Image search based on convolutional neural network feature extraction.
Download the dataset and extract it:
wget -c http://data.csail.mit.edu/places/places365/train_256_places365standard.tar
tar -xf train_256_places365standard.tar
Run to split the dataset into training and testing parts:
./train_test_split.sh
To train with hard mining (web api available):
python3 resnet.py
After the model is trained and saved, you can run the sample website: FLASK_APP=web_pova.py flask run
To train without hard mining (web api not available):
python3 model_noHardMin.py
To evaluate the saved trained model run:
python3 eval_results.py
Requirements: Keras, tensorflow, [Flask - for web api]
Authors:
- Tomáš Sýkora (tms.sykora@gmail.com)
- Josef Jon (xjonjo00@stud.fit.vutbr.cz)