Required version of Python: 3.10+
Installing this tool is pretty easy, beacause it depends only on two main packages: NumPy and OpenCV. So you can at first run:
python -m pip install -r requirements.txt
usage: main.py [-h] [--root ROOT] [--output OUTPUT] [--format FORMAT] [--ttsplit TTSPLIT] [-vw VIEWPORT_WIDTH] [-vh VIEWPORT_HEIGHT] [--image-width IMAGE_WIDTH] [--image-height IMAGE_HEIGHT]
options:
-h, --help show this help message and exit
--root ROOT Path to the folder with input images.
--output OUTPUT Path to the folder where dataset will be stored.
--format FORMAT Choose between 'standard' and 'tficon' format of COCO dataset.
--ttsplit TTSPLIT Value between 0.0 and 1.0 that sets the size of the train part.
-vw VIEWPORT_WIDTH, --viewport-width VIEWPORT_WIDTH
Width of the viewport window.
-vh VIEWPORT_HEIGHT, --viewport-height VIEWPORT_HEIGHT
Height of the viewport window.
--image-width IMAGE_WIDTH
Width of the image to save. If None than the width will not change.
--image-height IMAGE_HEIGHT
Height of the image to save. If None than the height will not change.
The example usage of the tool is:
python main.py --root example/inputs --output output
You should get the same output as in the example/output folder.
- For saving current state of the labelling press 's'.
- Moving to the next image 'n'.
- Back to the previous image 'p'.