OpenCV (Open Source Computer Vision) is a computer vision library that contains various functions to perform operations on Images or videos.
OpenCV's application areas include : 1) Facial recognition system 2) motion tracking 3) Artificial neural network 4) Deep neural network 5) video streaming etc.
In Python, one can use an OpenCV library named
CV2. Python does not come with cv2, so user needs to install it separately.
For Windows :pip install opencv-python
For Linux :
sudo apt-get install python-opencv
OpenCv library can be used to perform multiple operations on videos. Let’s try to do something interesting using
CV2. Take a video as input and play it in a reverse mode by breaking the video into frame by frame and simultaneously store that frame in the list. After getting list of frames we perform iteration over the frames. For playing video in reverse mode, we need only to iterate reverse in the list of frames. Use reverse method of the list for reversing the order of frames in the list.
Below is the implementation :
- Python | Play a video using OpenCV
- OpenCV C++ Program to play a video
- Python | Create video using multiple images using OpenCV
- OpenCV Python program for Vehicle detection in a Video frame
- OpenCV C++ Program to blur a Video
- Saving Operated Video from a webcam using OpenCV
- Python | Pandas dataframe.mode()
- Python statistics | mode function
- Python | Pandas Series.mode()
- Finding Mean, Median, Mode in Python without libraries
- scipy stats.mode() function | Python
- Python | Image blurring using OpenCV
- Template matching using OpenCV in Python
- Reading an image in OpenCV using Python
- Python | Grayscaling of Images using OpenCV
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to email@example.com. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.