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Kaggle Cdiscount's Image Classification Challenge solution with Keras

My code for Cdiscount's Image Classification Challenge. Tested on a subset of 10k samples from the ~7m on the full dataset.


Requirements

  • Keras 2.0 w/ TF backend
  • sklearn
  • skimage
  • tqdm
  • h5py
  • imgaug

Usage

  1. In params.py set base_dir to your working directory. You can also set the model to use and training parameters.
  2. Place train.bson and test.bson in {work_dir}/input.
  3. Run read_data_train.py and read_data_test.py to read and unpack train data and test data respectively.
  4. Run train.py to train the model and test_submit.py to predict on test data and generate submission file.

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