This Python script uses OpenCV to detect faces in an image using Haar cascades.
- Python 3.x
- OpenCV
To install OpenCV, you can use the following command:
To use the script, simply run it with the path to the image file and the name of the Haar cascade file as arguments:
python detect_image.py <image_path> <haar_cascade_name>
python detect_image.py PhotoExample\Example.jpg haarcascade_frontalface_default
The script will display the image with rectangles drawn around the detected faces.
The main function in the script is detect_image(), which takes two arguments: the path to the image file and the name of the Haar cascade file.
The script first creates a cv2.CascadeClassifier object using the Haar cascade file. It then reads the image file and converts it to grayscale.
The detectMultiScale() function is called on the grayscale image to detect faces. The function returns a list of rectangles that enclose the detected faces.
The script then draws rectangles around the detected faces using the cv2.rectangle() function.
Finally, the image is displayed using the cv2.imshow() function.
The script uses Haar cascades to detect faces. Haar cascades are a type of machine learning algorithm that can be trained to recognize specific features in images.
The script includes a Haar cascade file for detecting frontal faces, which is located in the HaarCascadeFiles directory. You can add more Haar cascade files to the directory to detect other features, such as eyes or mouths. More HaarCascadeFiles can be found here https://github.com/opencv/opencv/tree/master/data/haarcascades