| milesial/Pytorch-UNet |
7,861 |
|
0 |
0 |
over 2 years ago |
0 |
|
80 |
gpl-3.0 |
Python |
| PyTorch implementation of the U-Net for image semantic segmentation with high quality images |
| PaddlePaddle/PaddleX |
4,510 |
|
0 |
2 |
over 2 years ago |
54 |
December 10, 2021 |
538 |
apache-2.0 |
Python |
| PaddlePaddle End-to-End Development Toolkit(『飞桨』深度学习全流程开发工具) |
| zhixuhao/unet |
4,218 |
|
0 |
0 |
about 3 years ago |
0 |
|
203 |
mit |
Jupyter Notebook |
| unet for image segmentation |
| jakeret/tf_unet |
1,582 |
|
0 |
0 |
about 6 years ago |
0 |
|
85 |
gpl-3.0 |
Python |
| Generic U-Net Tensorflow implementation for image segmentation |
| yeyun111/dlcv_for_beginners |
1,409 |
|
0 |
0 |
over 5 years ago |
0 |
|
|
bsd-3-clause |
Python |
| 《深度学习与计算机视觉》配套代码 |
| MIC-DKFZ/medicaldetectiontoolkit |
1,249 |
|
0 |
0 |
over 2 years ago |
0 |
|
44 |
apache-2.0 |
Python |
| The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images. |
| The-AI-Summer/Deep-Learning-In-Production |
949 |
|
0 |
0 |
about 3 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples. |
| black0017/MedicalZooPytorch |
896 |
|
0 |
0 |
over 4 years ago |
0 |
|
13 |
mit |
Python |
| A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation |
| akirasosa/mobile-semantic-segmentation |
677 |
|
0 |
0 |
over 4 years ago |
0 |
|
14 |
mit |
Python |
| Real-Time Semantic Segmentation in Mobile device |
| thuyngch/Human-Segmentation-PyTorch |
532 |
|
0 |
0 |
over 3 years ago |
0 |
|
21 |
|
Jupyter Notebook |
| Human segmentation models, training/inference code, and trained weights, implemented in PyTorch |