Detecting human face using python2.7 and openCV. Source code for live face detection and recognition of humans.
# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0)
# Load a sample picture and learn how to recognize it.
rajesh_image = face_recognition.load_image_file("rajesh1.jpg")# Load a second sample picture and learn how to recognize it.
rajesh_face_encoding = face_recognition.face_encodings(rajesh_image)
andi_image = face_recognition.load_image_file("andi.jpg")# Create arrays of known face encodings and their names
andi_face_encoding = face_recognition.face_encodings(andi_image)
known_face_encodings = [while True:
known_face_names = [
# 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(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):
# 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]
# Draw a box around the face
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
# Draw a label with a name below the face
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
# Display the resulting image
# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
# Release handle to the webcam