Severstal

Deep Learning excercise on Severstal dataset from Kaggle competition https://www.kaggle.com/c/severstal-steel-defect-detection

Learning objectives:

• perform data exploration
• build deep learning model using U-Net for Image Segmentation
• learn/use keras and tensorflow
• using Colab for running Notebook with GPU

Links to used sources

1. Downloading data in Colab using Kaggle API https://towardsdatascience.com/downloading-datasets-into-google-drive-via-google-colab-bcb1b30b0166
2. how to build and visualize masks https://www.kaggle.com/titericz/building-and-visualizing-masks
3. Building Keras data generator https://stanford.edu/~shervine/blog/keras-how-to-generate-data-on-the-fly
4. Model architecture https://www.kaggle.com/xhlulu/severstal-simple-keras-u-net-boilerplate

Running notebook

Use Google Colab

Make sure to use GPU as Hardware Accelerator in Edit -> Notebook settings

TODO:

Results validation