• B.Tech. Final year project on Face Similarity Detection AI using Siamese Networks.
• The project is built using TensorFlow and Keras.
• The model is trained on the Extracted Faces dataset from the face-recognition-dataset.
• The model uses Triplet Loss to minimize the distance between the anchor and positive images and maximize the distance between the anchor and negative images.
• Model is exported as "H5" and wrapped in a Fast API.
• The API is to be deployed on AWS as a containerized service, using Docker.
• A React Frontend is built to interact with the API.

• backend: Contains the model and API. ( Tech Stack: FastAPI, TensorFlow, Keras, Pillow, AWS )
• frontend: Contains the React Frontend. ( Tech Stack: React, Axios, TailwindCSS )

• Install the required packages using pip install -r requirements.txt.

• Run the API using uvicorn main:app --reload.

• Working

• Sample 1:

• Sample 2:

• Install the required packages using npm install.
• Run the frontend using npm start.

• The model takes 3 input images, (anchor, image-1, image-2) and gives a distance value that indicates which of these 2 images are similar or dissimilar to the anchor image.
• Sample UI for the project:

Prakhar Tandon, Vaibhav Shankhwar, Abhishek Agrahri and Mansi Purwar.
Final B.Tech. Computer Science & Engineering.
Under Guidance of Dr. Vivek Verma, Professor, CSE Dept, HBTU Kanpur.