Three-View Orthographic Projection to Dynamic Video Conversion (Unreleased)
This workflow can automatically convert static images of three-view orthographic projections (front view and side view) into dynamic rotating videos, enhancing visual presentation. By combining AI image generation technology with video generation interfaces, it can automatically generate multi-angle images and seamlessly synthesize them into dynamic videos, ensuring that the character's facial expressions remain unchanged. This process greatly simplifies the work of designers and animators, making it suitable for various scenarios such as game character design, animation production, and product demonstrations.
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Workflow Name
Three-View Orthographic Projection to Dynamic Video Conversion (Unreleased)
Key Features and Highlights
This workflow automates the entire process of generating and converting static three-view orthographic projection images (front and side views) into dynamic rotating videos. By integrating advanced AI image generation techniques with video generation APIs, it automatically extracts and stitches multi-view images to produce a smoothly rotating dynamic video while maintaining consistent facial expressions of the character.
Core Problem Addressed
Traditional three-view orthographic projection images are typically static and cannot directly showcase dynamic rotation effects of characters or objects, resulting in less vivid visual presentations. This workflow significantly enhances the visualization of static design drawings by automatically generating multi-angle images and synthesizing them into dynamic videos, enabling designers and animators to quickly obtain dynamic demonstration effects.
Application Scenarios
- Dynamic presentation of three-view images in game character design
- Rapid generation of rotating demonstration videos in animation production workflows
- Multi-angle dynamic demonstrations for product design prototypes
- Dynamic explanations of 3D object structures in educational and training contexts
Main Process Steps
- Manually trigger the workflow, inputting basic parameters (API key and initial image URL).
- Use the GPT-4o model to generate and obtain the front view image URL.
- Verify the generation status of the front view; if unsuccessful, regenerate.
- Use the GPT-4o model to generate and obtain the side view image URL.
- Verify the generation status of the side view; if unsuccessful, regenerate.
- Trigger the video generation API (Kling model) by submitting multi-view images to create a dynamic rotating video task.
- Poll periodically to wait for video generation completion.
- Upon completion, extract the final watermark-free video URL to complete the entire conversion process.
Involved Systems or Services
- OpenAI GPT-4o Model API: Used for generating front and side view images.
- PiAPI Kling Video Generation API: Enables dynamic conversion from images to video.
- n8n Automation Platform Nodes: Including manual trigger, HTTP requests, conditional checks, code processing, and wait nodes.
Target Users and Value
- 3D modelers, animation designers, and game developers who need to quickly convert static three-view images into dynamic videos, improving design presentation efficiency.
- Product managers and marketers aiming to create more engaging dynamic product demonstrations.
- Educators and trainers looking to vividly illustrate 3D object structures and dynamic effects.
- Automation enthusiasts and developers exploring AI-driven automatic image and video generation for creative applications.
By intelligently combining multi-view image generation with video synthesis, this workflow greatly simplifies the conversion from 2D orthographic projection images to dynamic content, achieving seamless integration between design and presentation.
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