Automatic Annotations

We provide gradio examples to obtain annotations that are aligned to our pretrained production-ready models.

Just run

python gradio_annotator.py

Since everyone has different habit to organize their datasets, we do not hard code any scripts for batch processing. But "gradio_annotator.py" is written in a super readable way, and modifying it to annotate your images should be easy.

In the gradio UI of "gradio_annotator.py" we have the following interfaces:

Canny Edge

Be careful about "black edge and white background" or "white edge and black background".

HED Edge

Be careful about "black edge and white background" or "white edge and black background".

MLSD Edge

Be careful about "black edge and white background" or "white edge and black background".

MIDAS Depth and Normal

Be careful about RGB or BGR in normal maps.

Openpose

Be careful about RGB or BGR in pose maps.

For our production-ready model, the hand pose option is turned off.

Uniformer Segmentation

Be careful about RGB or BGR in segmentation maps.