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https://github.com/supermoudy/b7b_el_cima

An application that converts black and white videos or images into colored and nice ones.
https://github.com/supermoudy/b7b_el_cima

asu-computer-vision b7b-el-cima black-and-white coloring-image coloring-video colorization computer-vision computer-vision-competition deep-learning image-processing video-processing

Last synced: 2 months ago
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An application that converts black and white videos or images into colored and nice ones.

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README 

        







# b7b_el_cima



## Content

* [Overview](#overview)



* [Specifications](#specifications)



* [Model Architecture](#model-architecture)



* [How to use?](#how-to-use)



* [Examples](#examples) 



* [Our Team](#our-team)



* [License](#license)



---

## Overview

Academic project of an application that converts black and white videos or images into colored and nice ones.

For more, check our [Project Proposal](B7b%20El-Cima.pdf) and [Video](https://www.youtube.com/watch?v=HuqR4sw75ko)



![before1](images/before1.jpg) | ![after1](images/after1.png)

-|-



---

## Specifications

A simple [website](http://127.0.0.1:5000) containing a colorization app for video or image



![](images/website.jpg)

- The front-end is in [HTML5](https://developer.mozilla.org/en-US/docs/Web/Guide/HTML/HTML5), [CSS3](https://developer.mozilla.org/en-US/docs/Web/CSS/CSS3), [Javascript](https://www.javascript.com/), [Ajax](http://api.jquery.com/jquery.ajax/) and [Bootstrap 4](https://getbootstrap.com/).



- The back-end is in [Python 3](https://www.python.org/download/releases/3.0/) using [Flask](http://flask.pocoo.org/) framework.



- Model Architectures are written using [Keras](https://keras.io/).



- The Core project is developed using [Tensorflow](https://www.tensorflow.org/) and [OpenCV](https://opencv.org/).



- Models Training is done using [Colab](https://colab.research.google.com)



- Development is OS independent.



---

## Model Architecture

- We learned 3 different architectures

you can find all details [here](Model_Arch.md).



- By comparing the initial results of them the one which gave the best result was U-Net so we continue training on it. 



- We trained it by 66k images from old colored movies. you can find the dataset [here](https://drive.google.com/file/d/1g6wtlkZVHAMKwucdRPqke37aBcQaImWw/view).



- The training took 2 days on colab to make 20 epochs with batch size 32.



---

## How to use?

### 1) Download this repo

- From GitHub: Clone or Download the repository or

- From Git:

    > git clone https://github.com/SuperMoudy/b7b_el_cima



### 2) Download the model

- Create a new folder in the repo and name it "models"

- In this folder(models), download the model from [here](https://drive.google.com/file/d/1biUjfEqCFgmNGzGXg8yTf9vsXTsLaB39/view)



### 3) Install dependencies

- Using command line:

    > pip install -r requirements.txt



### 4) To run the website

- Go to the project directory

- Go to Web App

- Run command line there and type:

    > python abbas.py



### 5) To colorize an Image:

- Include a url or upload an image then click Colorize:



    ![](images/how_to_use_image.jpg)



### 6) To colorize a Video:

- Upload a video then click Colorize:



    ![](images/how_to_use_video.jpg)



---

## Examples

### Image

![](images/Image_Example.png)



### Video

![](images/Video_Example.jpg)

---

## Our Team

- [Aladdin Mostafa](https://github.com/Aladdin95)

- [Mohamed Hussein](https://github.com/teamleader6)

- [Rawan Mahmoud](https://github.com/RawanMahmoud)

- [Mado Mohamed](https://github.com/MadoMohamed)

- [SuperMoudy](https://github.com/SuperMoudy)



---

## License