fast_sam

FastSAM

Input

(Image from https://github.com/CASIA-IVA-Lab/FastSAM/tree/main/images/cat.png)

Output

segmentation

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 fast_sam.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 fast_sam.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --model_type, -m option, you can specify model type which is selected from "FastSAM-s","FastSAM-x".(default is FastSAM-x)

$ python3 fast_sam.py -m FastSAM-s

Box

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 fast_sam.py --box_prompt "[[252,108,726,1808]]"

Text Prompt

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 fast_sam.py --text_prompt "cat" 

Reference

• FastSAM

Framework

PyTorch

Model Format

ONNX opset = 17

Netron

FastSAM-s.onnx.prototxt FastSAM-x.onnx.prototxt

ViT-B32-encode_image.onnx.prototxt ViT-B32-encode_text.onnx.prototxt