Laurent/REVA-QCAV
1
0
Fork 0
mirror of https://github.com/Laurent2916/REVA-QCAV.git synced 2024-09-19 11:35:28 +00:00
Code Issues Packages Projects Releases Wiki Activity

Update README with xs:code

Browse source 
Former-commit-id: 84f8392b619940bd542dc670761a0a7a1357001d
This commit is contained in:
milesial 2020-07-23 17:04:38 -07:00 committed by GitHub
parent cc2ac3db07
commit 04c2cb1ed4
1 changed files with 8 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

8
README.md
View file

@ -1,5 +1,8 @@
# UNet: semantic segmentation with PyTorch
[![xscode](https://img.shields.io/badge/Available%20on-xs%3Acode-blue?style=?style=plastic&logo=appveyor&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAMAAACdt4HsAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAAZQTFRF////////VXz1bAAAAAJ0Uk5T/wDltzBKAAAAlUlEQVR42uzXSwqAMAwE0Mn9L+3Ggtgkk35QwcnSJo9S+yGwM9DCooCbgn4YrJ4CIPUcQF7/XSBbx2TEz4sAZ2q1RAECBAiYBlCtvwN+KiYAlG7UDGj59MViT9hOwEqAhYCtAsUZvL6I6W8c2wcbd+LIWSCHSTeSAAECngN4xxIDSK9f4B9t377Wd7H5Nt7/Xz8eAgwAvesLRjYYPuUAAAAASUVORK5CYII=)](https://xscode.com/milesial/Pytorch-UNet)
![input and output for a random image in the test dataset](https://framapic.org/OcE8HlU6me61/KNTt8GFQzxDR.png)
@ -92,6 +95,11 @@ Predicting images of 1918*1280 takes 1.5GB of memory.
Training takes much approximately 3GB, so if you are a few MB shy of memory, consider turning off all graphical displays.
This assumes you use bilinear up-sampling, and not transposed convolution in the model.
## Support
Personalized support for issues with this repository, or integrating with your own dataset, available on [xs:code](https://xscode.com/milesial/Pytorch-UNet).
---
Original paper by Olaf Ronneberger, Philipp Fischer, Thomas Brox: [https://arxiv.org/abs/1505.04597](https://arxiv.org/abs/1505.04597)