{"library":"segmentation-models-pytorch","type":"library","category":null,"description":"Segmentation Models PyTorch (SMP) is a Python library offering a high-level API for various neural network architectures, pre-trained backbones, losses, and metrics for image semantic segmentation. It supports 12 encoder-decoder architectures and over 800 pre-trained convolutional and transformer-based encoders, leveraging `timm` for a vast selection. The library focuses on simplicity, fast convergence, and compatibility with PyTorch's `torch.jit.script`, `torch.compile`, and `torch.export` features. It is currently at version 0.5.0 and maintains an active release cadence with frequent updates and new model integrations.","language":"python","status":"active","version":"0.5.0","tags":["pytorch","segmentation","deep-learning","computer-vision","models","unet","fpn","deeplabv3","transformers","image-processing"],"install":[{"cmd":"pip install segmentation-models-pytorch","imports":["import segmentation_models_pytorch as smp","model = smp.Unet(...)","from segmentation_models_pytorch.encoders import get_preprocessing_fn"]}],"homepage":null,"github":"https://github.com/qubvel-org/segmentation_models.pytorch","docs":null,"changelog":null,"pypi":"https://pypi.org/project/segmentation-models-pytorch/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":90,"avg_install_s":71.9,"avg_import_s":14.44,"wheel_type":"sdist"},"url":"https://checklist.day/v1/registry/segmentation-models-pytorch/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}