Metadata-Version: 2.1
Name: vidgear
Version: 0.1.3
Summary: A Lightweight Multi-Threaded OpenCV Video Processing Python Wrapper Library
Home-page: https://github.com/abhiTronix/vidgear
Author: abhiTronix
Author-email: abhi.una12@gmail.com
License: MIT License
Download-URL: https://github.com/abhiTronix/vidgear/tarball/0.1.3
Project-URL: Bug Reports, https://github.com/abhiTronix/vidgear/issues
Project-URL: Funding, https://paypal.me/AbhiTronix?locale.x=en_GB
Project-URL: Source, https://github.com/abhiTronix/vidgear
Description: <h1 align="center"><img alt="vidgear Logo" src="https://raw.githubusercontent.com/abhiTronix/Imbakup/master/Images/vidgear.png" width="50%" height="50%"></h1>
        
        [![PyPi version](https://pypip.in/v/vidgear/badge.png)](https://pypi.org/project/vidgear/)
        [![Last Commit](https://img.shields.io/github/last-commit/abhiTronix/vidgear.svg)](https://github.com/abhiTronix/vidgear/commits/master)
        [![Downloads](https://pepy.tech/badge/vidgear)](https://pepy.tech/project/vidgear)
        
        **VidGear** is a lightweight python wrapper around OpenCV [Video I/O module](https://docs.opencv.org/master/d0/da7/videoio_overview.html) that contains powerful multi-thread modules(gears) to enable high-speed video frames read functionality across various devices and platforms. It is a reworked implementation of [imutils](https://github.com/jrosebr1/imutils) library's video modules with all major bugs fixed and comes with addition features like direct network streaming(*GStreamer Pipeline supported*) and flexible direct source parameters/attributes manipulation of OpenCV's [VideoCapture Class properties](https://docs.opencv.org/master/d4/d15/group__videoio__flags__base.html#gaeb8dd9c89c10a5c63c139bf7c4f5704d) on the go. This library is also very well compatible with Raspberry Pi Camera module's [Picamera library](http://picamera.readthedocs.io/) and provides us the ability exploit its various features like `brightness, saturation, sensor_mode` etc. easily. This library supports *Python 2.7 and all above versions.*
        
        ## Features:
        Key features which differentiates it from the other existing multi-threaded open source solutions:
        - [x]  Multi-Threaded high-speed OpenCV video-frame capturing(resulting in High FPS)
        - [x]  Flexible Direct control over the video stream
        - [x]  Lightweight
        - [x]  Built-in Robust Error and frame synchronization Handling
        - [x]  Multi-Platform compatibility
        - [x]  Full Support for Network Video Streams(*Including Gstreamer Raw Video Capture Pipeline*) 
        
        ## Prerequisites
        * **Critical:** VidGear must require `OpenCV`(*with contrib*) library to be installed on your machine which is critical for its core algorithm functioning. You can build it from from [scratch](https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv/) ([Raspberry Pi](https://www.pyimagesearch.com/2018/09/26/install-opencv-4-on-your-raspberry-pi/)) or install it from PyPi as follows(*Latest versions recommended*):
          ```
          pip install opencv-python
          pip install opencv-contrib-python
          ```
        * **Additional:** If you are using Raspberry Pi Camera Modules such as *OmniVision OV5647 Camera Module* and *Sony IMX219 Camera Module*. It requires additional [Picamera](https://picamera.readthedocs.io/en/release-1.13/install.html) library installation on your Raspberry Pi machine prior to its installation (*Latest versions recommended*). You can install it from PyPi easily as follows:
          ```
          pip install picamera
          ```
          ***Also, make sure to [enable Raspberry Pi hardware specific settings](https://picamera.readthedocs.io/en/release-1.13/quickstart.html) prior using this library.***
        
        ## Installation
        - **From PyPI(Stable Only):** `VidGear` can be easily installed as follows(*available on [Python Package Index (PyPI)](https://pypi.org/project/vidgear/)*):
          ```bash
          sudo pip install vidgear
          ```
        - **Clone this repository(Latest But experimental):** You can also directly clone this repo. for latest patches(*maybe experimental*) and development purposes and thereby can install as follows:
          ```bash
          git clone https://github.com/abhiTronix/vidgear.git
          cd vidgear
          sudo pip install .
          ```
        - **Conda Install:**  Anaconda prefers to use its own `conda package manager`, but it’s also possible to install packages using `pip` as follows:
           ```bash
           pip install vidgear
           ```
        
        ## Documentation and Usage
        
        <h3 align="center">You can checkout VidGear detailed <a href = https://github.com/abhiTronix/vidgear/wiki>Wiki-Section</a> for detailed documentation with examples for each Class(Gear).</h3>
        
        ### Basic example: 
        
        The basic example of VideoGear Class for webcam stream is as follows :
        
        ```python
        # import required libraries
        from vidgear.gears import VideoGear
        import cv2
        
        stream = VideoGear(source=0).start() 
        # define various attributes and start the stream
        
        # infinite loop
        while True:
        	
        	frame = stream.read()
        	# read frames
        
        	# check if frame is None
        	if frame is None:
        		#if True break the infinite loop
        		break
        	
        	# do something with frame here
        	
        	cv2.imshow("Output Frame", frame)
        	# Show output window
        
        	key = cv2.waitKey(1) & 0xFF
        	# check for 'q' key-press
        	if key == ord("q"):
        		#if 'q' key-pressed exit loop
        		break
        
        cv2.destroyAllWindows()
        # close output window
        
        stream.stop()
        # safely close video stream.
        ```
        
        
        ## Contribution and Development
        You are welcome to contribute with suggestions, feature requests and [pull requests](https://github.com/abhiTronix/vidgear/pulls).
        
        ## Author
        
        - Abhishek Thakur [@abhiTronix](https://github.com/abhiTronix)
        
        ## License
        
        Copyright © 2019 Abhitronix
        
        This project is under the MIT License. See the LICENSE file for the full license text.
        
Keywords: computer vision,multi-thread,opencv,opencv2,opencv4,picamera
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=2.7
Description-Content-Type: text/markdown
