def search_train(self): # 已知访客搜索初始化 后面补充10秒清空时加入这个为了人员信息管理时的更新，先判断feature_change==1
with open('./data/index_enter.pkl', 'rb') as f:
self.index_dict = pkl.load(f)
with open('./data/database_enter.npy', 'rb') as f:
self.feature_data = np.load('./data/database_enter.npy')
self.search_eign = Search_engin(self.feature_data)
self.search_eign.train()
def verify_img(img):
image1 = img
p_id_list = []
api_unknown = 0
if image1 is not None:
with open('./data/index_enter.pkl', 'rb') as f:
index_dict = pkl.load(f)
with open('./data/database_enter.npy', 'rb') as f:
feature_data = np.load('./data/database_enter.npy')
search_eign = Search_engin(feature_data)
search_eign.train()
#print('get image')
image1 = cv2.flip(image1, 1)
width = int(image1.shape[1] / 2)
height = int(image1.shape[0] / 2)
image = cv2.resize(image1.copy(), (width, height))
try:
bboxs = naivedlib.getALLFaces(image)
print('bbox detect took ')
bboxs = [dlib.rectangle(int(bbox.left() * downsample_ratio), int(bbox.top() * downsample_ratio),
int(bbox.right() * downsample_ratio), int(bbox.bottom() * downsample_ratio))
for bbox in bboxs]
facenum = len(bboxs)
if bboxs is not None:
for bbox in bboxs:
# 对每个人脸进行操作
#print('bbox is detected')
query = []
left_eye, right_eye = naivedlib.get_eyes(image1, bbox)
start = time.time()
save_croped, crop_image = crop_rotate_part(image1[:, :, ::-1], bbox, left_eye, right_eye,
bbox.width() * 0.895)
save_croped = cv2.cvtColor(save_croped, cv2.COLOR_BGR2RGB)
end = time.time()
print('\tpreprocess took {}'.format(end - start))
flip_image = cv2.flip(crop_image.copy(), 1)
crop_image = proc_img(crop_image, is_whiten=False)
flip_image = proc_img(flip_image, is_whiten=False)
query.append(crop_image[0])
query.append(flip_image[0])
prob_image = np.asarray(query)
start = time.time()
feature = extractor.extract_feature(prob_image)
end = time.time()
print('\textract feature took {}'.format(end - start))
feature = feature / np.linalg.norm(feature)
idx_list = search_eign.search(feature) # 获取搜索后的排列
idx_list = [idx_list[0][i] for i in range(idx_list.shape[1])]
score_list = []
name_list = []
for idx in idx_list:
score = 1 - spatial.distance.cosine(feature, feature_data[int(idx)])
name = {value: key for key, value in index_dict.items()}[int(idx)]
score_list.append(score)
name_list.append(name)
#print(name_list)
#print(score_list)
score = 1 - spatial.distance.cosine(feature, feature_data[int(idx_list[0])])
#print(thresh)
if score > thresh:
p_id_list.append(name_list[0])
else:
api_unknown = api_unknown + 1
except:
pass
#print(p_id_list)
return (p_id_list, api_unknown)
class Face_Verification(object):
def __init__(self):
ext_model_path = './model/facenet/inception-ring-1024.pb'
# self.video_capture = cv2.VideoCapture(camera_Id)
# self.video_capture = cv2.VideoCapture(HKcam)
# self.is_camera_on = True
self.id_image = None
self.id_image2 = None
self.id_image1_2 = None
# self.probe_image = None
self.ID_label = 0
self.count = 0
self.ID_lib = {}
self.ID_name = {}
self.feature_data = None
self.index_dict = None
self.unknownum = 0 # 10秒内未知人员数
self.knownum = 0 # 10秒内已知人员数
self.unknown_feature_read()
self.naivedlib = NaiveDlib()
self.extractor = Extractor(ext_model_path, gpu_fraction=0) # gpu_fraction显存占用比例
temp = np.ones((5, 112, 96, 1))
self.extractor.extract_feature(im_arr=temp)
self.query = deque(maxlen=2)
self.search_train()
def search_train(self): # 已知访客搜索初始化 后面补充10秒清空时加入这个为了人员信息管理时的更新，先判断feature_change==1
with open('./data/index_enter.pkl', 'rb') as f:
self.index_dict = pkl.load(f)
with open('./data/database_enter.npy', 'rb') as f:
self.feature_data = np.load('./data/database_enter.npy')
self.search_eign = Search_engin(self.feature_data)
self.search_eign.train()
def unknown_feature_read(self):
