Update python code

examples/talk_detector/talkdet.py

@@ -15,6 +15,30 @@ ARRAY_DIM = 6
 
 MOUTH_AR_THRESH = 0.2
 
+def verify_alpha_channel(frame):
+    try:
+        frame.shape[3]  # 4th position
+    except IndexError:
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA)
+    return frame
+
+def alpha_blend(frame_1, frame_2, mask):
+    alpha = mask/255.0
+    blended = cv2.convertScaleAbs(frame_1*(1-alpha) + frame_2*alpha)
+    return blended
+
+def apply_circle_focus_blur(frame, x, y):
+    frame = verify_alpha_channel(frame)
+    height, width, _ = frame.shape
+    mask = np.zeros((height, width, 4), dtype='uint8')
+    cv2.circle(mask, (int(x), int(y)), int(x/2),
+               (255, 255, 255), -1, cv2.LINE_AA)
+    mask = cv2.GaussianBlur(mask, (41, 41), cv2.BORDER_DEFAULT)
+    blured = cv2.GaussianBlur(frame, (41, 41), cv2.BORDER_DEFAULT)
+    blended = alpha_blend(frame, blured, 255-mask)
+    frame = cv2.cvtColor(blended, cv2.COLOR_BGRA2BGR)
+    return frame
+
 # define class GoPixelSlice to map to:
 # C type struct { void *data; GoInt len; GoInt cap; }
 class GoPixelSlice(Structure):
@@ -22,7 +46,7 @@ class GoPixelSlice(Structure):
         ("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
     ]
 
-# Obtain the camera pixels and transfer them to Go trough Ctypes.
+# Obtain the camera pixels and transfer them to Go trough Ctypes
 def process_frame(pixs):
     dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
     pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
@@ -36,9 +60,11 @@ def process_frame(pixs):
     ndets = pigo.FindFaces(faces)
     data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
 
-	if data_pointer :
+    if data_pointer:
-		buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
+        buffarr = ((c_longlong * ARRAY_DIM) *
-		res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, ARRAY_DIM,))
+                   MAX_NDETS).from_address(addressof(data_pointer.contents))
+        res = np.ndarray(buffer=buffarr, dtype=c_longlong,
+                         shape=(MAX_NDETS, ARRAY_DIM,))
 
         # The first value of the buffer aray represents the buffer length.
         dets_len = res[0][0]
@@ -58,13 +84,14 @@ cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
 # For this reason we should delay the object detection process with a few milliseconds.
 time.sleep(0.4)
 
-showFaceDet = True
+showFaceDet = False
 showPupil = True
 showLandmarkPoints = True
 
 while(True):
     ret, frame = cap.read()
-	pixs = np.ascontiguousarray(frame[:, :, 1].reshape((frame.shape[0], frame.shape[1])))
+    pixs = np.ascontiguousarray(
+        frame[:, :, 1].reshape((frame.shape[0], frame.shape[1])))
     pixs = pixs.flatten()
 
     # Verify if camera is intialized by checking if pixel array is not empty.
@@ -77,15 +104,19 @@ while(True):
                 if q > 50:
                     if det_type == 0:  # 0 == face;
                         if showFaceDet:
-							cv2.rectangle(frame, (col-scale/2, row-scale/2), (col+scale/2, row+scale/2), (0, 0, 255), 2)
+                            cv2.rectangle(
+                                frame, (col-scale/2, row-scale/2), (col+scale/2, row+scale/2), (0, 0, 255), 2)
                     elif det_type == 1:  # 1 == pupil;
                         if showPupil:
-							cv2.circle(frame, (int(col), int(row)), 4, (0, 0, 255), -1, 8, 0)
+                            cv2.circle(frame, (int(col), int(row)),
+                                       4, (0, 0, 255), -1, 8, 0)
                     elif det_type == 2:  # 2 == facial landmark;
                         if showLandmarkPoints:
-							cv2.circle(frame, (int(col), int(row)), 4, (0, 255, 0), -1, 8, 0)
+                            cv2.circle(frame, (int(col), int(row)),
+                                       4, (0, 255, 0), -1, 8, 0)
                     elif det_type == 3:
                         if mouth_ar < MOUTH_AR_THRESH:  # mouth is open
+                            frame = apply_circle_focus_blur(frame, col, row)
                             cv2.putText(frame, "TALKING!", (10, 30),
                                 cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)