FLUX-fill Standalone
This workflow implements AI-based automated image editing. Users can upload or select images via a web page, draw local masks, and input text prompts, which then call the intelligent fill API for image content generation. The integrated canvas editing library and comparison slider component allow users to intuitively compare the original image with the generated image. The operation is simple and the effects are evident, greatly enhancing image editing efficiency and making it suitable for various scenarios such as e-commerce, graphic design, and advertising.
Workflow Name
FLUX-fill Standalone
Key Features and Highlights
This workflow implements an automated image editing process based on the FLUX AI image inpainting service. Users can upload or select images via a web-based interactive editor, perform local mask drawing and input text prompts, and invoke FLUX’s intelligent fill API to generate and replace image content. The edited image results are returned in real-time. The workflow integrates the Konva.js canvas editing library and an image comparison slider component, enabling users to intuitively compare the original and generated images. The operation is user-friendly and the effects are visually clear.
Core Problems Addressed
It solves the automation challenge of local intelligent image repair and generation, simplifying the traditionally complex manual drawing and retouching steps in image editing. By automating calls to the AI fill interface, it significantly improves the efficiency of image content creation and modification, especially suitable for scenarios requiring rapid generation or adjustment of image details.
Application Scenarios
- Local intelligent replacement and beautification of e-commerce product images
- Creative image content generation in graphic design
- Rapid modification and iteration of advertising and visual content
- Image processing requiring quick generation of transparent backgrounds or local fill effects
- Any scenario requiring local image generation based on masks and text prompts
Main Workflow Steps
- Receive user requests via Webhook and load the editor page
- User uploads or selects images from a default collection, edits masks using Konva.js, and inputs text prompts
- Trigger FLUX Fill HTTP request, submitting the original image, mask, prompt, and parameters to the FLUX AI fill API
- Poll the API to check the fill task status and wait for completion
- Retrieve the filled image data upon generation completion
- Return the generated image in binary format to the user, supporting real-time display and comparison on the web
- User can choose to save or continue editing
Involved Systems and Services
- FLUX AI Image Fill API (https://api.bfl.ml)
- n8n automation tool with HTTP request, Webhook, conditional logic, and wait nodes
- Konva.js image editing library and img-comparison-slider component
- Frontend HTML editor page integrating various JS and CSS resources
Target Users and Value
- Designers and content creators: Quickly achieve creative image content replacement and generation, enhancing design efficiency
- E-commerce operators: Conveniently optimize product image details to boost visual appeal
- Marketing professionals and advertising teams: Rapidly iterate advertising materials and shorten production cycles
- Developers and technical teams: Integrate as an intelligent image processing module within larger systems to support automated batch processing
- Any users needing AI-assisted rapid local image editing and generation
Overall, the FLUX-fill standalone workflow seamlessly integrates frontend interaction with backend intelligent fill services to realize fully automated local intelligent image generation. It greatly lowers the threshold and time cost of image editing, making it suitable for intelligent image processing needs across various industries and scenarios.