Rajesh photo

Rajesh D.

Penetration Tester

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Detecting human face using python2.7 and openCV. Source code for live face detection and recognition of humans.

import face_recognition
import cv2
# 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")
rajesh_face_encoding = face_recognition.face_encodings(rajesh_image)[0]

# Load a second sample picture and learn how to recognize it.

andi_image = face_recognition.load_image_file("andi.jpg")
andi_face_encoding = face_recognition.face_encodings(andi_image)[0]

# Create arrays of known face encodings and their names

known_face_encodings = [
rajesh_face_encoding,
andi_face_encoding,]
known_face_names = [
"Rajesh",
"Anderson",]

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(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
cv2.imshow('Video', frame)

# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()

Live Face Recognition Result

Face Recognition