Rerender / ControlNet /docs /annotator.md
Anonymous-sub's picture
merge (#1)
251e479
|
raw
history blame
1.26 kB
# 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".
![p](../github_page/a1.png)
### HED Edge
Be careful about "black edge and white background" or "white edge and black background".
![p](../github_page/a2.png)
### MLSD Edge
Be careful about "black edge and white background" or "white edge and black background".
![p](../github_page/a3.png)
### MIDAS Depth and Normal
Be careful about RGB or BGR in normal maps.
![p](../github_page/a4.png)
### Openpose
Be careful about RGB or BGR in pose maps.
For our production-ready model, the hand pose option is turned off.
![p](../github_page/a5.png)
### Uniformer Segmentation
Be careful about RGB or BGR in segmentation maps.
![p](../github_page/a6.png)