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face_recognition_python.py
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face_recognition_python.py
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
import face_recognition
import os
import cv2
# In[2]:
def known():
known_faces_dir=r'F:\f\face\face recognition\face_recognition package'
known_faces=[]
known_names=[]
for name in os.listdir(known_faces_dir):
for filename in os.listdir(f'{known_faces_dir}/{name}'):
image=face_recognition.load_image_file(f'{known_faces_dir}/{name}/{filename}')
encoding=face_recognition.face_encodings(image)[0]
#encoding=pickle.load(open(f'{name}/{filename}','rb'))
known_faces.append(encoding)
known_names.append(name)
return known_faces, known_names
# In[3]:
def get_match():
known_faces,known_names= known()
video = cv2.VideoCapture(0)
TOLERANCE=0.5
frame_thickness=3
font_thickness=2
model='hog'
img_counter = 0
while True:
ret,image=video.read()
if not ret:
print("failed to grab frame")
break
locations=face_recognition.face_locations(image,model=model)
encodings=face_recognition.face_encodings(image,locations)
for face_encoding ,face_location in zip(encodings,locations):
results=face_recognition.compare_faces(known_faces,face_encoding,TOLERANCE)
#print(f'results{results}')
match=None
try:
match=known_names[results.index(True)]
except ValueError:
print('Not recognized')
else:
print(f"match found:{match}")
img_counter += 1
if img_counter==1:
break
video.release()
return match
# In[ ]: