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test.py
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test.py
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import face_recognition
import cv2
import socket
# This is a super simple (but slow) example of running face recognition on live video from your webcam.
# There's a second example that's a little more complicated but runs faster.
# 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.
# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0)
# Load a sample picture and learn how to recognize it.
lucasface = face_recognition.load_image_file("lucas.jpg")
lucasface_encoding = face_recognition.face_encodings(lucasface)[0]
# Load a second sample picture and learn how to recognize it.
lucasinsta = face_recognition.load_image_file("lucas1.jpg")
lucasinsta_encoding = face_recognition.face_encodings(lucasinsta)[0]
paulo = face_recognition.load_image_file("paulo.png")
paulo_encoding = face_recognition.face_encodings(paulo)[0]
suzy = face_recognition.load_image_file("suzy.jpeg")
suzy_encoding = face_recognition.face_encodings(suzy)[0]
barbara = face_recognition.load_image_file("barbara.jpeg")
barbara_encoding = face_recognition.face_encodings(barbara)[0]
antonio = face_recognition.load_image_file("antonio.jpeg")
antonio_encoding = face_recognition.face_encodings(antonio)[0]
florencia = face_recognition.load_image_file("florencia.jpeg")
florencia_encoding = face_recognition.face_encodings(florencia)[0]
anderson = face_recognition.load_image_file("anderson.jpeg")
anderson_encoding = face_recognition.face_encodings(anderson)[0]
# Create arrays of known face encodings and their names
known_face_encodings = [
lucasface_encoding,
paulo_encoding,
suzy_encoding,
barbara_encoding,
antonio_encoding,
florencia_encoding,
anderson_encoding
]
known_face_names = [
"Lucas",
"Paulo",
"Suzy",
"Barbara",
"Antonio",
"Florencia",
"Anderson"
]
HOST = '127.0.0.1' # Endereco IP do Servidor
PORT = 8884 # Porta que o Servidor esta
tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
dest = (HOST, PORT)
tcp.connect(dest)
print ('Para sair use CTRL+X\n')
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]
else:
# Draw a box around the face
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 155), 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()