from imutils import face_utils, video, resize
import dlib
import numpy as np
import cv2
import argparse
import os
import glob
W = ‘./shape_predictor_68_face_landmarks.dat’
P = ‘C:/Users/CHINMAYEE/Pictures/Saved Pictures/facial-landmarks-master/deploy.prototxt’
M = ‘C:/Users/CHINMAYEE/Pictures/Saved Pictures/facial-landmarks-master/res10_300x300_ssd_iter_140000.caffemodel’
T = 0.6
predictor = dlib.shape_predictor(W)
#image = cv2.imread(“C:/Users/CHINMAYEE/Pictures/Saved Pictures/facial-landmarks-master/IMG2.PNG”)
path= glob.glob(“C:/Users/CHINMAYEE/Pictures/Saved Pictures/facial-landmarks-master/images/*.PNG”)
for File in path:
#print(File)
img=cv2.imread(File)
#cv2.imshow('image',img)
Converting the image to gray scale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
This is based on SSD deep learning pretrained model
dl_detector = cv2.dnn.readNetFromCaffe(P, M)
Facial landmarks with DL
#inputBlob = cv2.dnn.blobFromImage(cv2.resize(
#img, (300, 300)), 1, (300, 300), (104, 177, 123))
dl_detector.setInput(img)
detections = dl_detector.forward()
for i in range(0, detections.shape[1]):
# Probability of prediction
prediction_score = detections[0, 0, i, 2]
if prediction_score < T:
continue
# Finding height and width of frame
(h, w) = img.shape[:2]
# compute the (x, y)-coordinates of the bounding box for the
# object
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(x1, y1, x2, y2) = box.astype("int")
y1, x2 = int(y1 * 1.15), int(x2 * 1.05)
print(x1, y1, x2, y2)
# Make the prediction and transfom it to numpy array
shape = predictor(gray, dlib.rectangle(left=x1, top=y1, right=x2, bottom=y2))
shape = face_utils.shape_to_np(shape)
cv2.rectangle(img, (x1, y1), (x2, y2), (0, 0, 255), 2)
# Draw on our image, all the finded cordinate points (x,y)
for (x, y) in shape:
cv2.circle(img, (x, y), 2, (0, 0, 255), -1)
img_height, img_width = img.shape[:2]
cv2.putText(img, “DL”, (img_width - 100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 0, 255), 2)
show the output frame
cv2.imshow(“Facial Landmarks”, img)
cv2.waitKey(0)
cv2.destroyAllWindows()
this is the full code
I have more than 1 image in the image folder but this code runs for only one image. can you please help me out with this.