This repository provides instructions and code for setting up a Skin Cancer Image Semantic Search engine leveraging VMware Greenplum as Vector Database.
Follow these steps to set up the Skin Image Search System on your local machine.
- Greenplum Database
- pgvector extension
- Jupyter Notebook
- Python dependencies (requirements.txt)
-
Run the
script.sql
file to create tables for storing images, metadata and embeddings in your Greenplum database:$ psql -U your_username -d your_database -a -f script.sql
-
Install the required Python packages listed in
requirements.txt
.$ pip install -r requirements.txt
- Use the
Skin_Cancer_Image_Semantic_Search.ipynb
Notebook to download the dataset and generate embeddings into Greenplum.
-
Run the Streamlit App using:
$ streamlit run app.py
-
Access the web application by opening a web browser and navigating to:
http://localhost:8501