# self.datetime = datetime.now().strftime('%Y_%m_%d')
# self.unknownfeature_path = './data/unknown_feature.npy'
# self.unknown_pic_path = './image_saved/{}/unknown'.format(self.datetime)
# self.known_pic_path = './image_saved/{}/known'.format(self.datetime)
self.unknownfeature = np.asarray([]) # 10秒内未知特征
self.unknownum = 0
self.knownum = 0
self.knownlist = [] # 10秒内已知人名
self.summary = {} # 10秒内统计信息
def wait_clean(self): # 10秒数据清除和人数保存
with open('feature_change.txt', 'r') as f:
data = f.readline()
feature_change = int(data)
if feature_change == 1:
self.search_train()
feature_change = 0
with open('feature_change.txt', 'w+') as f:
f.write(str(feature_change))
self.knownum = 0
self.unknownum = 0
self.unknownfeature = np.asarray([])
self.knownlist = []
def insert_summary(self): # 10秒内有人进来则将这10秒的第一个人进来的时间，已知访客的p_id,已知访客人数，未知访客数，总数插入
comtime = self.summary["comtime"]
knownum = self.knownum
unknownum = self.unknownum
num = knownum + unknownum
conn = pymysql.connect(host='localhost',
port=3306,
user='******',
passwd='1234567',
db="face_info",
charset="utf8"
)
c = conn.cursor()
try:
for i in range(self.knownum):
p_id = self.knownlist[i]
sql = '''insert into num_info
(comtime,
p_id,
knownum,
unknownum,
num)
VALUES ('%s','%s', '%d', '%d', '%d') ''' % (
comtime, p_id, knownum, unknownum, num)
c.execute(sql)
conn.commit()
print("Table inserted successfuly")
c.close()
conn.close()
except:
print("Table inserted failed")
def verify(self, thresh): # 识别比对
global VIDEO_IMAGE
global isPass
global first
new_person = 0 # newperson = 1时则说明有人来
knownflag = 0
unknownflag = 0
currentunknownum = 0
currentknownum = 0
idname = [] # 可显示id照片的编号列表
currentDate = datetime.now().strftime('%Y_%m_%d')
currentTime = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
currentTime_img = datetime.now().strftime('%Y-%m-%d %H-%M-%S')
# if self.pic_time != None and (datetime.datetime.now() - self.pic_time).seconds > pic_time:
# self.image_clear()
image1 = None
for i in range(VIDEO_IMAGE.qsize()):
image1 = VIDEO_IMAGE.get()
#image1 = cv2.imread('./user_pic/13800000001.bmp') # 加载图片测试
if image1 is not None:
print('get image')
image1 = cv2.flip(image1, 1)
width = int(image1.shape[1] / 2)
height = int(image1.shape[0] / 2)
image = cv2.resize(image1.copy(), (width, height))
try:
# total_start = time.time()
bboxs = self.naivedlib.getALLFaces(image)
# bbox_end = time.time()
print('bbox detect took ')
bboxs = [dlib.rectangle(int(bbox.left() * downsample_ratio), int(bbox.top() * downsample_ratio),
int(bbox.right() * downsample_ratio), int(bbox.bottom() * downsample_ratio))
for bbox in bboxs]
facenum = len(bboxs)
if bboxs is not None:
new_person = 1
print(time.strftime('%H:%M:%S', time.localtime(time.time())))
for bbox in bboxs:
# 对每个人脸进行操作
print('bbox is detected')
query = []
left_eye, right_eye = self.naivedlib.get_eyes(image1, bbox)
start = time.time()
save_croped, crop_image = crop_rotate_part(image1[:, :, ::-1], bbox, left_eye, right_eye,
bbox.width() * 0.895)
save_croped = cv2.cvtColor(save_croped, cv2.COLOR_BGR2RGB)
# bbox_temp = [bbox.left(),bbox.top(),bbox.right(),bbox.bottom()]
# crop_image = crop_only(image1,bbox_temp)
# cv2.imwrite('image.jpg',crop_image)
end = time.time()
print('\tpreprocess took {}'.format(end - start))
flip_image = cv2.flip(crop_image.copy(), 1)
crop_image = proc_img(crop_image, is_whiten=False)
flip_image = proc_img(flip_image, is_whiten=False)
query.append(crop_image[0])
query.append(flip_image[0])
prob_image = np.asarray(query)
start = time.time()
feature = self.extractor.extract_feature(prob_image)
end = time.time()
print('\textract feature took {}'.format(end - start))
feature = feature / np.linalg.norm(feature)
idx_list = self.search_eign.search(feature) # 获取搜索后的排列
