dkafetzis/deep-learning-landmark-classification

deep-learning-landmark-classification

Environment setup

1. Install conda.
2. Install requirements.txt conda create --name dl-env --file ./requirements.txt.
3. Depending on environment cuda might or might not be needed consult this page and install torch and friends accordingly.
4. Create an empty checkpoints directory if it does not exist already
5. Download the dataset
   • International dataset
   • Greek dataset
6. Rename the dataset file to landmark_images if necessary.

Training the models

The models can be trained from the 2 notebooks provided:

• custom_cnn.ipynb for out custom cnn model
• transfer_learning.ipynb for the 3 transfer learning models

Running the notebook trains the corresponding model saving the best performing checkpoint each time and in the end of the training it wraps the model with a predicting wrapper to change the output of the model from percentages to a single prediction, runs a confusion matrix and saves the model with the wrapper.

Android application

The trained models are used in the SpotTheSpot application