Image Feature Extraction Using GenAI

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.

3. 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.