segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
About this project
Python library with Neural Networks for Image Semantic Segmentation based on PyTorch. The main features of the library are: — 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 🤝 Sponsor: withoutBG withoutBG is a high-quality background removal tool. They built their open-source image matting and refiner models using smp.Unet and are proudly…
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