ankurag12/CIFAR-10
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Download data from: https://www.kaggle.com/c/cifar-10/data To convert jpegs into TFRecords (one-time run) $python convert_to_records.py Evaluation can be run independently of training. Training script saves checkpoint files, which evaluation script can read. (Must run training for sufficient time to generate a checkpoint file. Default is 1 epoch) To train the model: $python train_cnn.py To evaluate the model on validation set: $python eval_cnn.py 'validation' To evaluate the model on test set: $python eval_cnn.py 'test' To visualize training data on TensorBoard: $tensorboard --logdir=tmp/train_data/ To visualize evaluation data on TensorBoard: $tensorboard --logdir=tmp/eval_data/ Currently getting 85% accuracy on validation set. Code highly inspired from tensorflow tutorials.
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Image classification on the popular dataset CIFAR-10
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