U-Net Architecture

The project is was inspired from the original U-Net Architecture paper "U-Net: Convolutional Networks for Biomedical Image Segmentation"[https://arxiv.org/abs/1505.04597]

• The Architecture of the model implemented can be found in the following Image

Prepare the dataset

Downloading from Kaggle

kaggle competitions download -c carvana-image-masking-challenge

• Extract the dataset
• create a New folder "valid"
• select copy and paste the last 48 Images in the train folder to "valid"

Run Locally

Clone the project

  git clone darthvader2/U-Net-implementation-from-scratch

Go to the project directory

  cd U-Net-implementation-from-scratch

Install dependencies

  pip install -r requirements.txt

Training the model

  python train.py

Changing the image directory in train.py