Wait forrrr ittt....

Searching by text. Query text: video games

Searching by image.

git clone https://github.com/k-zehnder/jina-clip-streamlit

cd jina-clip-streamlit

pip install -r requirements.txt

https://www.fer.unizg.hr/_download/repository/tattoo_images.zip

When you go to the link above it should begin downloading the tattoo image dataset. Its about 1500 images. Create a folder in the root directory called "data", and then inside the data folder make another folder called "tattoo_images". Dump the images you downloaded into the "tattoo_images" folder that you made inside the "data" folder. Use the directory structure below to help keep you oriented.

.
├── data
│   └── tattoo_images
├── docs
│   └── usage
├── frontend
│   ├── __pycache__
│   ├── config.py
│   ├── frontend.py
│   ├── helpers.py
│   └── widgets.py
├── image_searcher
│   ├── app.py
│   └── config.py
├── indexer
│   ├── __pycache__
│   ├── app.py
│   └── helpers.py
├── text_searcher
│   ├── app.py
│   └── config.py
├── workspace # 'workspace' directory will be created automatically when you index so don't worry about this to start. It will be created when you index.
│   └── PQLiteIndexer
├── README.md
├── dataset_instructions.txt
├── post.txt
├── requirements.txt
└── website.txt

This will create embeddings for all images using CLIPImageEncoder, and then store them on disk (with metadata) with PQLiteIndexer.

Open a new terminal window/tab, and run from same root directory.

1. python indexer/app.py to index data

Open a new terminal window/tab, run from same root directory.

1. python text_searcher/app.py to start the text search server

Open a new terminal window/tab, run from same root directory.

1. python image_searcher/app.py to start the image search server

Open a new terminal window/tab, run from same root directory.

1. streamlit run frontend/frontend.py to start frontend