Fix #271 - convert BGR to RBG when using OpenCV VideoCapture

examples/facerec_from_video_file.py

@@ -42,9 +42,12 @@ while True:
     if not ret:
         break
 
+    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
+    rgb_frame = frame[:, :, ::-1]
+
     # Find all the faces and face encodings in the current frame of video
-    face_locations = face_recognition.face_locations(frame)
-    face_encodings = face_recognition.face_encodings(frame, face_locations)
+    face_locations = face_recognition.face_locations(rgb_frame)
+    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
 
     face_names = []
     for face_encoding in face_encodings:

examples/facerec_from_webcam.py

@@ -19,9 +19,12 @@ while True:
     # Grab a single frame of video
     ret, frame = video_capture.read()
 
+    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
+    rgb_frame = frame[:, :, ::-1]
+
     # Find all the faces and face enqcodings in the frame of video
-    face_locations = face_recognition.face_locations(frame)
-    face_encodings = face_recognition.face_encodings(frame, face_locations)
+    face_locations = face_recognition.face_locations(rgb_frame)
+    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
 
     # Loop through each face in this frame of video
     for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):

examples/facerec_from_webcam_faster.py

@@ -30,11 +30,14 @@ while True:
     # Resize frame of video to 1/4 size for faster face recognition processing
     small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
 
+    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
+    rgb_small_frame = small_frame[:, :, ::-1]
+
     # Only process every other frame of video to save time
     if process_this_frame:
         # Find all the faces and face encodings in the current frame of video
-        face_locations = face_recognition.face_locations(small_frame)
-        face_encodings = face_recognition.face_encodings(small_frame, face_locations)
+        face_locations = face_recognition.face_locations(rgb_small_frame)
+        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
 
         face_names = []
         for face_encoding in face_encodings:

examples/find_faces_in_batches.py

@@ -28,6 +28,9 @@ while video_capture.isOpened():
     if not ret:
         break
 
+    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
+    frame = frame[:, :, ::-1]
+
     # Save each frame of the video to a list
     frame_count += 1
     frames.append(frame)