| 
				
					
						
							 | 
			||
|---|---|---|
| .github | ||
| assets | ||
| docker | ||
| iopaint | ||
| scripts | ||
| web_app | ||
| .gitignore | ||
| LICENSE | ||
| README.md | ||
| build_docker.sh | ||
| main.py | ||
| publish.sh | ||
| requirements-dev.txt | ||
| requirements.txt | ||
| setup.py | ||
		
			
				
				README.md
			
		
		
			
			
		
	
	IOPaint
A free and open-source inpainting & outpainting tool powered by SOTA AI model.
| Erase | Replace Object | 
|---|---|
| Draw Text | Out-painting | 
|---|---|
Quick Start
Start webui
IOPaint provides a convenient webui for using the latest AI models to edit your images. You can install and start IOPaint easily by running following command:
# In order to use GPU, install cuda version of pytorch first.
# pip3 install torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/cu118
# AMD GPU users, please utilize the following command, only works on linux, as pytorch is not yet supported on Windows with ROCm.
# pip3 install torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/rocm5.6
pip3 install iopaint
iopaint start --model=lama --device=cpu --port=8080
That's it, you can start using IOPaint by visiting http://localhost:8080 in your web browser.
Batch processing
You can also use IOPaint in the command line to batch process images:
iopaint run --model=lama --device=cpu \
--input=/path/to/image_folder \
--mask=/path/to/mask_folder \
--output=output_dir
--input is the folder containing input images, --mask is the folder containing corresponding mask images.
When --mask is a path to a mask file, all images will be processed using this mask.
You can see more information about the available models and plugins supported by IOPaint below.
Features
- Completely free and open-source, fully self-hosted, support CPU & GPU & Apple Silicon
 - Windows 1-Click Installer
 - Supports various AI models:
- Erase models: These models can be used to remove unwanted object, defect, watermarks, people from image. I have also developed a macOS native app called OptiClean that provides this feature.
 - Stable Diffusion models: You can use any Stable Diffusion Inpainting(or normal) models from Huggingface in IOPaint. Some popular used models include:
 - Other Diffusion models:
 
 - Plugins
- Segment Anything: Accurate and fast interactive object segmentation
 - RemoveBG: Remove image background or generate masks for foreground objects
 - Anime Segmentation: Similar to RemoveBG, the model is specifically trained for anime images.
 - RealESRGAN: Super Resolution
 - GFPGAN: Face Restoration
 - RestoreFormer: Face Restoration
 
 - FileManager: Browse your pictures conveniently and save them directly to the output directory.