segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Create advanced image segmentation models easily with a library that includes many pre-trained options.
From the README
$ pip install segmentation-models-pytorch
- Super simple high-level API (just two lines to create a neural network)
- 12 encoder-decoder model architectures (Unet, Unet++, Segformer, DPT, ...)
- 800+ pretrained convolution- and transform-based encoders, including timm support
- Popular metrics and losses for training routines (Dice, Jaccard, Tversky, ...)
- ONNX export and torch script/trace/compile friendly
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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segmentation_models.pytorch has 11.7k stars on GitHub. It has been forked 1.8k times. segmentation_models.pytorch is written mainly in Python. It has been in active development since 2019. segmentation_models.pytorch is available under the MIT license. Its main topics are computer-vision, deeplab-v3-plus, deeplabv3, dpt.
What is segmentation_models.pytorch?
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Is segmentation_models.pytorch open source?
segmentation_models.pytorch is an open-source project. It is released under the MIT license.
Is segmentation_models.pytorch free?
Yes. segmentation_models.pytorch is free and open source — you can use, modify and self-host it.
What license does segmentation_models.pytorch use?
segmentation_models.pytorch is available under the MIT license.
What language is segmentation_models.pytorch written in?
segmentation_models.pytorch is written mainly in Python.
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