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https://github.com/tharuneshwar-369/ai-image-colorization

The Flask-Python web app utilizes a pre-trained image colorization model based on Caffe. It allows users to upload black and white images and applies the colorization model to automatically generate colored versions. The app leverages the power of deep learning to provide an intuitive and interactive way to add color to grayscale images with ease.
https://github.com/tharuneshwar-369/ai-image-colorization

black-and-white-image caffemodel deep-learning flask html-css-javascript-jquery image-colorization pretrained-models python python-flask-website

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The Flask-Python web app utilizes a pre-trained image colorization model based on Caffe. It allows users to upload black and white images and applies the colorization model to automatically generate colored versions. The app leverages the power of deep learning to provide an intuitive and interactive way to add color to grayscale images with ease.

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# Ai-image-colorization
[![Maintenance](https://img.shields.io/badge/python-3.9-blue.svg)](https://www.python.org/downloads/release/python-390/)
[![Maintenance](https://img.shields.io/badge/framework-flask-red.svg)](https://flask.palletsprojects.com/en/2.0.x/)
[![Maintenance](https://img.shields.io/badge/Frontend-HTML/CSS-green.svg)](https://img.shields.io/badge/Frontend-HTML/CSS/JS-green.svg)
[![Maintenance](https://img.shields.io/badge/Backend-Javascript/JQuery-yellow.svg)](https://img.shields.io/badge/Backend-Javascript-yellow.svg)
[![Maintenance](https://img.shields.io/badge/AI-Deep_learning-blue.svg)](https://img.shields.io/badge/Backend-JD-yellow.svg)

Black & white image colorization using Deep Learning using (Pretrained Model)

> Check out Live Demo: https://bw-image-color.onrender.com

## Example Images

# How to run the App
> 1. ```$ git clone https://github.com/THARUNESHWAR-369/Ai-image-colorization.git```
> 2. ```$ cd Ai-image-colorization```
> 4. ```$ pip3 install -r requirements.txt```
> 5. ```$ python app.py```
> 6. Go to your browser and type http://127.0.0.1:5000/ in the address bar. Hurray! That's it.