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Face_recognition 与人脸识别解决方案
很久之前做的,好像是从github上参考一老外的,用到了当前比较火的face_recognition第三方库,我在此基础上做了一些改进
现在可以在你的系统path下放一组样本照片,文件名为人名,可以通过import这个demo开始体验人脸识别的乐趣吧。
import cv2
import face_recognition
import os
path = "c:/Python36/Data/img/face_recognition"
cap = cv2.VideoCapture(0)
total_image_name = []
total_face_encoding = []
for fn in os.listdir(path):
print(path + "/" + fn)
total_face_encoding.append(
face_recognition.face_encodings(
face_recognition.load_image_file(path + "/" + fn))[0])
fn = fn[:(len(fn) - 4)]
total_image_name.append(fn)
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
while True:
ret, frame = cap.read()
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
rgb_small_frame = small_frame[:, :, ::-1]
if process_this_frame:
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:
matches = face_recognition.compare_faces(total_face_encoding, face_encoding)
name = "Unknown"
# If a match was found in known_face_encodings, just use the first one.
first_match_index = matches.index(True)
name = total_image_name[first_match_index]
face_names.append(name)
process_this_frame = not process_this_frame
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
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
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)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()