windows-face-stabiliziation-with-DNN.py

import cv2
import dlib
import numpy as np 

def shapePoints(shape, dtype="int"):
	coords = np.zeros((68, 2), dtype=dtype)
	for i in range(0, 68):
		coords[i] = (shape.part(i).x, shape.part(i).y)
	return coords

def rectPoints(rect):
    x = rect.left()
    y = rect.top()
    w = rect.right() - x
    h = rect.bottom() - y
    return (x, y, w, h)

def stabilization(cx, cy, frame):
	x = 650
	y = 450
	return x-cx, y-cy

def detectFacesWithDNN(frame):
    size = (300,300)
    scalefactor = 1.0
    swapRB = (104.0, 117.0, 123.0)

    height, width = frame.shape[:2]
    resizedFrame = cv2.resize(frame, size)
    blob = cv2.dnn.blobFromImage(resizedFrame, scalefactor, size, swapRB)
    net.setInput(blob)
    dnnFaces = net.forward()
    for i in range(dnnFaces.shape[2]):
        confidence = dnnFaces[0, 0, i, 2]
        if confidence > 0.5:
            box = dnnFaces[0, 0, i, 3:7] * np.array([width, height, width, height])
            (x, y, x1, y1) = box.astype("int")
            cv2.rectangle(frame, (x, y), (x1, y1), (193, 69, 42), 2)
    return frame, x, y, x1, y1

def prepareBackground(cap):
	# copying frame from the camera to create the background
	ret, frame = cap.read()
	background = frame.copy()
	background = cv2.resize(background, (1300,900))
	background = cv2.GaussianBlur(background, (101,101), 0)
	# copying the background to achieve refresh
	backgroundCopy = background.copy()
	backgroundCopy = cv2.GaussianBlur(backgroundCopy, (101,101), 0)
	return background, backgroundCopy


# pre-trained model
modelFile = "models/res10_300x300_ssd_iter_140000.caffemodel"
# prototxt has the information of where the training data is located.
configFile = "models/deploy.prototxt"
net = cv2.dnn.readNetFromCaffe(configFile, modelFile)

cap = cv2.VideoCapture(0)
background, backgroundCopy = prepareBackground(cap)

while True:
    ret, frame = cap.read()
    frame = cv2.resize(frame, (720,480))

    if not ret:
        break

    try:
        frame, x, y, xw, yh = detectFacesWithDNN(frame)
        cy = int((y+yh)/2)
        cx = int((x+xw)/2)
        color = (255,255,255)
        cv2.circle(frame, (cx, cy), 4, color, 2)
        cv2.imshow('Face Stabilization with DNN', frame)
        x,y = stabilization(cx,cy,frame)
        cv2.moveWindow('Face Stabilization with DNN',int(x),int(y))
    except:
        cv2.imshow('Face Stabilization with DNN', frame)


    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()