The objective of the program given is to detect object of interest(face) in real time and to keep tracking of the same object.This is a simple example of how to detect face in Python. You can try to use training samples of any other object of your choice to be detected by training the classifier on required objects.
Here is the steps to download the requirements below.
- Download Python 2.7.x version, numpy and Opencv 2.7.x version.Check if your Windows either 32 bit or 64 bit is compatible and install accordingly.
- Make sure that numpy is running in your python then try to install opencv.
- Put the haarcascade_eye.xml & haarcascade_frontalface_default.xml files in the same folder(links given in below code).
Next Article: Opencv C++ Program for face detection
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.
- OpenCV C++ Program for Face Detection
- Face Detection using Python and OpenCV with webcam
- OpenCV Python program for Vehicle detection in a Video frame
- 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 coin detection
- Python | Smile detection using OpenCV
- Line detection in python with OpenCV | Houghline method
- Detection of a specific color(blue here) using OpenCV with Python
- Image Processing in Java | Set 9 ( Face Detection )
- Python | Program to extract frames using OpenCV
- OpenCV Python Program to blur an image
- OpenCV Python Program to analyze an image using Histogram