules between these logical chains and the subject characteristics of the main information subjects.

[0075] These corresponding rules are highly configurable, allowing designers to flexibly define judgment conditions according to business needs, including field value comparisons (such as amount, region), category tag matching (such as new / used homes), time periods (such as holiday promotions), and even external data linkage (such as customer satisfaction ratings). Subject features can also be automatically extracted or manually annotated to form structured metadata. Leveraging the logical chain topology graph, when generating posters, the system can automatically retrieve and select the most matching target logical chain based on the subject features in the current content information, achieving personalized visual expression without manual intervention. This mechanism not only improves the intelligence level of poster generation but also supports cross-scenario, multi-strategy visual operations, serving as the core supporting architecture for achieving "personalized" dynamic posters.

[0076] Figure 4 This is a flowchart of the poster generation process according to an embodiment of this disclosure. (See reference) Figure 4 The process of generating the poster is explained.

[0077] After acquiring the content information, we match the field names with the field names that each poster element can process to determine the specific poster element associated with this content information. A piece of content information may be associated with multiple poster elements. For example, if the content information contains both a person's image and congratulatory text, it can be associated with at least the poster element displaying the person's image and the poster element displaying the congratulatory text. Each poster element will process the values ​​of its specific field names accordingly, ensuring that all types of information are accurately presented in the final poster design.

[0078] In step 401, the information subject of the content information is identified.

[0079] The information subject refers to the object described in the content information, such as a broker, client, or property listing. While identifying the information subject, it is bound to a series of preset subject characteristics, such as transaction amount, job level, region, number of deals closed, and years of service. Based on this, according to the judgment conditions preset during the poster element configuration phase, key features for logical chain matching are selected from these subject characteristics as the basis for selecting the target logical chain. For example, when a poster element is set to "select display style based on transaction amount," the "transaction amount" feature corresponding to the information subject will be extracted, and the appropriate processing flow will be matched in the logical chain topology graph accordingly. This mechanism supports flexible condition configuration, ensuring that the poster generation process can achieve personalized and intelligent visual expression based on specific business scenarios.

[0080] In step 402, the target logical chain corresponding to the information subject is determined.

[0081] In the configured logical chain topology diagram, based on the judgment conditions of the current poster element, the main feature used to judge the logical chain is determined, and the logical chain associated with this feature is taken as the target logical chain.

[0082] Figure 5 This is a schematic diagram of a logic chain according to an embodiment of this disclosure. For example... Figure 5 As shown, this scenario demonstrates a use of job title as the primary characteristic for judgment. The same poster element (such as "Upload Image") triggers different logical chains depending on the job title of the information subject. Specifically, when an image of a regular agent is uploaded, it undergoes a unified style processing at the "Stylization Node," then proceeds to the "Intelligent Background Removal Node," and finally, the "Sticker Processing Node" completes the beautification output. However, when an image of a managerial agent is uploaded, the stylization processing is skipped, and it directly proceeds to the "Intelligent Background Removal Node" for further processing. This design, by recognizing the key characteristic of the information subject's job title, achieves differentiated processing paths within the process. This ensures that images of different roles maintain a consistent core processing logic while possessing personalized visual presentation effects, demonstrating the intelligent routing and efficient execution capabilities of the logical chain based on subject characteristics.

[0083] In step 403, the logic chain is invoked to process the content information and generate screen data.

[0084] A logical chain is a collection of processing nodes, each performing specific processing on the input information in sequence. It's important to note that these processing nodes actually operate on the portion of the content information that matches their function and can be effectively processed.

[0085] A logical chain may contain multiple branch paths to identify nodes that can be processed in parallel based on the currently acquired data and the initial demand labels of each processing node, and to simultaneously launch these nodes to process the data they depend on. This not only improves processing efficiency but also optimizes resource utilization, ensuring that different types of processing tasks can be completed in the shortest possible time.

[0086] In step 404, the image data is rendered in the poster canvas according to the layout information of the poster elements to generate an image instance.

[0087] Layout information includes the element's position coordinates on the canvas (i.e., horizontal and vertical range), hierarchy, rotation angle, transparency, and other visual attributes. Based on these precise layout rules, the image data is accurately drawn onto designated areas, forming visually representable units, or "image instances." For example, congratulatory text data processed with font, color, and shadow will be rendered as a graphic block with a specific style and position; a broker's portrait enhanced with cutouts and special effects will also be embedded into the corresponding position on the canvas according to the set size and coordinates. All image instances are stacked hierarchically to form a complete and stylistically unified preliminary poster view, laying the foundation for subsequent poster composition and output. This step achieves the crucial transformation from "data" to "visual content" and is the core link connecting intelligent processing and final presentation. The coordinates of poster elements on the poster canvas implicitly determine the element's size.

[0088] In step 405, the various screen instances in the poster canvas are integrated to obtain the poster. The poster records all the content information and can be displayed visually. If there is a need to modify the screen instances in the poster, adjustments can be made through the logical chain of the corresponding poster elements.

[0089] Figure 6 This is a schematic block diagram of the poster generation apparatus according to an embodiment of the present disclosure. Figure 6 As shown, this disclosure discloses a poster generation device 600, including: a logic chain configuration module 610, used to configure logic chains for poster elements in a poster canvas, the logic chains being used to convert the content information of the poster elements into the image data of the poster elements; a processing module 620, used to trigger the logic chain corresponding to the poster element in response to obtaining the content information of the poster element, the logic chains processing the content information into the image data of the poster element; a rendering module 630, used to render the image data into an image instance displayed in the poster canvas; and a poster generation module 640, used to generate a poster based on the image instance.

