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Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch Tutorial for Deep Learning Researchers
OpenMMLab Detection Toolbox and Benchmark
⚡ A Fast, Extensible Progress Bar for Python and CLI
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
A paper list of object detection using deep learning.
A suite of utilities for converting to and working with CSV, the king of tabular file formats.
Model summary in PyTorch similar to `model.summary()` in Keras
Paper and implementation of UNet-related model.
[IEEE TMI] Official Implementation for UNet++
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
Read, modify and write DICOM files with python code
pip install antialiased-cnns to improve stability and accuracy
A memory-efficient implementation of DenseNets
Retina blood vessel segmentation with a convolutional neural network
PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).
Here is a pytorch implementation of deeplabv3+ supporting ResNet(79.155%) and Xception(79.945%). Multi-scale & flip test and COCO dataset interface has been finished.
liver segmentation using deep learning
[TMI'20, AAAI'19] Synergistic Image and Feature Adaptation
LiTS - Liver Tumor Segmentation Challenge
MICCAI2019:3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation
3D Unet biomedical segmentation model powered by tensorpack with fast io speed
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiograph…