This codebase contains a pyqt application to create image captioning dataset to train image captioning models.
docker build --no-cache -t desalef/pyqt-caption-dataset .
xhost +
docker run --rm -it \
-e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix \
--ipc=host --volume="$HOME/.Xauthority:/root/.Xauthority:rw" \
--userns=host \
--net=host \
desalef/pyqt-caption-dataset:latest /bin/bash
python3 src/main.py
To caption images inside the folder you need to mount the folder into the docker container when you run the container. simply add " -v path/to/images:/usr/app \ "
after " --net=host \ "
on run command provided above.
- export captions into different dataset format
- Undo and Redo changes
- Enter for save and load next image
├── assets
│ ├── arrow-left.png
│ ├── arrow-right.png
│ └── ...
├── docker
│ ├── build.sh
│ └── run-docker.sh
├── src
│ ├── __init__.py
│ ├── actions.py
│ └── main.py
├── utils
│ ├── __init__.py
│ └── utils.py
├── Dockerfile
├── __init__.py
├── LICENSE
├── main.ui
└── README.md