Added comprehensive comparison of AI providers for inpainting: - OpenAI DALL-E 2 (not recommended, poor quality) - Stability AI (good quality, $0.04/image) - Replicate (best value, $0.01-0.025/image, multiple models) - Local GPU (best quality, no per-use cost) Includes cost analysis, quality rankings, and recommendations for different use cases and volume levels. Recommends Replicate as best overall value with no minimum purchase and access to multiple high-quality models.
AI Photo Edit
AI Photo Edit is a self-hosted, web-based image editing tool that allows you to regenerate only a selected area of a photo using AI.
Core Concept
Have AI regenerate only a selected area of a photo.
- Upload an image
- Select a specific region (rectangle, ellipse, or freehand lasso)
- Enter a prompt describing what to fix
- Have AI regenerate only the selected region
- Composite the regenerated region back into the original image
- Preserve every pixel outside the selection
- Maintain full edit history and reversibility
The system does not regenerate the entire image. The system does not alter any pixel outside the selected mask.
Features
Selection Tools
- Rectangle: Click and drag to select rectangular regions
- Ellipse: Click and drag to select elliptical regions
- Lasso: Draw freehand selections around irregular shapes
AI Modes
-
Mode A (Default): Send only the selected patch
- Faster processing
- Lower cost
- Best for isolated fixes
-
Mode B: Send patch + full image reference
- Better style consistency
- More context-aware results
- Higher cost
Edge Blending
- Adjustable feather slider (0-50 pixels)
- Smooth blending at selection edges
- Prevents harsh transitions
Edit History
- Full history of all edits
- Revert to any previous edit
- Reset to original image
- All edits are reversible
Architecture
AI Photo Edit
├── Frontend (React + Fabric.js)
│ ├── Image canvas with selection tools
│ ├── Controls (mode, feather, prompt)
│ └── Edit history viewer
│
├── Backend (FastAPI)
│ ├── Image processing
│ ├── AI provider integration
│ ├── Database (SQLite)
│ └── File storage
│
└── Docker Compose
├── Backend service
└── Frontend service (nginx)
Installation
Prerequisites
- Docker and Docker Compose
- AI API key (OpenAI or Stability AI) for production use
Quick Start
- Clone the repository
git clone <repository-url>
cd EditmaskwithAI
- Configure environment variables
cp .env.example .env
Edit .env and set your AI provider:
# For OpenAI (DALL-E)
AI_PROVIDER=openai
OPENAI_API_KEY=your-openai-api-key-here
# OR for Stability AI
AI_PROVIDER=stability
STABILITY_API_KEY=your-stability-api-key-here
# OR for testing (no AI, returns original)
AI_PROVIDER=mock
- Start the application
docker-compose up -d
- Access the application
- Frontend: http://localhost
- Backend API: http://localhost:8000
- API Documentation: http://localhost:8000/docs
Development Setup
For development with hot-reload:
docker-compose -f docker-compose.dev.yml up
- Frontend: http://localhost:5173 (Vite dev server)
- Backend: http://localhost:8000 (auto-reload enabled)
Usage
1. Create a Project
- Enter a project name
- Upload your image (PNG, JPG, etc.)
- Click "Create Project"
2. Select an Area
- Choose a selection tool (Rectangle, Ellipse, or Lasso)
- Draw your selection on the image
- Adjust the selection if needed
3. Configure Edit
- AI Mode: Choose Mode A (faster) or Mode B (better context)
- Feather: Adjust edge blending (0-50 pixels)
- Prompt: Describe what you want to change
Examples:
- "Remove the person"
- "Change sky to sunset"
- "Fix the red eye"
- "Add flowers"
4. Process Edit
- Click "Fix Selected Area"
- Wait for AI processing (status shown in history)
- View the result on the canvas
5. Manage History
- View all edits in the history panel
- Revert to any previous edit
- Reset to original image anytime
API Documentation
Projects
Create Project
POST /projects/
Body: { "name": "My Project" }
Upload Image
POST /projects/{project_id}/upload
Body: multipart/form-data with image file
List Projects
GET /projects/
Get Project
GET /projects/{project_id}
Edits
Create Edit
POST /edits/projects/{project_id}/fix
Body: {
"prompt": "Remove the object",
"mode": "A",
"selection_type": "rectangle",
"bbox": { "x": 100, "y": 100, "width": 200, "height": 200 },
"feather_px": 5,
"selection_data": null
}
Get Edit Status
GET /edits/{edit_id}
Revert to Edit
POST /edits/projects/{project_id}/revert/{edit_id}
Reset to Original
POST /edits/projects/{project_id}/reset
Images
Get Original Image
GET /projects/{project_id}/original
Get Current Image
GET /projects/{project_id}/current
Get Edit Result
GET /projects/{project_id}/history/{edit_id}/result
File Structure
EditmaskwithAI/
├── backend/
│ ├── app/
│ │ ├── models/ # Database models
│ │ ├── routers/ # API endpoints
│ │ ├── services/ # Business logic
│ │ ├── utils/ # Image processing utilities
│ │ ├── config.py # Configuration
│ │ ├── database.py # Database setup
│ │ └── main.py # FastAPI app
│ ├── Dockerfile
│ └── requirements.txt
│
├── frontend/
│ ├── src/
│ │ ├── components/ # React components
│ │ │ ├── ImageCanvas.jsx
│ │ │ ├── Controls.jsx
│ │ │ └── History.jsx
│ │ ├── utils/ # API client
│ │ ├── App.jsx
│ │ └── main.jsx
│ ├── Dockerfile
│ ├── nginx.conf
│ └── package.json
│
├── data/ # Persistent data (auto-created)
│ ├── ai_photo_edit.db # SQLite database
│ └── projects/ # Project files
│
├── docker-compose.yml
├── docker-compose.dev.yml
└── README.md
Data Storage
Database (SQLite)
- users: User accounts
- projects: Project metadata
- edits: Edit history and metadata
Filesystem
data/projects/{project_id}/
├── original.png # Original uploaded image
├── current.png # Current edited image
└── history/{edit_id}/
├── patch_in.png # Original patch
├── patch_out.png # AI-generated patch
├── mask.png # Selection mask
├── result.png # Final result
└── meta.json # Edit metadata
AI Provider Configuration
OpenAI (DALL-E)
AI_PROVIDER=openai
OPENAI_API_KEY=sk-...
Stability AI
AI_PROVIDER=stability
STABILITY_API_KEY=sk-...
Mock (Testing)
AI_PROVIDER=mock
Returns the original patch unchanged - useful for testing without API costs.
Constraints
- Only the selected region is regenerated
- No modification outside the mask
- Slight drift inside mask is acceptable
- All edits are logged and reversible
- Mode A is default (cost-efficient)
- Mode B available for better style consistency
Non-Goals (MVP)
- No automatic anomaly detection
- No local GPU inference
- No full image regeneration
- No collaborative editing
Contributing
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch
- Make your changes
- Submit a pull request
License
MIT License - see LICENSE file for details
Support
For issues and questions:
- Open an issue on GitHub
- Check the API documentation at
/docs
Roadmap
Future enhancements:
- Multi-user authentication
- Batch processing
- Additional AI providers
- Advanced selection tools
- Real-time collaboration
- Export formats (PSD, TIFF)
AI Photo Edit - Regenerate only what you need to change.