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Indian-Paper-Currency-Classification

(★ 147)

Source code of Indian Paper Currency Classification :fire:

파일 탐색기

최종 버전 다운로드 (.zip)

- - .DS_Store
  - model.h5
- - __init__.py
- - __init__.py
  - base.html
  - consent.html
  - footer.html
  - index.html
- .DS_Store
- __init__.py
- main.py
- __init__.py
- __init__.py
.DS_Store
.gitignore
LICENSE
README.md
requirements.txt
runtime.txt
wsgi.py

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/rowhitswami/Indian-Paper-Currency-Classification

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd Indian-Paper-Currency-Classification

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Python

쉬움 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

pip install -r requirements.txt

requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

// repository documentation

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# Indian Paper Curreny Classification :india:

## Table of Content
  * [Demo](#demo)
  * [Overview](#overview)
  * [Motivation](#motivation)
  * [Technical Aspect](#technical-aspect)
  * [Installation](#installation)
  * [Run](#run)
  * [Deployement on Heroku](#deployement-on-heroku)
  * [Directory Tree](#directory-tree)
  * [To Do](#to-do)
  * [Bug / Feature Request](#bug---feature-request)
  * [Technologies Used](#technologies-used)
  * [Team](#team)
  * [License](#license)
  * [Credits](#credits)

## Demo
Link: [https://ipcc.rohitswami.com](https://ipcc.rohitswami.com)

[![](https://i.imgur.com/5gj4USj.png)](https://ipcc.rohitswami.com)

## Overview
This is a simple image classification Flask app trained on the top of Keras API. The trained model (`app/model/model.h5`) takes an image (Indian Paper Currency) as an input and classification the class of image from __10, 20, 50, 100, 200, 500, 2000__ denomination.

## Motivation
What could be a perfect way to utilize unfortunate lockdown period? Like most of you, I spend my time in cooking, Netflix, coding and reading some latest research papers on weekends. The idea of classifying indian currency struck to me when I was browsing through some research papers. I couldn't find any relevant research paper (and of course dataset!) associated with it. And that led me to collect the images of Indian currency to train a deep learning model using [this](https://github.com/hardikvasa/google-images-download) amazing tool.

## Technical Aspect
This project is divided into two part:
1. Training a deep learning model using Keras. (_Not covered in this repo. I'll update the link here once I make it public._)
2. Building and hosting a Flask web app on Heroku.
    - A user can choose image from a device or capture it using a pre-built camera.
    - Used __Amazon S3 Bucket__ to store the uploaded image and classification.
    - Used __CSRF Token__ to protect against CSRF attacks.
    - Used __Sentry__ to catch the exception on the back-end.
    - After uploading the image, the classifications are displayed on a __Bar Chart__.

## Installation
The Code is written in Python 3.7. If you don't have Python installed you can find it [here](https://www.python.org/downloads/). If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after [cloning](https://www.howtogeek.com/451360/how-to-clone-a-github-repository/) the repository:
```bash
pip install -r requirements.txt
```

## Run
> STEP 1
#### Linux and macOS User
Open `.bashrc` or `.zshrc` file and add the following credentials:
```bash
export AWS_ACCESS_KEY="your_aws_access_key"
export AWS_SECRET_KEY="your_aws_secret_key"
export ICP_BUCKET='your_aws_bucket_name'
export ICP_BUCKET_REGION='bucket_region'
export ICP_UPLOAD_DIR='bucket_path_to_save_images'
export ICP_PRED_DIR='bucket_path_to_save_classification'
export ICP_FLASK_SECRET_KEY='anything_random_but_unique'
export SENTRY_INIT='URL_given_by_sentry'
```
Note: __SENTRY_INIT__ is optional, only if you want to catch exceptions in the app, else comment/remove the dependencies and code associated with sentry in `app/main.py`

#### Windows User
Since, I don't have a system with Windows OS, here I collected some helpful resource on adding User Environment Variables in Windows.

__Attention__: Please perform the steps given in these tutorials at your own risk. Please don't mess up with the System Variables. It can potentially damage your PC. __You should know what you're doing__. 
- https://www.tenforums.com/tutorials/121855-edit-user-system-environment-variables-windows.html
- https://www.onmsft.com/how-to/how-to-set-an-environment-variable-in-windows-10

> STEP 2

To run the app in a local machine, shoot this command in the project directory:
```bash
gunicorn wsgi:app
```

## Deployement on Heroku
Set the environment variable on Heroku as mentioned in _STEP 1_ in the __Run__ section. [[Reference](https://devcenter.heroku.com/articles/config-vars)]

![](https://i.imgur.com/TmSNhYG.png)

Our next step would be to follow the instruction given on [Heroku Documentation](https://devcenter.heroku.com/articles/getting-started-with-python) to deploy a web app.

## Directory Tree 
```
├── app 
│   ├── __init__.py
│   ├── main.py
│   ├── model
│   ├── static
│   └── templates
├── config
│   ├── __init__.py
├── processing
│   ├── __init__.py
├── requirements.txt
├── runtime.txt
├── LICENSE
├── Procfile
├── README.md
└── wsgi.py
```

## To Do
1. Convert the app to run without any internet connection, i.e. __PWA__.
2. Add a better vizualization chart to display the classification.

## Bug / Feature Request
If you find a bug (the website couldn't handle the query and / or gave undesired results), kindly open an issue [here](https://github.com/rowhitswami/Indian-Paper-Currency-Classification/issues/new) by including your search query and the expected result.

If you'd like to request a new function, feel free to do so by opening an issue [here](https://github.com/rowhitswami/Indian-Paper-Currency-Classification/issues/new). Please include sample queries and their corresponding results.

## Technologies Used

![](https://forthebadge.com/images/badges/made-with-python.svg)

[<img target="_blank" src="https://keras.io/img/logo.png" width=200>](https://keras.io/) [<img target="_blank" src="https://flask.palletsprojects.com/en/1.1.x/_images/flask-logo.png" width=170>](https://flask.palletsprojects.com/en/1.1.x/) [<img target="_blank" src="https://number1.co.za/wp-content/uploads/2017/10/gunicorn_logo-300x85.png" width=280>](https://gunicorn.org) [<img target="_blank" src="https://www.kindpng.com/picc/b/301/3012484.png" width=200>](https://aws.amazon.com/s3/)

[<img target="_blank" src="https://sentry-brand.storage.googleapis.com/sentry-logo-black.png" width=270>](https://www.sentry.io/) [<img target="_blank" src="https://openjsf.org/wp-content/uploads/sites/84/2019/10/jquery-logo-vertical_large_square.png" width=100>](https://jquery.com/)

## Team
[![Rohit Swami](https://avatars1.githubusercontent.com/u/16516296?v=3&s=144)](https://rohitswami.com/) |
-|
[Rohit Swami](https://rohitswami.com/) |)

## License
[![Apache license](https://img.shields.io/badge/license-apache-blue?style=for-the-badge&logo=appveyor)](http://www.apache.org/licenses/LICENSE-2.0e)

Copyright 2020 Rohit Swami

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

## Credits
- [Google Images Download](https://github.com/hardikvasa/google-images-download) - This project wouldn't have been possible without this tool. It saved my enormous amount of time while collecting the data. A huge shout-out to its creator [Hardik Vasa](https://github.com/hardikvasa).