Detecting face and landmarks from image using dlib and opencv

dlib_face_landmarks.py

#pip install dlib
#download pretrained dlib file and unzip 
#$wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
#$bzip2 -d /content/shape_predictor_68_face_landmarks.dat.bz2

import sys
import numpy as np 
import cv2 
#below line of code is used only in colab
from google.colab.patches import cv2_imshow
import dlib 
pretrained_dlib_detector = "/content/shape_predictor_68_face_landmarks.dat"
detector = detector = dlib.get_frontal_face_detector()
#frame is a 3-channel image
rects = detector(frame, 1)
predictor = dlib.shape_predictor(pretrained_dlib_detector)
def rect_to_bb(rect):
	# take a bounding predicted by dlib and convert it
	# to the format (x, y, w, h) as we would normally do
	# with OpenCV
	x = rect.left()
	y = rect.top()
	w = rect.right() - x
	h = rect.bottom() - y
	# return a tuple of (x, y, w, h)
	return (x, y, w, h)
 
def shape_to_np(shape, dtype="int"):
    # initialize the list of (x, y)-coordinates
    coords = np.zeros((68, 2), dtype=dtype)
    # loop over the 68 facial landmarks and convert them
    # to a 2-tuple of (x, y)-coordinates
    for i in range(0, 68):
      coords[i] = (shape.part(i).x, shape.part(i).y)
    # return the list of (x, y)-coordinates
    return coords

for (i, rect) in enumerate(rects):
	# determine the facial landmarks for the face region, then
	# convert the facial landmark (x, y)-coordinates to a NumPy
	# array
	shape = predictor(frame, rect)
	shape = shape_to_np(shape)
	# convert dlib's rectangle to a OpenCV-style bounding box
	# [i.e., (x, y, w, h)], then draw the face bounding box
	(x, y, w, h) = rect_to_bb(rect)
	cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
	# show the face number
	cv2.putText(frame, "Face #{}".format(i + 1), (x - 10, y - 10),
		cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
	# loop over the (x, y)-coordinates for the facial landmarks
	# and draw them on the image
	for (x, y) in shape:
		cv2.circle(frame, (x, y), 1, (0, 0, 255), -1)
# show the output image with the face detections + facial landmarks
#below is used only in colab
cv2_imshow(frame)