Metadata-Version: 2.1
Name: mydia
Version: 2.2.1
Summary: A simple and efficient wrapper for reading videos as NumPy tensors.
Home-page: https://github.com/MrinalJain17/mydia
Author: Mrinal Jain
Author-email: mrinaljain007@gmail.com
License: MIT
Project-URL: Documentation, https://mrinaljain17.github.io/mydia/
Project-URL: Source, https://github.com/MrinalJain17/mydia
Description: 
        # Mydia
        [![Build Status](https://travis-ci.org/MrinalJain17/mydia.svg?branch=master)](https://travis-ci.org/MrinalJain17/mydia)
        ![Code Style](https://img.shields.io/badge/code%20style-black-black.svg)
        ![Platform](https://img.shields.io/badge/Platforms-linux--64,osx--64,win--64-orange.svg)
        
        Reading videos as NumPy arrays was never more simple. This library provides an 
        entire range of additional functionalities such as custom frame selection, frame 
        resizing, pixel normalization, grayscale conversion and much more.
        
        [**READ THE DOCUMENTATION**](https://mrinaljain17.github.io/mydia)
        
        ## Getting started
        
        #### 1. Read a video, given its path
        
        ```python
        
        # Import
        from mydia import Videos
        
        # Initialize video path
        video_path = r".docs/examples/sample_video/bigbuckbunny.mp4"
        
        # Create a reader object
        reader = Videos()
        
        # Call the 'read()' function to get the video tensor
        # which will be of shape (1, 132, 720, 1280, 3)
        video = reader.read(video_path)
        
        ```
        
        The tensor can be interpreted as:
        
        - 1 video
        - Having 132 frames, 
        - Dimension (width x height) of each frame: 1280x720 pixels
        - `3` denotes that the video is in RGB format
        
        #### 2. You can even use multiple workers for reading the videos in parallel
        
        ```python
        
        from mydia import Videos
        
        video_paths = [
            "path/to/video_1", 
            "path/to/video_2", 
            "path/to/video_3",
            ...,
        ]
        
        reader = Videos()
        video = reader.read(video_path, workers=4)
        
        ```
        
        #### 3. View detailed examples [here](https://mrinaljain17.github.io/mydia/auto_examples/)
        
        ## Requirements
        
        - `Python 3.x` (preferably from the [Anaconda Distribution](https://www.anaconda.com/download/))
        
        - [`FFmpeg`](https://www.ffmpeg.org/): The backend for reading and processing 
          the videos.
        
          **The recommended (and probably the easiest) way of installing `FFmpeg` is 
          via the conda package manager.**
        
          ```bash
              conda install -c mrinaljain17 ffmpeg
          ```
        
          However, if you are not using *conda*, then
          
          For **Linux** users - 
          
          ```bash
              $ sudo apt-get update
              $ sudo apt-get install ffmpeg
          ```
          
          For **Windows or MAC/OSX** users - 
          
          Download the required binaries from [here](https://www.ffmpeg.org/download.html). 
          Extract the zip file and add the location of binaries to the `PATH` variable.
        
        ## Installation
        
        1. **Using the conda package manager (recommended):**
        
            ```bash
                conda install -c mrinaljain17 mydia
            ```
        
        2. **Using pip:**
        
            ```bash
                pip install mydia
            ```
        
        The following python packages that `mydia` depends on, will also be 
        installed, along with their dependencies.
        
        - [ffmpeg-python](https://github.com/kkroening/ffmpeg-python)
        - [Numpy](http://www.numpy.org/)
        - [tqdm](https://pypi.python.org/pypi/tqdm#installation) - Required for 
          displaying the progress bar.
        
        ## License
        
        Copyright 2018 [Mrinal Jain](https://mrinaljain17.github.io/).
        
        Released under the [MIT License](https://mrinaljain17.github.io/license/).
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Multimedia :: Video :: Capture
Description-Content-Type: text/markdown