[0090] The poster generating apparatus 600 disclosed herein can be in the form of computer software, and each module of the poster generating apparatus 600 can be in the form of computer software modules.

[0091] The various modules of the poster generation device 600 disclosed herein are set up to implement the various steps of the poster generation method. The execution principle and steps can be referred to the above text and will not be repeated here.

[0092] Figure 7 This is a schematic block diagram of an electronic device according to one embodiment of the present disclosure. Figure 7As shown, this disclosure also provides an electronic device 1000, including: a processor 1200 and a memory 1300, the memory 1300 storing execution instructions; the processor 1200 executes the execution instructions stored in the memory 1300, causing the processor 1200 to execute a poster generation method.

[0093] The hardware architecture of the electronic device 1000 can be implemented using a bus architecture. The bus architecture can include any number of interconnect buses and bridges, depending on the specific application of the hardware and overall design constraints. Bus 1100 connects various circuits, including one or more processors 1200, memory 1300, and / or hardware modules. Bus 1100 can also connect various other circuits 1400, such as peripheral devices, voltage regulators, power management circuits, external antennas, etc.

[0094] Bus 1100 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Component (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, only one connection line is used in this diagram, but this does not imply that there is only one bus or only one type of bus.

[0095] This disclosure also provides a readable storage medium storing a computer program that, when executed by a processor, is used to implement the methods described above. A "readable storage medium" can be any means capable of containing, storing, communicating, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples of a readable storage medium include: an electrical connection with one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable read-only memory (CDROM), etc.

[0096] This disclosure also provides a computer program product, the methods of which can be implemented wholly or partially through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented wholly or partially as a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed, all or part of the processes or functions of this disclosure are performed.

[0097] Computer programs or instructions can be stored in a readable storage medium or transferred from one readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The readable storage medium can be any available medium capable of access, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a digital video optical disc; or a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or it can include both volatile and non-volatile types of storage media.

[0098] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, electronic devices, readable storage media, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., refer to specific features, structures, or characteristics described in connection with that embodiment / mode or example, which are included in at least one embodiment / mode or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0103] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0104] Those skilled in the art should understand that the above embodiments are merely for illustrating the present disclosure and are not intended to limit the scope of the disclosure. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications still fall within the scope of the present disclosure.

[0105] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0106] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0107] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0108] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0109] At the same time, it is understood that the data involved in this disclosed technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

Claims

1. A poster generation method, characterized in that, include: Configure a logic chain for the poster elements in the poster canvas, the logic chain being used to convert the content information of the poster elements into the image data of the poster elements; In response to obtaining the content information of the poster element, the logic chain corresponding to the poster element is triggered, and the logic chain processes the content information into the image data of the poster element; The image data is rendered into an image instance displayed on the poster canvas; as well as A poster is generated based on the image instance.

2. The poster generation method according to claim 1, characterized in that, Configure logical chains for poster elements in the poster canvas, including: Acquire multiple processing nodes for the poster element, wherein each processing node is a functional unit that performs a unit processing step in the process of converting the content information into the image data; and Based on the first requirement label and the second requirement label of each processing node, the dependency relationship between each processing node is determined to form the logical chain. The first requirement label is an identifier of the input data that the processing node can process, and the second requirement label is an identifier of the output data through the processing node. The logical chain includes the plurality of processing nodes and the dependency relationship between each processing node.

3. The poster generation method according to claim 1, characterized in that, Configure logical chains for poster elements in the poster canvas, including: Determine if an existing logical chain exists that applies to the poster element; When an existing logic chain exists that is applicable to the poster element, the existing logic chain is used as the logic chain for the poster element, wherein the logic chain is used for multiple poster elements.

4. The poster generation method according to claim 1, characterized in that, Configure logical chains for poster elements in the poster canvas, including: Configure a logical chain for the poster element that is suitable for the information subject, where the information subject is the descriptive subject of the content information associated with the poster element, and the poster element corresponds to multiple logical chains.

5. The poster generation method according to claim 1, characterized in that, In response to obtaining the content information of the poster element, the logic chain corresponding to the poster element is triggered, including: Identify the subject characteristics of the information subject in the content information, and select a target logic chain suitable for the subject characteristics from multiple logic chains bound to the poster elements; and The target logic chain is invoked to process the content information into the screen data.

6. The poster generation method according to claim 5, characterized in that, The target logic chain is invoked to process the content information into the image data, including: In the target logic chain, at least one processing node with the content information as the first requirement tag is invoked to process the content information, thereby obtaining the output data of each processing node regarding the content information and the identifier of the output data; and Identify at least one other processing node that uses the identifier of the output data as the first demand label, and control the at least one other processing node to process the corresponding output data to obtain new output data and the identifier of the new output data, until the new output data is the screen data.

7. The poster generation method according to claim 1, characterized in that, Also includes: The layout information of the poster element is determined, including the position information, layer, and style information of the poster element in the poster canvas.

8. An electronic device, characterized in that, include: The memory stores execution instructions; as well as A processor that executes execution instructions stored in the memory, causing the processor to perform the poster generation method according to any one of claims 1 to 7.

9. A readable storage medium, characterized in that, The readable storage medium stores execution instructions, which, when executed by a processor, are used to implement the poster generation method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the poster generation method according to any one of claims 1 to 7.

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