Reverse Dependencies of segmentation-models-pytorch

The following projects have a declared dependency on segmentation-models-pytorch:

• adelecv — no summary
• atomvision — atomvision
• audiossl — no summary
• autoalbument — AutoML for image augmentation
• autoballs — Python package for segmentation of axons and morphological analysis.
• celldetection — Cell Detection with PyTorch.
• cloths-segmentation — High quality model for cloths segmentation.
• cloudsen12 — A Python package for use cloudsen12
• cnn-framework — CNN framework
• convnext-unet — Unet model with ConvNext as its encoder.
• custom-bgr — Customized background removal app
• devolearn — Accelerate data driven research in developmental biology with deep learning models
• doc2graph — Repo to transform Documents to Graphs, performing several tasks on them.
• earsegmentationai — Pytorch Based - Efficient and Lightweight Ear Segmentation
• earthnet-minicuber — EarthNet Minicuber
• earthnet-models-pytorch — EarthNet Models PyTorch
• exlib — Toolkit for explainability by BrachioLab
• fractalai — Integrated image classification and semantic segmentation package
• gandlf — PyTorch-based framework that handles segmentation/regression/classification using various DL architectures for medical imaging.
• geowatch — no summary
• icflow — A collection of simple utilities for machine learning workflows.
• imsy-htc — Framework for automatic classification and segmentation of hyperspectral images.
• innoframework — no summary
• lightning-flash — Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes.
• marinedebrisdetector — A detector of marine debris with Sentinel-2 scenes
• midv500models — Document segmentation.
• moonshine — Pretrained remote sensing models.
• napari-PHILOW — PHILOW is an interactive deep learning-based platform for 3D datasets
• nntemplate — Bundle of usefull tools for training segmentation or image classification neural networks.
• page2struct — Repo to extract structure from document page.
• pathpretrain — Simple setup train image models.
• people-segmentation — High quality model for people segmentation.
• pixel-classifier-torch — no summary
• pmap3.0.7 — TEST PMAP
• pmap3.0.8 — TEST PMAP
• pytorch-segmentation-models-trainer — Image segmentation models training of popular architectures.
• rudalle — ruDALL-E generate images from texts in Russian language
• satseg — A python package to assist in multispectral satellite image segmentation.
• segal — SegAL is an active learning freamwork for semantice segmentation.
• self-supervised-dermatology — Unsupervised Pre-Training for Texture Segmentation in Dermatology
• SiriusN16CXRseg — Проект по сегментации легких.
• slideflow — Deep learning tools for digital histology
• tati-tools — Tools for computer vision tasks.
• torch-pixel-classifier — no summary
• torchgeo — TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
• volume-segmantics — A toolkit for semantic segmentation of volumetric data using pyTorch deep learning models
• volume-segmantics-vsui — A toolkit for semantic segmentation of volumetric data using pyTorch deep learning models
• wow-ai-sam — Finetune segment-anything