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Object detection with OpenCV

· 2 min read
Sparsh Agarwal

Face detection​

We will use the frontal face Haar cascade classifier model to detect faces in the given image. The following function first passes the given image into the classifier model to detect a list of face bounding boxes and then runs a loop to draw a red rectangle box around each detected face in the image:

def detect_faces(fix_img):
    face_rects = face_classifier.detectMultiScale(fix_img)
    for (x, y, w, h) in face_rects:
        cv2.rectangle(fix_img,
                     (x,y),
                     (x+w, y+h),
                     (255,0,0),
                     10)
    return fix_img

Eyes detection​

The process is almost similar to the face detection process. Instead of frontal face Haar cascade, we will use the eye detection Haar cascade model.

Input image

Input image

detected faces and eyes in the image

detected faces and eyes in the image

Pedestrian detection​

We will use the full-body Haar cascade classifier model for pedestrian detection. We will apply this model to a video this time. The following function will run the model on each frame of the video to detect the pedestrians:

# While Loop
while cap.isOpened():
    # Read the capture
        ret, frame = cap.read()
    # Pass the Frame to the Classifier
        bodies = body_classifier.detectMultiScale(frame, 1.2, 3)
    # if Statement
        if ret == True:
        # Bound Boxes to Identified Bodies
                for (x,y,w,h) in bodies:
            cv2.rectangle(frame,
                         (x,y),
                         (x+w, y+h),
                         (25,125,225),
                         5)
            cv2.imshow('Pedestrians', frame) 
        # Exit with Esc button
                if cv2.waitKey(1) == 27:
            break  
    # else Statement
        else:
        break
    
# Release the Capture & Destroy All Windows
cap.release()
cv2.destroyAllWindows()

Car detection​

The process is almost similar to the pedestrian detection process. Again, we will use this model on a video. Instead of people Haar cascade, we will use the car cascade model.

Car number plate detection​

The process is almost similar to the face and eye detection process. We will use the car number plate cascade model.

You can find the code here on Github.