Image Colorization Using Deep Learning

Colorize any black and white image using deep learning

Project Description 

This project focuses on developing a web-based application for automatic image colorization using deep learning techniques. A Convolutional Neural Network (CNN) is trained to convert grayscale images into realistic color images by learning spatial and semantic features from training data. The trained model is deployed using a Flask backend, and users can upload black-and-white images through a simple web interface to receive colorized outputs in real time. 

Features 

• Automatic grayscale to color image conversion

• CNN-based deep learning model trained using PyTorch

• Web-based interface for easy image upload and preview

• Real-time model inference via Flask REST APIs

• Downloadable colorized output images

• Suitable for final-year and deep learning projects

Tech Stack

• Python

• PyTorch(Deep Learning)

• Flask (Backend Framework)

• HTML, CSS, JavaScript (Frontend)

• Other supporting Python libraries

System Requirements

• Python 3.10+

• Anaconda

• No GPU is required

Deliverables 

• Project Code

• Setup over video call 

• WhatsApp support