idx_list = [idx_list[0][i] for i in range(idx_list.shape[1])]
score_list = []
name_list = []
for idx in idx_list:
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx)])
name = {value: key for key, value in self.index_dict.items()}[int(idx)]
score_list.append(score)
name_list.append(name)
#print(name_list)
#print(score_list)
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx_list[0])])
thresh = float(thresh)
# print(thresh)
if score > thresh:
knownflag = 1
name = name_list[0]
if self.knownum == 0:
self.knownum = 1
first = 1
self.summary["comtime"] = currentTime
self.knownlist.append(name)
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime_img,
name),
save_croped)
idname.append(name) # 当前帧中的已知访客name
print("欢迎" + name)
print("推送")
push_info = self.push_summary_known(name)
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
# print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
if name not in self.knownlist:
self.knownlist.append(name)
self.knownum = self.knownum + 1
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime_img,
name),
save_croped)
idname.append(name) # 当前帧中的已知访客name
print("欢迎" + name)
print("推送")
push_info = self.push_summary_known(name)
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
# print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
unknownflag = 1
if self.unknownum == 0:
print("第一个未知人员")
first = 1
currentunknownum = currentunknownum + 1
self.unknownum = 1
if self.summary == []:
self.summary["comtime"] = currentTime
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime_img,
self.unknownum), save_croped)
self.unknownfeature = feature[np.newaxis, :]
print("推送")
push_info = self.push_summary_unknown()
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
# face.insert_summary()
else:
unthresh = 0.5
self.search_eign_unknown = Search_engin(self.unknownfeature) # 未知访客搜索
self.search_eign_unknown.train()
unknown_idx = self.search_eign_unknown.search(feature)
unknown_idx = [unknown_idx[0][i] for i in range(unknown_idx.shape[1])]
print(unknown_idx)
uscore = 1 - spatial.distance.cosine(feature, self.unknownfeature[int(unknown_idx[0])])
print(uscore)
if uscore < unthresh: # 第一次识别出该未知人员
self.unknownum = self.unknownum + 1
currentunknownum = currentunknownum + 1
# self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
cv2.imwrite(
'./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime_img,
self.unknownum), save_croped)
self.unknownfeature = np.vstack((self.unknownfeature, feature))
print("推送")
push_info = self.push_summary_unknown()
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
else:
new_person = 0
except:
pass
else:
print("图片为空！")
return (new_person)
def push_summary(self): # 推送汇总
dict_push = {}
if self.knownum != 0:
dict_push["known"] = "{}".format(self.knownum)
dict_push["unknown"] = "{}".format(self.unknownum)
for i in range(self.knownum):
p_id = self.knownlist[i]
result = getperson_tables(p_id)
#image_url = result[0][3]
image_url = "http://" + host_ip + ":5000" + "/user_pic/{}".format(p_id)
count, lasttime = select_tables(p_id)
dict_push["person_{}".format(i)] = {"count": "{}".format(count), "lasttime": "{}".format(lasttime),
"image": image_url}
else:
# 全是未知人员
dict_push["known"] = 0
dict_push["unknown"] = "{}".format(self.unknownum)
return (dict_push)
def push_summary_known(self,p_id):
dict_push = {}
#result = getperson_tables(p_id)
# image_url = result[0][3]
image_url = "http://" + host_ip + ":5000" + "/user_pic/{}".format(p_id)
count, lasttime = select_tables(p_id)
dict_push["data"] = {"p_id":"{}".format(p_id),"count": "{}".format(count), "lasttime": "{}".format(lasttime),
"image": image_url}
return (dict_push)
def push_summary_unknown(self):
dict_push = {}
dict_push["data"] = "unknown!"
