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How to detect humans in an image in OpenCV Python?
To detect humans in an image and draw bounding boxes around them, you can use the steps given below −
Import the required library. In all the following examples, the required Python library is OpenCV. Make sure you have already installed it.
Read the input image using cv2.imread() in a grayscale. Specify the full image path.
Initialize a HOG descriptor object hog = cv2.HOGDescriptor() and set the SVM detector as hog.setSVMDetector() as default people detector.
Detect humans in the input image using hog.detectMultiScale(). It returns the coordinates of detected humans in (x,y,w,h) format.
Loop over all detected humans in the image and draw the bounding rectangles around the detected humans in the original image using cv2.rectangle().
Display the image with the drawn bounding rectangles around the humans.
Let's have a look at the example below for more clear understanding.
We will use this image as the Input File for the following example −
Example
In this example, detect humans in the input image using the Hog descriptor.
# import required libraries import cv2 # Reading the Image image = cv2.imread('people1.jpg') # initialize the HOG descriptor hog = cv2.HOGDescriptor() hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector()) # detect humans in input image (humans, _) = hog.detectMultiScale(image, winStride=(10, 10), padding=(32, 32), scale=1.1) # getting no. of human detected print('Human Detected : ', len(humans)) # loop over all detected humans for (x, y, w, h) in humans: pad_w, pad_h = int(0.15 * w), int(0.01 * h) cv2.rectangle(image, (x + pad_w, y + pad_h), (x + w - pad_w, y + h - pad_h), (0, 255, 0), 2) # display the output image cv2.imshow("Image", image) cv2.waitKey(0) cv2.destroyAllWindows()
Output
When you run the above Python program, it will produce the following output −
Human Detected: 4
And we get the following output window −
The bounding boxes around the detected humans are drawn with green color.
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