OpenCV 3 Computer Vision with Python Cookbook

How to do it...

You need to complete these steps:

1. Import the modules:

import cv2import numpy as np

2. Load the model and set the confidence threshold:

model = cv2.dnn.readNetFromCaffe('../data/face_detector/deploy.prototxt',                                  '../data/face_detector/res10_300x300_ssd_iter_140000.caffemodel')CONF_THR = 0.5

3. Open the video:

video = cv2.VideoCapture('../data/faces.mp4')while True:    ret, frame = video.read()    if not ret: break

4. Detect the faces in the current frame:

    h, w = frame.shape[0:2]    blob = cv2.dnn.blobFromImage(frame, 1, (300*w//h,300), (104,177,123), False)    model.setInput(blob)    output = model.forward()

5. Visualize the results:

    for i in range(output.shape[2]):        conf = output[0,0,i,2]        if conf > CONF_THR:            label = output[0,0,i,1] x0,y0,x1,y1 ...