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@@ -100,14 +100,14 @@ pip install "rembg[cli]" # for library + cli
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Otherwise, install `rembg` with explicit CPU/GPU support.
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-CPU support:
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+### CPU support:
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```bash
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pip install rembg[cpu] # for library
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pip install "rembg[cpu,cli]" # for library + cli
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```
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-GPU support:
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+### GPU support:
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First of all, you need to check if your system supports the `onnxruntime-gpu`.
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@@ -124,6 +124,8 @@ pip install "rembg[gpu]" # for library
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pip install "rembg[gpu,cli]" # for library + cli
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```
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+Nvidia GPU may require onnxruntime-gpu, cuda, and cudnn-devel. [#668](https://github.com/danielgatis/rembg/issues/668#issuecomment-2689830314) . If rembg[gpu] couldn't work probably and your can't install cuda or cudnn-devel, use rembg[cpu] and onnxruntime instead.
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+
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## Usage as a cli
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After the installation step you can use rembg just typing `rembg` in your terminal window.
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@@ -346,6 +348,8 @@ Try this:
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docker run -v path/to/input:/rembg danielgatis/rembg i input.png path/to/output/output.png
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```
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+Notice: Right now docker version only support CPU Acceleration.
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+
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## Models
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All models are downloaded and saved in the user home folder in the `.u2net` directory.
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