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FocalLoss.py
README.md
augmentation.py
class_weight.npy
cls.py
cnn_runner_pth.py
downloader.py
evaluate_submit.py
evaluate_val_acc.py
misc.py
models.py
statistics.py
submit.py
sx.csv
transformToRGB.py
utils.py

README.md

Kaggle: imaterialist-challenge-furniture-2018

Competition: image classification with 128 classes Link: https://www.kaggle.com/c/imaterialist-challenge-furniture-2018

How to run

  1. Download data from kaggle to ./data/
  2. Train model python cnn_runner_pth.py train model_name augmentation_mixup mixup_alpha
  3. Predict python cnn_runner_pth.py predict model_name augmentation_mixup mixup_alpha
  4. Calculate weights for finetuned models python statistics.py
  5. Generate submission python submit.py

Ensemble

  • ensemble denset201, inceptionv4, inceptionresnetv2, senet154, se_resnext101, naslarge
  • hflip at test

Result

  • Public Borard: 9/436 Private Board: 13/436
  • models trained at model

Related Projects

  • skrypka : winner of imaterialist furniture 2018
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