Read videos as numpy arrays
Project description
Reading videos into 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.
Getting started
How to simply read a video, given its path?
# 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, 1080, 3)
video = reader.read(video_path)
The tensor can be interpreted as -
1 video
Having 132 frames,
Dimension (width x height) of each frame: 1080x720 pixels
3 denotes that the video is RGB
View more examples here
Installation
Install Mydia from PyPI (recommended):
pip install mydia
Alternatively, install from Github source:
First, clone the repository.
git clone https://github.com/MrinalJain17/mydia.git
Then, build the module
cd mydia python setup.py install
Requirements
Python 3.x (preferably from the Anaconda Distribution)
The program uses ffmpeg-python, which provides python bindings for FFmpeg (used as the backend for reading and processing videos)
To install FFmpeg on your machine -
For Linux users:
$ sudo apt-get update $ sudo apt-get install libav-tools
For Windows or MAC/OSX users:
Download the required binaries from here. Extract the zip file and add the location of binaries to the PATH variable
Additional Libraries to install:
Install the following packages along with their dependencies:
tqdm - Required for displaying the progress bar.
Matplotlib - (Optional) For plotting the frames of a video
pip install ffmpeg-python numpy tqdm matplotlib
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