Add facerec_from_webcam_much_faster.py

examples/facerec_from_webcam_much_faster.py

+import face_recognition
+import cv2
+import threading
+import time
+
+# This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the
+# other example, but it includes some basic performance tweaks to make things run a lot faster:
+#   1. Process each video frame at 1/4 resolution (though still display it at full resolution)
+#   2. Only detect faces in every other frame of video.
+#   3. Use a thread to capture frames, which can improve delay.
+
+# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
+# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
+# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.
+
+global frame, is_exit, video_capture
+
+
+# A function use to capture frames, will be used by capture_thread.
+def capture():
+    global frame, is_exit
+    while not is_exit:
+        # Grab a single frame of video
+        ret, frame = video_capture.read()
+
+
+if __name__ == '__main__':
+    # Get a reference to webcam #0 (the default one)
+    video_capture = cv2.VideoCapture(0)
+
+    # Create a thread to capture frames, which can improve delay.
+    is_exit = False
+    capture_thread = threading.Thread(target=capture, name='captureThread', daemon=True)
+    capture_thread.start()
+
+    # Load a sample picture and learn how to recognize it.
+    obama_image = face_recognition.load_image_file("obama.jpg")
+    obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
+
+    # Load a second sample picture and learn how to recognize it.
+    biden_image = face_recognition.load_image_file("biden.jpg")
+    biden_face_encoding = face_recognition.face_encodings(biden_image)[0]
+
+    # Create arrays of known face encodings and their names
+    known_face_encodings = [
+        obama_face_encoding,
+        biden_face_encoding
+    ]
+    known_face_names = [
+        "Barack Obama",
+        "Joe Biden"
+    ]
+
+    # Initialize some variables
+    face_locations = []
+    face_encodings = []
+    face_names = []
+    process_this_frame = True
+
+    while True:
+        # Store a frame to process
+        frame_process = frame
+
+        # Resize frame of video to 1/4 size for faster face recognition processing
+        small_frame = cv2.resize(frame_process, (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(rgb_small_frame)
+            face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
+
+            face_names = []
+            for face_encoding in face_encodings:
+                # See if the face is a match for the known face(s)
+                matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
+                name = "Unknown"
+
+                # If a match was found in known_face_encodings, just use the first one.
+                if True in matches:
+                    first_match_index = matches.index(True)
+                    name = known_face_names[first_match_index]
+
+                face_names.append(name)
+
+        process_this_frame = not process_this_frame
+
+        # Display the results
+        for (top, right, bottom, left), name in zip(face_locations, face_names):
+            # Scale back up face locations since the frame we detected in was scaled to 1/4 size
+            top *= 4
+            right *= 4
+            bottom *= 4
+            left *= 4
+
+            # Draw a box around the face
+            cv2.rectangle(frame_process, (left, top), (right, bottom), (0, 0, 255), 2)
+
+            # Draw a label with a name below the face
+            cv2.rectangle(frame_process, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
+            font = cv2.FONT_HERSHEY_DUPLEX
+            cv2.putText(frame_process, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
+
+        # Display the resulting image
+        cv2.imshow('Video', frame_process)
+
+        # Hit 'q' on the keyboard to quit!
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            is_exit = True
+            time.sleep(0.1)
+            break
+
+    # Release handle to the webcam
+    video_capture.release()
+    cv2.destroyAllWindows()