Transfer learning using inception_resnet_v2
This project obtained from https://github.com/kwotsin/transfer_learning_tutorial enables the application of a transfer learning approach using a inception_resnet_v2 pre-trained model.
Run create_tfrecord.py to create tfrecords.
Run train_dais.py for training and eval_dais.py for evaluation.
Images are stored in dais\dais_photos
- Python 2.7.x
- TensorFlow >= 0.12
NOTE: If you want to run this program on Python 3, clone and run git checkout python-3.0 for the Python 3 branch instead.
- dataset_dir (string): The directory to your dataset that is arranged in a structured way where your subdirectories keep classes of your images.
For example:
dais\
dais_photos\
cars\
....jpg
....jpg
....jpg
empty_road\
....jpg
Note: Your dataset_dir should be /path/to/dais and not /path/to/dais/dais_photos
- tfrecord_filename (string): The output name of your TFRecord files.