Add glasses filter in video stream module

README.md

@@ -37,6 +37,11 @@ python eye_blink_detect.py --shape-predictor shape_predictor_68_face_landmarks.d
 python glasses_effect.py --shape-predictor shape_predictor_68_face_landmarks.dat --image images/elon.jpg --glass images/glasses.png
 ```
 
+## 6. If you want to try glasses filter on video stream
+```bash
+python glasses_stream.py --shape-predictor shape_predictor_68_face_landmarks.dat --glass images/glasses.png
+```
+
 # References
 
 ## 1. Dlib

glasses_stream.py

@@ -0,0 +1,74 @@
+"""Apply glasses filter to video stream."""
+# USAGE
+# python glasses_stream.py --shape-predictor shape_predictor_68_face_landmarks.dat --glass images/glasses.png
+from imutils.video import VideoStream
+from imutils import face_utils
+import numpy as np
+import argparse
+import imutils
+import time
+import dlib
+import cv2
+
+# construct the argument parse and parse the arguments
+ap = argparse.ArgumentParser()
+ap.add_argument("-p", "--shape-predictor", required=True,
+    help="path to facial landmark predictor")
+ap.add_argument("-g", "--glass", required=True, help="path to the glasses image")
+args = vars(ap.parse_args())
+
+# init dlib's HOG face detector and the facial landmarks predictor
+print("[INFO] loading facial landmark predictor...")
+face_hog_detector = dlib.get_frontal_face_detector()
+landmark_predictor = dlib.shape_predictor(args["shape_predictor"])
+
+# the image is made up of 4 layers: Blue, Green, Red, and an Alpha transparency layer (BGR-A)
+img_glasses = cv2.imread(args["glass"], -1)
+# take just the alpha layer used for masking the area for the glasses
+original_mask_glasses = img_glasses[:, :, 3]
+# take the inverse mask for region around the glasses
+original_mask_glasses_inv = cv2.bitwise_not(original_mask_glasses)
+img_glasses = img_glasses[:, :, 0:3]
+original_glasses_height, original_glasses_width = img_glasses.shape[:2]
+
+# start the video stream thread
+print("[INFO] starting video stream thread...")
+vs = VideoStream(src=0).start()
+time.sleep(1.0)
+
+while True:
+    frame = vs.read()
+    frame = imutils.resize(frame, width=600)
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # detect faces in the grayscale frame
+    rects = face_hog_detector(gray, 0)
+
+    for rect in rects:
+        shape = landmark_predictor(gray, rect)
+
+        glasses_width = abs(shape.part(16).x - shape.part(1).x)
+        glasses_height = int(glasses_width * original_glasses_height / original_glasses_width) 
+
+        glasses = cv2.resize(img_glasses, (glasses_width, glasses_height), interpolation=cv2.INTER_AREA)
+        mask_glasses = cv2.resize(original_mask_glasses, (glasses_width, glasses_height), interpolation=cv2.INTER_AREA)
+        mask_glasses_inv = cv2.resize(original_mask_glasses_inv, (glasses_width, glasses_height), interpolation=cv2.INTER_AREA)
+        y1 = int(shape.part(24).y)
+        y2 = int(y1 + glasses_height)
+        x1 = int(shape.part(27).x - (glasses_width/2))
+        x2 = int(x1 + glasses_width)
+        roi = frame[y1:y2, x1:x2]
+        roi_bg = cv2.bitwise_and(roi, roi, mask=mask_glasses_inv)
+        roi_fg = cv2.bitwise_and(glasses, glasses, mask=mask_glasses)
+        frame[y1:y2, x1:x2] = cv2.add(roi_bg, roi_fg)
+
+    # show the frame
+    cv2.imshow("Frame", frame)
+    key = cv2.waitKey(1) & 0xFF
+
+    # if the `q` key was pressed, break from the loop
+    if key == ord("q"):
+        break
+# do a bit of cleanup
+cv2.destroyAllWindows()
+vs.stop()