Simple static web-based mask drawer, supporting semantic drawing with Segment Anything Model (SAM).

From top to bottom

• Clear image
• Drawer
• SAM point-segmenter (Need backend)
• SAM rect-segmenter (Need backend)
• SAM Seg-Everything (Need backend)
• Undo
• Eraser
• Download

After Seg-Everything, the downloaded files would include .zip file, which contains all cut-offs.

If don't need SAM for segmentation, just open segDrawer.html and use tools except SAM segmenter.

If use SAM segmenter, do following steps (CPU can be time-consuming)

• Download models as mentioned in segment-anything. For example

wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_l_0b3195.pth

• Launch backend

python server.py

• Go to Browser

http://127.0.0.1:8000

For configuring CPU/GPU and model, just change the code in server.py

sam_checkpoint = "sam_vit_l_0b3195.pth" # "sam_vit_l_0b3195.pth" or "sam_vit_h_4b8939.pth"
model_type = "vit_l" # "vit_l" or "vit_h"
device = "cuda" # "cuda" if torch.cuda.is_available() else "cpu"

Follow this Colab example, or run on Colab. Need to register an ngrok account and copy your token to replace "{your_token}".