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@@ -0,0 +1 @@ +/rembg-2.0.35.tar.gz diff --git a/python-rembg.spec b/python-rembg.spec new file mode 100644 index 0000000..7b42254 --- /dev/null +++ b/python-rembg.spec @@ -0,0 +1,1123 @@ +%global _empty_manifest_terminate_build 0 +Name: python-rembg +Version: 2.0.35 +Release: 1 +Summary: Remove image background +License: MIT License +URL: https://github.com/danielgatis/rembg +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a7/8c/0ac2711dfd4440225963395d00d4768528cc9c4572539dd4a51df067d159/rembg-2.0.35.tar.gz +BuildArch: noarch + +Requires: python3-aiohttp +Requires: python3-asyncer +Requires: python3-click +Requires: python3-fastapi +Requires: python3-filetype +Requires: python3-imagehash +Requires: python3-numpy +Requires: python3-onnxruntime +Requires: python3-opencv-python-headless +Requires: python3-pillow +Requires: python3-pooch +Requires: python3-pymatting +Requires: python3-multipart +Requires: python3-scikit-image +Requires: python3-scipy +Requires: python3-tqdm +Requires: python3-uvicorn +Requires: python3-watchdog +Requires: python3-onnxruntime-gpu + +%description +# Rembg + +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://img.shields.io/badge/License-MIT-blue.svg) +[](https://huggingface.co/spaces/KenjieDec/RemBG) +[](https://bgremoval.streamlit.app/) + + +Rembg is a tool to remove images background. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.out.png" width="100" /> +</p> + +**If this project has helped you, please consider making a [donation](https://www.buymeacoffee.com/danielgatis).** + +## Sponsor + +<table> + <tr> + <td align="center" vertical-align="center"> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor" > + <img src="https://font-cdn.photoroom.com/media/api-logo.png" width="120px;" alt="Unsplash" /> + </a> + </td> + <td align="center" vertical-align="center"> + <b>PhotoRoom Remove Background API</b> + <br /> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor">https://photoroom.com/api</a> + <br /> + <p width="200px"> + Fast and accurate background remover API<br/> + </p> + </td> + </tr> +</table> + +## Requirements + +``` +python: >3.7, <3.11 +``` + +## Installation + +CPU support: + +```bash +pip install rembg +``` + +GPU support: + +First of all, you need to check if your system supports the `onnxruntime-gpu`. + +Go to https://onnxruntime.ai and check the installation matrix. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/onnxruntime-installation-matrix.png" width="400" /> +</p> + +If yes, just run: + +```bash +pip install rembg[gpu] +``` + +## Usage as a cli + +After the installation step you can use rembg just typing `rembg` in your terminal window. + +The `rembg` command has 3 subcommands, one for each input type: +- `i` for files +- `p` for folders +- `s` for http server + +You can get help about the main command using: + +``` +rembg --help +``` + +As well, about all the subcommands using: + +``` +rembg <COMMAND> --help +``` + +### rembg `i` + +Used when input and output are files. + +Remove the background from a remote image + +``` +curl -s http://input.png | rembg i > output.png +``` + +Remove the background from a local file + +``` +rembg i path/to/input.png path/to/output.png +``` + +Remove the background specifying a model + +``` +rembg i -m u2netp path/to/input.png path/to/output.png +``` + +Remove the background returning only the mask + +``` +rembg i -om path/to/input.png path/to/output.png +``` + + +Remove the background applying an alpha matting + +``` +rembg i -a path/to/input.png path/to/output.png +``` + +Passing extras parameters + +``` +rembg i -m sam -x '{"input_labels": [1], "input_points": [[100,100]]}' path/to/input.png path/to/output.png +``` + +### rembg `p` + +Used when input and output are folders. + +Remove the background from all images in a folder + +``` +rembg p path/to/input path/to/output +``` + +Same as before, but watching for new/changed files to process + +``` +rembg p -w path/to/input path/to/output +``` + +### rembg `s` + +Used to start http server. + +To see the complete endpoints documentation, go to: `http://localhost:5000/docs`. + +Remove the background from an image url + +``` +curl -s "http://localhost:5000/?url=http://input.png" -o output.png +``` + +Remove the background from an uploaded image + +``` +curl -s -F file=@/path/to/input.jpg "http://localhost:5000" -o output.png +``` + +## Usage as a library + +Input and output as bytes + +```python +from rembg import remove + +input_path = 'input.png' +output_path = 'output.png' + +with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + output = remove(input) + o.write(output) +``` + +Input and output as a PIL image + +```python +from rembg import remove +from PIL import Image + +input_path = 'input.png' +output_path = 'output.png' + +input = Image.open(input_path) +output = remove(input) +output.save(output_path) +``` + +Input and output as a numpy array + +```python +from rembg import remove +import cv2 + +input_path = 'input.png' +output_path = 'output.png' + +input = cv2.imread(input_path) +output = remove(input) +cv2.imwrite(output_path, output) +``` + +How to iterate over files in a performatic way + +```python +from pathlib import Path +from rembg import remove, new_session + +session = new_session() + +for file in Path('path/to/folder').glob('*.png'): + input_path = str(file) + output_path = str(file.parent / (file.stem + ".out.png")) + + with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + 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`. + +Try this: + +``` +docker run danielgatis/rembg i path/to/input.png path/to/output.png +``` + +## Models + +All models are downloaded and saved in the user home folder in the `.u2net` directory. + +The available models are: + +- u2net ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for general use cases. +- u2netp ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2netp.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A lightweight version of u2net model. +- u2net_human_seg ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net_human_seg.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for human segmentation. +- 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 + +<table> + <tr> + <th>original</th> + <th>u2net</th> + <th>u2netp</th> + <th>u2net_human_seg</th> + <th>u2net_cloth_seg</th> + <th>silueta</th> + <th>isnet-general-use</th> + <th>sam</th> + </tr> + <tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/car-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.sam.png" width="100" /></th> + </tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/cloth-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.sam.png" width="100" /></th> + </tr> +</table> + + +### How to train your own model + +If You need more fine tunned models try this: +https://github.com/danielgatis/rembg/issues/193#issuecomment-1055534289 + + +## Some video tutorials + +- https://www.youtube.com/watch?v=3xqwpXjxyMQ +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=Ai-BS_T7yjE +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=D7W-C0urVcQ + +## References + +- https://arxiv.org/pdf/2005.09007.pdf +- https://github.com/NathanUA/U-2-Net +- https://github.com/pymatting/pymatting + +## Buy me a coffee + +Liked some of my work? Buy me a coffee (or more likely a beer) + +<a href="https://www.buymeacoffee.com/danielgatis" target="_blank"><img src="https://bmc-cdn.nyc3.digitaloceanspaces.com/BMC-button-images/custom_images/orange_img.png" alt="Buy Me A Coffee" style="height: auto !important;width: auto !important;"></a> + +## License + +Copyright (c) 2020-present [Daniel Gatis](https://github.com/danielgatis) + +Licensed under [MIT License](./LICENSE.txt) + + + + +%package -n python3-rembg +Summary: Remove image background +Provides: python-rembg +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-rembg +# Rembg + +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://img.shields.io/badge/License-MIT-blue.svg) +[](https://huggingface.co/spaces/KenjieDec/RemBG) +[](https://bgremoval.streamlit.app/) + + +Rembg is a tool to remove images background. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.out.png" width="100" /> +</p> + +**If this project has helped you, please consider making a [donation](https://www.buymeacoffee.com/danielgatis).** + +## Sponsor + +<table> + <tr> + <td align="center" vertical-align="center"> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor" > + <img src="https://font-cdn.photoroom.com/media/api-logo.png" width="120px;" alt="Unsplash" /> + </a> + </td> + <td align="center" vertical-align="center"> + <b>PhotoRoom Remove Background API</b> + <br /> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor">https://photoroom.com/api</a> + <br /> + <p width="200px"> + Fast and accurate background remover API<br/> + </p> + </td> + </tr> +</table> + +## Requirements + +``` +python: >3.7, <3.11 +``` + +## Installation + +CPU support: + +```bash +pip install rembg +``` + +GPU support: + +First of all, you need to check if your system supports the `onnxruntime-gpu`. + +Go to https://onnxruntime.ai and check the installation matrix. