semvec/pypi-packages huggingface dataset:
app-ocr 1.2.14
E-kyc for Industries application
License: MIT
Requires Python: >=3.9

# EKYC (OCR&FaceID) API 
<!-- [![My Skills](https://skills.thijs.gg/icons?i=python&theme=light)](https://skills.thijs.gg) -->
EKYC (OCR&FaceID) API is an API developed to provide Optical Character Recognition (OCR) and Face ID functionalities. The API supports the scanning of national ID cards, motorbike registration certificates, and EVN bills. It utilizes Makesense AI for labeling data, Yolov5 for text detection, and VietOCR for text recognition.

In addition to OCR, the API also provides Face ID functionality, including face detection, face recognition, and quality checks. It utilizes SCRFD for face detection, ArcFace for face recognition, and provides face liveness detection, face quality assessment, face mask detection, and closed eyes detection.

# Scanning Card Type 🚀

+ Type Support 
  + National ID card
  + MRC (Motorbike Registation Certificate) 
  + Passport
+ OCR Techniques: 
  + Makesense AI for labeling data
  + Yolov5 for Text Detection task 
  + VietOCR for Text Recognition task
# Face ID 🚀 

+ Face Detection & Face Recognition
  + SCRFD (Sample and Computation Redistribution for Efficient) for Face Detection
  + ArcFace (From InsightFace project with high accuracy in Face Recognition)
  + Check Quality techniques:
    + Face Liveness Detection 
    + Face Quality Assessment
    + Face Mask Detection 
    + Closed Eyes Detection 

# How to install
Install Python version: 3.8.10
Clone the project and create virtual enviroment by running these lines in terminal:
``
python -m venv venv
``

``
venv\Scripts\activate
``

Install requirements by running this line in terminal
``
pip install -r requirements.txt
``

If you are using windows run this to install dlib package
``
pip install 'app\config\dlib-19.19.0-cp38-cp38-win_amd64.whl'  
``
# How to use 🏆

+ For running API in Dev Environment :

``
  uvicorn just_scan_api:app --reload
``
and run on 
``
http://127.0.0.1:8000/docs
``

+ You have to convert your image from array -> base64 by using image to base64 (ex: https://codebeautify.org/image-to-base64-converter) and then paste your base64 string into input API for running
dict2xlsx 0.0.1
Python Package to convert dict to xlsx
License: MIT
Keywords: excel,dict-to-xlsx,convert,dict2xlsx

# Dict2XLSX

Dict2XLSX is a Python package that allows you to convert a dictionary into an XLSX (Excel) file.


## Introduction

- [Installation](#installation)
- [Features](#features)
- [Usage](#usage)
- [Dependencies](#dependencies)
- [Contributing](#contributing)

<br />

## Installation


You can install Dict2XLSX using pip:

```shell
pip install dict2xlsx
```

## Features

* `Dictionary to XLSX Conversion`: Convert a dictionary into an XLSX file with ease.
* `Columnar Organization`: Automatically organizes dictionary * key-value pairs into separate columns in the XLSX file.
* `Data Integrity`: Maintains the order of keys and values from the original dictionary during the conversion process.
* `Simple Integration`: Easy-to-use API allows for seamless integration into existing Python projects.
* `Customization Options`: Customize the output file name, sheet name, and formatting options.

## Usage

```python
from dict2xlsx import Dict2XLSX

data = [
    {'first_name': 'Satyam', 'last_name': 'Lohiya', 'age': '21'},
    {'first_name': 'Shivam', 'age': '28'},
    {'first_name': 'Rahul', 'last_name': 'Sharma'},
]


xlsx_obj = Dict2XLSX(data)
xlsx_obj.save('output.xlsx')
```

![Screenshot 2023-06-20 144745](https://github.com/Satyam-2001/Dumb-Charades/assets/88069082/17c85e71-4a32-44f5-8071-b3bfba06a41e)

## Dependencies

Dict2XLSX has the following dependencies:

* openpyxl: A Python library for reading and writing Excel (XLSX) files.

## Contributing

Contributions are welcome! If you encounter any issues or have suggestions for improvements, please open an issue on the GitHub repository.

To contribute to Dict2XLSX, follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Implement your changes.
4. Write tests to ensure the correctness of your code (if applicable).
5. Run the test suite to make sure all tests pass.
6. Submit a pull request.