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.