PIMMI : Python IMage MIning

Library allowing visual search in a corpus of images, from Twitter... or elsewhere.

SIFT interest points, clustering, based on OpenCV and Faiss, multithreaded.

Very preliminary stuff for now.

Install with pyenv and pip

pyenv virtualenv 3.7.0 pimmi-env
pyenv activate pimmi-env
pip install -U pip
pip install pimmi

Demo

# Install dependencies
pip install -r requirements.txt

# --- Play with a very small dataset
# Create a default index structure and fill it with the demo dataset  
python3 index_dataset.py --action fill --thread 16 --index "IVF1024,Flat" --save_faiss index/small_dataset.ivf1024 --images_dir demo_dataset/small_dataset

# Query the same dataset on this index
python3 query_dataset.py --simple --thread 16 --load_faiss index/small_dataset.ivf1024 --save_mining index/small_dataset.ivf1024.mining --images_mining --images_root demo_dataset/dataset1


# --- Play with the demo dataset 1
python3 index_dataset.py --action fill --thread 16 --index "IVF1024,Flat" --save_faiss index/dataset1.ivf1024 --images_dir demo_dataset/dataset1
python3 query_dataset.py --thread 16 --load_faiss index/dataset1.ivf1024 --save_mining index/dataset1.ivf1024.mining --images_mining --images_root demo_dataset/dataset1

# Post process the mining results in order to visualize them
python3 fuse_query_results.py
python3 generate_cluster_viz.py

Happy hacking !