PyTorch implementation of 1D, 2D and 3D U-Net.
Project description
PyTorch implementation of 1D, 2D and 3D U-Net.
The U-Net architecture was first described in Ronneberger et al. 2015, U-Net: Convolutional Networks for Biomedical Image Segmentation. The 3D version was described in Çiçek et al. 2016, 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation.
Installation
pip install unet
Credits
If you used this code for your research, please cite this repository using the information available on its Zenodo entry:
Pérez-García, Fernando. (2020). fepegar/unet: PyTorch implementation of 2D and 3D U-Net (v0.7.5). Zenodo. https://doi.org/10.5281/zenodo.3697931
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file unet-0.8.1.tar.gz.
File metadata
- Download URL: unet-0.8.1.tar.gz
- Upload date:
- Size: 8.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.5.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d7a7529a755fa93a067c94ecaf023c248651721041cd316f987b964ad3f1f89b
|
|
| MD5 |
68b3db4b56976fd4ef2288d1a8fce0f2
|
|
| BLAKE2b-256 |
daef4ecc5c1df855b91e094cc501ffe009a8f28c03d86ec646276ec075374ea3
|
File details
Details for the file unet-0.8.1-py3-none-any.whl.
File metadata
- Download URL: unet-0.8.1-py3-none-any.whl
- Upload date:
- Size: 7.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.5.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9ffeffa23e2042c52e937b7d6749eae1a0d0fb2e2ff81c08ca15334194994893
|
|
| MD5 |
5a52e0b549d9f8d34d425406093bdde3
|
|
| BLAKE2b-256 |
75626c202bc1f6e20cab375298b33b66f7c89fba999fd96dce36ddcd88d7fb40
|