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/onnxruntime-installation-matrix.png" width="400" /> +</p> + +If yes, just run: + +```bash +pip install rembg[gpu] +``` + +## Usage as a cli + +After the installation step you can use rembg just typing `rembg` in your terminal window. + +The `rembg` command has 3 subcommands, one for each input type: +- `i` for files +- `p` for folders +- `s` for http server + +You can get help about the main command using: + +``` +rembg --help +``` + +As well, about all the subcommands using: + +``` +rembg <COMMAND> --help +``` + +### rembg `i` + +Used when input and output are files. + +Remove the background from a remote image + +``` +curl -s http://input.png | rembg i > output.png +``` + +Remove the background from a local file + +``` +rembg i path/to/input.png path/to/output.png +``` + +Remove the background specifying a model + +``` +rembg i -m u2netp path/to/input.png path/to/output.png +``` + +Remove the background returning only the mask + +``` +rembg i -om path/to/input.png path/to/output.png +``` + + +Remove the background applying an alpha matting + +``` +rembg i -a path/to/input.png path/to/output.png +``` + +Passing extras parameters + +``` +rembg i -m sam -x '{"input_labels": [1], "input_points": [[100,100]]}' path/to/input.png path/to/output.png +``` + +### rembg `p` + +Used when input and output are folders. + +Remove the background from all images in a folder + +``` +rembg p path/to/input path/to/output +``` + +Same as before, but watching for new/changed files to process + +``` +rembg p -w path/to/input path/to/output +``` + +### rembg `s` + +Used to start http server. + +To see the complete endpoints documentation, go to: `http://localhost:5000/docs`. + +Remove the background from an image url + +``` +curl -s "http://localhost:5000/?url=http://input.png" -o output.png +``` + +Remove the background from an uploaded image + +``` +curl -s -F file=@/path/to/input.jpg "http://localhost:5000" -o output.png +``` + +## Usage as a library + +Input and output as bytes + +```python +from rembg import remove + +input_path = 'input.png' +output_path = 'output.png' + +with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + output = remove(input) + o.write(output) +``` + +Input and output as a PIL image + +```python +from rembg import remove +from PIL import Image + +input_path = 'input.png' +output_path = 'output.png' + +input = Image.open(input_path) +output = remove(input) +output.save(output_path) +``` + +Input and output as a numpy array + +```python +from rembg import remove +import cv2 + +input_path = 'input.png' +output_path = 'output.png' + +input = cv2.imread(input_path) +output = remove(input) +cv2.imwrite(output_path, output) +``` + +How to iterate over files in a performatic way + +```python +from pathlib import Path +from rembg import remove, new_session + +session = new_session() + +for file in Path('path/to/folder').glob('*.png'): + input_path = str(file) + output_path = str(file.parent / (file.stem + ".out.png")) + + with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + 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`. + +Try this: + +``` +docker run danielgatis/rembg i path/to/input.png path/to/output.png +``` + +## Models + +All models are downloaded and saved in the user home folder in the `.u2net` directory. + +The available models are: + +- u2net ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for general use cases. +- u2netp ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2netp.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A lightweight version of u2net model. +- u2net_human_seg ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net_human_seg.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for human segmentation. +- 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 + +<table> + <tr> + <th>original</th> + <th>u2net</th> + <th>u2netp</th> + <th>u2net_human_seg</th> + <th>u2net_cloth_seg</th> + <th>silueta</th> + <th>isnet-general-use</th> + <th>sam</th> + </tr> + <tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/car-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.sam.png" width="100" /></th> + </tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/cloth-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.sam.png" width="100" /></th> + </tr> +</table> + + +### How to train your own model + +If You need more fine tunned models try this: +https://github.com/danielgatis/rembg/issues/193#issuecomment-1055534289 + + +## Some video tutorials + +- https://www.youtube.com/watch?v=3xqwpXjxyMQ +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=Ai-BS_T7yjE +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=D7W-C0urVcQ + +## References + +- https://arxiv.org/pdf/2005.09007.pdf +- https://github.com/NathanUA/U-2-Net +- https://github.com/pymatting/pymatting + +## Buy me a coffee + +Liked some of my work? Buy me a coffee (or more likely a beer) + +<a href="https://www.buymeacoffee.com/danielgatis" target="_blank"><img src="https://bmc-cdn.nyc3.digitaloceanspaces.com/BMC-button-images/custom_images/orange_img.png" alt="Buy Me A Coffee" style="height: auto !important;width: auto !important;"></a> + +## License + +Copyright (c) 2020-present [Daniel Gatis](https://github.com/danielgatis) + +Licensed under [MIT License](./LICENSE.txt) + + + + +%package help +Summary: Development documents and examples for rembg +Provides: python3-rembg-doc +%description help +# Rembg + +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://pepy.tech/project/rembg) +[](https://img.shields.io/badge/License-MIT-blue.svg) +[](https://huggingface.co/spaces/KenjieDec/RemBG) +[](https://bgremoval.streamlit.app/) + + +Rembg is a tool to remove images background. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/car-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/animal-3.out.png" width="100" /> +</p> + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-1.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-2.out.png" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.jpg" width="100" /> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/examples/girl-3.out.png" width="100" /> +</p> + +**If this project has helped you, please consider making a [donation](https://www.buymeacoffee.com/danielgatis).** + +## Sponsor + +<table> + <tr> + <td align="center" vertical-align="center"> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor" > + <img src="https://font-cdn.photoroom.com/media/api-logo.png" width="120px;" alt="Unsplash" /> + </a> + </td> + <td align="center" vertical-align="center"> + <b>PhotoRoom Remove Background API</b> + <br /> + <a href="https://photoroom.com/api/remove-background?utm_source=rembg&utm_medium=github_webpage&utm_campaign=sponsor">https://photoroom.com/api</a> + <br /> + <p width="200px"> + Fast and accurate background remover API<br/> + </p> + </td> + </tr> +</table> + +## Requirements + +``` +python: >3.7, <3.11 +``` + +## Installation + +CPU support: + +```bash +pip install rembg +``` + +GPU support: + +First of all, you need to check if your system supports the `onnxruntime-gpu`. + +Go to https://onnxruntime.ai and check the installation matrix. + +<p style="display: flex;align-items: center;justify-content: center;"> + <img src="https://raw.githubusercontent.com/danielgatis/rembg/master/onnxruntime-installation-matrix.png" width="400" /> +</p> + +If yes, just run: + +```bash +pip install rembg[gpu] +``` + +## Usage as a cli + +After the installation step you can use rembg just typing `rembg` in your terminal window. + +The `rembg` command has 3 subcommands, one for each input type: +- `i` for files +- `p` for folders +- `s` for http server + +You can get help about the main command using: + +``` +rembg --help +``` + +As well, about all the subcommands using: + +``` +rembg <COMMAND> --help +``` + +### rembg `i` + +Used when input and output are files. + +Remove the background from a remote image + +``` +curl -s http://input.png | rembg i > output.png +``` + +Remove the background from a local file + +``` +rembg i path/to/input.png path/to/output.png +``` + +Remove the background specifying a model + +``` +rembg i -m u2netp path/to/input.png path/to/output.png +``` + +Remove the background returning only the mask + +``` +rembg i -om path/to/input.png path/to/output.png +``` + + +Remove the background applying an alpha matting + +``` +rembg i -a path/to/input.png path/to/output.png +``` + +Passing extras parameters + +``` +rembg i -m sam -x '{"input_labels": [1], "input_points": [[100,100]]}' path/to/input.png path/to/output.png +``` + +### rembg `p` + +Used when input and output are folders. + +Remove the background from all images in a folder + +``` +rembg p path/to/input path/to/output +``` + +Same as before, but watching for new/changed files to process + +``` +rembg p -w path/to/input