# COPAINT
TLDR: From generated Image -> Copaint PDF
<!-- insert image data/demo.png -->
[![demo](data/demo.jpg)](data/demo.jpg)


```
git clone https://github.com/ThibaultGROUEIX/copaint.git
git lfs pull #(install git LFS)
```


## Usage and Install
```
# Install dependencies
poetry install --with ui

# Run Gradio App on local server
poetry run copaint-app
```

## Alternative Usage and Install (CLI)
```
# Install dependencies
pip install torch torchvision reportlab PyPDF2 Pillow argparse gradio_pdf

# Run
python copaint.py --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output

# Using the CLI
pip install --upgrade pip
pip install -e .

# Case 1 : generate all the presets
copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --use_presets True

# Case 2 : provide a number of participants, the program will generate the best grid
copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --nparticipants 45 

# Case 3 : provide the number of cells in the grid
copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --h_cells 3 --w_cells 4
```

## Build and deploy
```
# Build
poetry build
# Deploy
poetry publish
```

## Time bottleneck
-- the biggest time bottleneck is writing to disk the back image and loading for the PDF creation.



# Deploy to huggingface.
git remote add hf https://huggingface.co/spaces/groueix/copaint
git push hf main