Image Similarity Comparison Web Application
This project is a web-based application that allows users to upload images and compare them to find the most visually similar ones based on a user-defined similarity threshold. The application utilizes a pre-trained VGG16 model to extract features from images and measures similarity using cosine similarity.
Features
- Upload an input image and a set of comparison images.
- Define a similarity threshold to control the sensitivity of the comparison.
- Automatically identify and display the most similar images.
- Option to retry with different images or threshold settings.
- User-friendly interface with an impressive, creative design.
Technologies Used
- Backend: Python, Flask, TensorFlow, VGG16, scikit-learn
- Frontend: HTML, CSS, Bootstrap
- Image Processing: PIL, NumPy
Usage
- Upload Images: On the homepage, upload your primary image and a set of comparison images.
- Set Similarity Threshold: Input the similarity threshold value at the start.
- View Results: The application will process the images and display the ones that are most similar to the primary image.
- Try Again: After viewing the results, you have the option to try with different images.
Practical Applications
- E-commerce: Helps in recommending visually similar products to users.
- Digital Asset Management: Assists in organizing and finding similar visual content from a large collection.
- Creative Industry: Useful for artists and designers to find similar visual references.
WebApp
