Metadata-Version: 2.1
Name: PyEmotion
Version: 1.0.0
Summary: A PyTorch library for detecting facial emotions
Home-page: UNKNOWN
Author: Karthick Nagarajan
Author-email: karthick965938@gmail.com
License: MIT
Description: # PyEmotion
        
        **[PyEmotion-Version 1.0.0](https://pypi.org/project/PyEmotion/)** - A Python package for Facial Emotion Recognition using PyTorch. PyEmotion is a python package which is helping to get the emotion of the person.
        
        
        [![python version](https://img.shields.io/badge/Python-3.6-yellow)](https://pypi.org/project/PyEmotion/)
        [![PyPI](https://img.shields.io/badge/pypi-v1.0.0-blue)](https://pypi.org/project/PyEmotion/)
        [![Downloads](https://pepy.tech/badge/pyemotion)](https://pepy.tech/project/pyemotion)
        [![Downloads](https://pepy.tech/badge/pyemotion/month)](https://pepy.tech/project/pyemotion/month)
        
        **Author**: Karthick Nagarajan
        
        **Email**: karthick965938@gmail.com
        
        ## Installation
        We can install ***PyEmotion*** package using this command
        
        ```sh
        pip install PyEmotion
        ```
        
        ## How to test?
        When you run python3 in the terminal, it will produce output like this:
        
        ```sh
        Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21) 
        [GCC 7.3.0] on linux
        Type "help", "copyright", "credits" or "license" for more information.
        >>> 
        ```
        
        Run the following code to you can get the Initialize process output for the PyEmotion package.
        
        ```sh
        >>> from PyEmotion import *
        >>> PyEmotion()
        ```
        ![package_sample_output](https://raw.githubusercontent.com/karthick965938/PyEmotion/master/assets/init.png?token=AD2U5DY7DKRVR6QIOOJDZ3S7IHEOS)
        
        ## Requirements
        ```sh
        pytorch >= 1.5.1
        torchvision >= 0.6.1
        ```
        
        
        ## Available Operations
        
        1) ***Webcam***  —  Result as a video
        ```sh
        from PyEmotion import *
        import cv2 as cv
        
        PyEmotion()
        er = DetectFace(device='cpu', gpu_id=0)
        
        # Open you default camera
        cap = cv.VideoCapture(0)
        
        while(True):
          ret, frame = cap.read()
          frame, emotion = er.predict_emotion(frame)
          cv.imshow('frame', frame)
          if cv.waitKey(1) & 0xFF == ord('q'):
            break
        cap.release()
        cv.destroyAllWindows()
        ```
        2) ***Image***  —  Result as a image
        ```sh
        from PyEmotion import *
        import cv2 as cv
        
        PyEmotion()
        er = DetectFace(device='cpu', gpu_id=0)
        
        # Open you default camera
        cap = cv.VideoCapture(0)
        ret, frame = cap.read()
        frame, emotion = er.predict_emotion(frame)
        cv.imshow('frame', frame)
        cv.waitKey(0)
        ```
        
        ## Arguments
        
        ```sh
        er = DetectFace(device='cpu', gpu_id=0)
        
        device = 'gpu' or cpu'
        
        gpu_id will be effective only when more than two GPUs are detected or it will through error.
        ```
        
        ## Contributing
        All issues and pull requests are welcome! To run the code locally, first, fork the repository and then run the following commands on your computer:
        
        ```sh
        git clone https://github.com/<your-username>/PyEmotion.git
        cd PyEmotion
        # Recommended creating a virtual environment before the next step
        pip3 install -r requirements.txt
        ```
        When adding code, be sure to write unit tests where necessary.
        
        ## Contact
        PyEmotion was created by [Karthick Nagarajan](https://stackoverflow.com/users/6295641/karthick-nagarajan?tab=profile). Feel free to reach out on [Twitter](https://twitter.com/Karthick965938) or through [Email!](karthick965938@gmail.com)
        
Keywords: image data datascience emotion PyEmotion expression ML ml machinelearning AI ai
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
