Implementation of modified U-Net: Convolutional Networks for Biomedical Image Segmentation in TF 2.0 keras API.

Results

Initial predict	Training process

Usage example

python main.py \
    --train_path=data/membrane/train\
    --batch_size=2 \
    --epoch=50 \
    --steps_per_epoch=300 \

References

paper

• https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/

blogs

Those are nicely explained material to understand sementic segmentation and convolution operation.

• Understanding Semantic Segmentation with UNET https://towardsdatascience.com/understanding-semantic-segmentation-with-unet-6be4f42d4b47
• Up-sampling with transposed convolution https://medium.com/activating-robotic-minds/up-sampling-with-transposed-convolution-9ae4f2df52d0

code

Implementation of deep learning framework -- Unet, using Keras https://github.com/zhixuhao/unet

Model Architecture