Update Facial Recognition codes

Facial_Instruction.txt

@@ -28,7 +28,7 @@ So to run the demo, we need to install Dlib on our system.
 
 
 3. Requirements for face registration:
-	a. User can sometimes turn your head a little bit to let us get more face data, but you must make sure that there're 5 colles on each photo.
-	b. Don't register you face when too much light is coming.
+	a. User can sometimes slightly rotate their face, but must make sure their facical features (mouth, eyes, nose...) are within the camera view.
+	b. Ambient light could affect the performance of the facial detection, such as overexposure, glare, reflection or so on;
 
 welcome any try-out and comments!

Facial_Recognition_Enrollment.py

@@ -43,12 +43,12 @@ def enroll_face_dataset():
   i = 0
   faceDescriptors = None
   for imagePath in imagePaths:
-    print("processing: {}".format(imagePath))
+    #print("processing: {}".format(imagePath))
     img = cv2.imread(imagePath)
 
     faces = faceDetector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
 
-    print("{} Face(s) found".format(len(faces)))
+    #print("{} Face(s) found".format(len(faces)))
 
     for k, face in enumerate(faces):
 

Facial_Recognition_Inference.py

@@ -13,7 +13,7 @@ pwd = sys.path[0]
 PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat'
 FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat'
 
-SKIP_FRAMES = 10
+SKIP_FRAMES = 1
 THRESHOLD = 0.4
 
 faceDetector = dlib.get_frontal_face_detector()
@@ -25,9 +25,10 @@ faceDescriptorsEnrolled = np.load(pwd+'/Facial_models/descriptors.npy')
 
 
 cam = cv2.VideoCapture(1)
-
 count = 0
 
+x1 = x2 = y1 = y2 = 0
+
 while True:
   t = time.time()
   success, im = cam.read()
@@ -72,16 +73,10 @@ while True:
       else:
         label = 'unknown'
 
-      print("time taken = {:.3f} seconds".format(time.time() - t))
+      #print("time taken = {:.3f} seconds".format(time.time() - t))
 
 
   cv2.rectangle(im, (x1, y1), (x2, y2), (0, 255, 0), 2)
-
-      #center = (int((x1 + x2)/2.0), int((y1 + y2)/2.0))
-      #radius = int((y2-y1)/2.0)
-      #color = (0, 255, 0)
-      #cv2.circle(im, center, radius, color, thickness=1, lineType=8, shift=0)
-
   font_face = cv2.FONT_HERSHEY_SIMPLEX
   font_scale = 0.8
   text_color = (0, 255, 0)

Facial_Recognition_Registration.py

@@ -4,7 +4,6 @@ import math
 import cv2
 import Facial_Recognition_Enrollment
 
-
 def register_your_face(label):
     num_cap = 50
 
@@ -32,6 +31,12 @@ def register_your_face(label):
 
 
 if __name__ == "__main__":
-    label = input('Enter a label: ')
+    print("Face registration start...")
+    print()
+    label = input('Pleas enter your Name/Label: ')
     register_your_face(label)
-    Facial_Recognition_Enrollment.enroll_face_dataset()
+    print("Data saved! Starting enrollment...")
+    print()
+    Facial_Recognition_Enrollment.enroll_face_dataset()  #Need discuss and modify after intergrate with database. 
+    print("Face registration completed!")
+    print()