Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
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Updated
Aug 26, 2024 - Python
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Paper and implementation of UNet-related model.
[IEEE TMI] Official Implementation for UNet++
3D U-Net model for volumetric semantic segmentation written in pytorch
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
《深度学习与计算机视觉》配套代码
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
PyTorch implementation of UNet++ (Nested U-Net).
Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation
This is a code repository for pytorch c++ (or libtorch) tutorial.
BCDU-Net : Medical Image Segmentation
The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
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