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Segment Anything

Input

Input

(Image from https://github.com/facebookresearch/segment-anything/blob/main/notebooks/images/truck.jpg)

Output

  • 1 positive point Output

  • 2 positive points Output

  • 1 positive point, 1 negative point Output

  • box Output

  • box, 1 negative point Output

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 segment-anything.py

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 segment-anything.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

If you want to specify the positive point, put the coordinates(x,y) after the --pos option.

$ python3 segment-anything.py --pos 500 375

And if you want to specify the negative point, put the coordinates after the --neg option.

$ python3 segment-anything.py --pos 500 375 --neg 360 405

If you want to specify the box, put the coordinates(x1,y1,x2,y2) after the --box option.

$ python3 segment-anything.py --box 425 600 700 875

These options can be combined.

$ python3 segment-anything.py --pos 500 375 --pos 1125 625
$ python3 segment-anything.py --box 425 600 700 875 --neg 575 750

By adding the --model_type option, you can specify model type which is selected from "sam_h", "sam_l", "sam_b". (default is sam_h)

$ python3 segment-anything.py --model_type sam_l

Reference

Framework

Pytorch

Model Format

ONNX opset=12

Netron

sam_h_4b8939.onnx.prototxt
sam_l_0b3195.onnx.prototxt
sam_b_01ec64.onnx.prototxt
vit_h_4b8939.onnx.prototxt
vit_l_0b3195.onnx.prototxt
vit_b_01ec64.onnx.prototxt