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added sam model to readme

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Flippchen 2023-04-20 22:57:24 +02:00
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README.md
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@ -243,7 +243,7 @@ for file in Path('path/to/folder').glob('*.png'):
output = remove(input, session=session)
o.write(output)
```
To see a full list of examples on how to use rembg, go to the [examples](USAGE.md) page.
## Usage as a docker
Just replace the `rembg` command for `docker run danielgatis/rembg`.
@ -266,6 +266,7 @@ The available models are:
- u2net_cloth_seg ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net_cloth_seg.onnx), [source](https://github.com/levindabhi/cloth-segmentation)): A pre-trained model for Cloths Parsing from human portrait. Here clothes are parsed into 3 category: Upper body, Lower body and Full body.
- silueta ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/silueta.onnx), [source](https://github.com/xuebinqin/U-2-Net/issues/295)): Same as u2net but the size is reduced to 43Mb.
- isnet-general-use ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/isnet-general-use.onnx), [source](https://github.com/xuebinqin/DIS)): A new pre-trained model for general use cases.
- sam ([download encoder](https://github.com/danielgatis/rembg/releases/download/v0.0.0/vit_b-encoder-quant.onnx), [download decoder](https://github.com/danielgatis/rembg/releases/download/v0.0.0/vit_b-decoder-quant.onnx), [source](https://github.com/facebookresearch/segment-anything)): A pre-trained model for any use cases.
### Some differences between the models result