/Image-Feature-Extraction-Using-GenAI

This project implements an advanced generative AI pipeline for extracting and rating features from images. It combines the power of Florence-2, a state-of-the-art vision-language model, with a fine-tuned version of Mistral-v3, a cutting-edge large language model.

Primary LanguageJupyter Notebook

Image-Feature-Extraction-Using-GenAI

This project implements an advanced generative AI pipeline for extracting and rating features from images. It combines the power of Florence-2, a state-of-the-art vision-language model, with a fine-tuned version of Mistral-v3, a cutting-edge large language model.

Key Features

  • Utilizes Florence-2 to generate detailed image descriptions
  • Employs a custom fine-tuned Mistral-v3 model for feature extraction and scoring
  • Outputs results in JSON format for easy integration with other applications

Image Description Generation

  • Model: Florence-2
  • Input: Raw image data
  • Output: Comprehensive text description of the image

Feature Extraction and Rating

  • Model: Fine-tuned Mistral-v3
  • Input: Text description from Florence-2
  • Output: JSON object containing extracted features and their scores

Usage

To run this project, follow these steps:

  1. Download the dataset
  2. Run the image scraping script:
python scrapeImages.py

This will scrape images from Airbnb based on the dataset.

  1. Open and run the GenAI_Approach.ipynb Jupyter notebook. Follow the instructions within the notebook to process the images and extract features.

Important note: Ensure you use the same file and directory names as specified in the scripts, or modify the paths in the code to match your directory structure.