path/to/output +``` + +### rembg `s` + +Used to start http server. + +To see the complete endpoints documentation, go to: `http://localhost:5000/docs`. + +Remove the background from an image url + +``` +curl -s "http://localhost:5000/?url=http://input.png" -o output.png +``` + +Remove the background from an uploaded image + +``` +curl -s -F file=@/path/to/input.jpg "http://localhost:5000" -o output.png +``` + +## Usage as a library + +Input and output as bytes + +```python +from rembg import remove + +input_path = 'input.png' +output_path = 'output.png' + +with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + output = remove(input) + o.write(output) +``` + +Input and output as a PIL image + +```python +from rembg import remove +from PIL import Image + +input_path = 'input.png' +output_path = 'output.png' + +input = Image.open(input_path) +output = remove(input) +output.save(output_path) +``` + +Input and output as a numpy array + +```python +from rembg import remove +import cv2 + +input_path = 'input.png' +output_path = 'output.png' + +input = cv2.imread(input_path) +output = remove(input) +cv2.imwrite(output_path, output) +``` + +How to iterate over files in a performatic way + +```python +from pathlib import Path +from rembg import remove, new_session + +session = new_session() + +for file in Path('path/to/folder').glob('*.png'): + input_path = str(file) + output_path = str(file.parent / (file.stem + ".out.png")) + + with open(input_path, 'rb') as i: + with open(output_path, 'wb') as o: + input = i.read() + 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`. + +Try this: + +``` +docker run danielgatis/rembg i path/to/input.png path/to/output.png +``` + +## Models + +All models are downloaded and saved in the user home folder in the `.u2net` directory. + +The available models are: + +- u2net ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for general use cases. +- u2netp ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2netp.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A lightweight version of u2net model. +- u2net_human_seg ([download](https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net_human_seg.onnx), [source](https://github.com/xuebinqin/U-2-Net)): A pre-trained model for human segmentation. +- 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 + +<table> + <tr> + <th>original</th> + <th>u2net</th> + <th>u2netp</th> + <th>u2net_human_seg</th> + <th>u2net_cloth_seg</th> + <th>silueta</th> + <th>isnet-general-use</th> + <th>sam</th> + </tr> + <tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/car-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/car-1.sam.png" width="100" /></th> + </tr> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/fixtures/cloth-1.jpg" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2netp.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_human_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.u2net_cloth_seg.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.silueta.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.isnet-general-use.png" width="100" /></th> + <th><img src="https://raw.githubusercontent.com/danielgatis/rembg/master/tests/results/cloth-1.sam.png" width="100" /></th> + </tr> +</table> + + +### How to train your own model + +If You need more fine tunned models try this: +https://github.com/danielgatis/rembg/issues/193#issuecomment-1055534289 + + +## Some video tutorials + +- https://www.youtube.com/watch?v=3xqwpXjxyMQ +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=Ai-BS_T7yjE +- https://www.youtube.com/watch?v=dFKRGXdkGJU +- https://www.youtube.com/watch?v=D7W-C0urVcQ + +## References + +- https://arxiv.org/pdf/2005.09007.pdf +- https://github.com/NathanUA/U-2-Net +- https://github.com/pymatting/pymatting + +## Buy me a coffee + +Liked some of my work? Buy me a coffee (or more likely a beer) + +<a href="https://www.buymeacoffee.com/danielgatis" target="_blank"><img src="https://bmc-cdn.nyc3.digitaloceanspaces.com/BMC-button-images/custom_images/orange_img.png" alt="Buy Me A Coffee" style="height: auto !important;width: auto !important;"></a> + +## License + +Copyright (c) 2020-present [Daniel Gatis](https://github.com/danielgatis) + +Licensed under [MIT License](./LICENSE.txt) + + + + +%prep +%autosetup -n rembg-2.0.35 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-rembg -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.35-1 +- Package Spec generated @@ -0,0 +1 @@ +033620da668484b8e4d7212ed4c64888 rembg-2.0.35.tar.gz |