Fully Convolutional Networks for Semantic Segmentation

Pytorch implementation of paper from berkeley@Jonathan Long.

I use KITTI road dataset, you can download link.

You will need the following package before you go through the tutorials.
Recommand you using Anaconda 3 !!!

FCN is using skipped network which stitches the pooling layers of pretrained model to compensate important features while training.

I think everyone eagered to see the result while the beginning. Hence, I recommend you to see what you got after this tutorials. demo.ipynb

Next, you will want to see the structure of this powerful model. introduction.ipynb

Last but not least, you will want to learn how you can build your own model. train.ipynb

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
archived		archived
FCN.py		FCN.py
LICENSE		LICENSE
README.md		README.md
data_helper.py		data_helper.py
demo.ipynb		demo.ipynb
draw.py		draw.py
introduction.ipynb		introduction.ipynb
labelmap.py		labelmap.py
sample.png		sample.png
train.ipynb		train.ipynb
validate.py		validate.py

Provide feedback