My code for Cdiscount's Image Classification Challenge. Tested on a subset of 10k samples from the ~7m on the full dataset.
- Keras 2.0 w/ TF backend
- sklearn
- skimage
- tqdm
- h5py
- imgaug
- In
params.py
setbase_dir
to your working directory. You can also set the model to use and training parameters. - Place train.bson and test.bson in {work_dir}/input.
- Run
read_data_train.py
andread_data_test.py
to read and unpack train data and test data respectively. - Run
train.py
to train the model andtest_submit.py
to predict on test data and generate submission file.