The objective of the program given is to detect object of interest(Car) in video frames and to keep tracking the same object. This is an example of how to detect vehicles in Python.
Why Vehicle Detection?
- The startling losses both in human lives and finance caused by vehicle accidents.
- Detecting vehicles in images acquired from a moving platform is a challenging problem.
Steps to download the requirements below:
- Download Python 2.7.x version, numpy and OpenCV 2.4.x version.Check if your Windows either 32 bit or 64 bit is compatible and install accordingly.
sudo apt-get install python pip install numpy
- install OpenCV from here
- Make sure that numpy is running in your python then try to install opencv.
- Put the cars.xml file in the same folder. Save this as .xml file.
- Download this video from here as input
- Opencv Python program for Face Detection
- Python Program to detect the edges of an image using OpenCV | Sobel edge detection method
- Real-Time Edge Detection using OpenCV in Python | Canny edge detection method
- Python | Corner Detection with Shi-Tomasi Corner Detection Method using OpenCV
- Python | Corner detection with Harris Corner Detection method using OpenCV
- OpenCV C++ Program for Face Detection
- OpenCV C++ Program for coin detection
- Python | Smile detection using OpenCV
- Circle Detection using OpenCV | Python
- Face Detection using Python and OpenCV with webcam
- Detection of a specific color(blue here) using OpenCV with Python
- Line detection in python with OpenCV | Houghline method
- OpenCV C++ Program to blur a Video
- OpenCV C++ Program to play a video
- Python | Play a video using OpenCV
This article is contributed by Afzal Ansari. 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 write comments if you find anything incorrect, or you want to share more information about the topic discussed above.