return (dict_push)
def verify(self, thresh): # 识别比对
global VIDEO_IMAGE
global isPass
global first
new_person = 0 # newperson = 1时则说明有人来
knownflag = 0
unknownflag = 0
currentunknownum = 0
currentknownum = 0
idname = [] # 可显示id照片的编号列表
currentDate = datetime.now().strftime('%Y_%m_%d')
currentTime = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
currentTime_img = datetime.now().strftime('%Y-%m-%d %H-%M-%S')
# if self.pic_time != None and (datetime.datetime.now() - self.pic_time).seconds > pic_time:
# self.image_clear()
image1 = None
for i in range(VIDEO_IMAGE.qsize()):
image1 = VIDEO_IMAGE.get()
#image1 = cv2.imread('./user_pic/13800000001.bmp') # 加载图片测试
if image1 is not None:
print('get image')
image1 = cv2.flip(image1, 1)
width = int(image1.shape[1] / 2)
height = int(image1.shape[0] / 2)
image = cv2.resize(image1.copy(), (width, height))
try:
# total_start = time.time()
bboxs = self.naivedlib.getALLFaces(image)
# bbox_end = time.time()
print('bbox detect took ')
bboxs = [dlib.rectangle(int(bbox.left() * downsample_ratio), int(bbox.top() * downsample_ratio),
int(bbox.right() * downsample_ratio), int(bbox.bottom() * downsample_ratio))
for bbox in bboxs]
facenum = len(bboxs)
if bboxs is not None:
new_person = 1
print(time.strftime('%H:%M:%S', time.localtime(time.time())))
for bbox in bboxs:
# 对每个人脸进行操作
print('bbox is detected')
query = []
left_eye, right_eye = self.naivedlib.get_eyes(image1, bbox)
start = time.time()
save_croped, crop_image = crop_rotate_part(image1[:, :, ::-1], bbox, left_eye, right_eye,
bbox.width() * 0.895)
save_croped = cv2.cvtColor(save_croped, cv2.COLOR_BGR2RGB)
# bbox_temp = [bbox.left(),bbox.top(),bbox.right(),bbox.bottom()]
# crop_image = crop_only(image1,bbox_temp)
# cv2.imwrite('image.jpg',crop_image)
end = time.time()
print('\tpreprocess took {}'.format(end - start))
flip_image = cv2.flip(crop_image.copy(), 1)
crop_image = proc_img(crop_image, is_whiten=False)
flip_image = proc_img(flip_image, is_whiten=False)
query.append(crop_image[0])
query.append(flip_image[0])
prob_image = np.asarray(query)
start = time.time()
feature = self.extractor.extract_feature(prob_image)
end = time.time()
print('\textract feature took {}'.format(end - start))
feature = feature / np.linalg.norm(feature)
idx_list = self.search_eign.search(feature) # 获取搜索后的排列
idx_list = [idx_list[0][i] for i in range(idx_list.shape[1])]
score_list = []
name_list = []
for idx in idx_list:
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx)])
name = {value: key for key, value in self.index_dict.items()}[int(idx)]
score_list.append(score)
name_list.append(name)
#print(name_list)
#print(score_list)
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx_list[0])])
thresh = float(thresh)
# print(thresh)
if score > thresh:
knownflag = 1
name = name_list[0]
if self.knownum == 0:
self.knownum = 1
first = 1
self.summary["comtime"] = currentTime
self.knownlist.append(name)
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime_img,
name),
save_croped)
idname.append(name) # 当前帧中的已知访客name
print("欢迎" + name)
print("推送")
push_info = self.push_summary_known(name)
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
# print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
if name not in self.knownlist:
self.knownlist.append(name)
self.knownum = self.knownum + 1
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime_img,
name),
save_croped)
idname.append(name) # 当前帧中的已知访客name
print("欢迎" + name)
print("推送")
push_info = self.push_summary_known(name)
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
# print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
unknownflag = 1
if self.unknownum == 0:
print("第一个未知人员")
first = 1
currentunknownum = currentunknownum + 1
self.unknownum = 1
if self.summary == []:
self.summary["comtime"] = currentTime
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime_img,
self.unknownum), save_croped)
self.unknownfeature = feature[np.newaxis, :]
print("推送")
push_info = self.push_summary_unknown()
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
# face.insert_summary()
else:
unthresh = 0.5
self.search_eign_unknown = Search_engin(self.unknownfeature) # 未知访客搜索
self.search_eign_unknown.train()
unknown_idx = self.search_eign_unknown.search(feature)
unknown_idx = [unknown_idx[0][i] for i in range(unknown_idx.shape[1])]
print(unknown_idx)
uscore = 1 - spatial.distance.cosine(feature, self.unknownfeature[int(unknown_idx[0])])
print(uscore)
if uscore < unthresh: # 第一次识别出该未知人员
self.unknownum = self.unknownum + 1
currentunknownum = currentunknownum + 1
# self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
cv2.imwrite(
'./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime_img,
self.unknownum), save_croped)
self.unknownfeature = np.vstack((self.unknownfeature, feature))
print("推送")
push_info = self.push_summary_unknown()
s = json.dumps(push_info)
r = requests.post(faceverify_post_url, data=s)
print(r)
#face.insert_summary()
else:
new_person = 0
except:
pass
else:
print("图片为空！")
return (new_person)
def verify(self, thresh):
global VIDEO_IMAGE
global isPass
knownflag = 0
unknownflag = 0
currentunknownum = 0
currentknownum = 0
idname = [] # 可显示id照片的编号列表
currentDate = datetime.now().strftime('%Y_%m_%d')
currentTime = datetime.now().strftime('%Y-%m-%d %H-%M-%S')
if currentDate != self.datetime: #新日期触发
self.today_clean(self.datetime)
self.datetime = currentDate
web = Web_Browser()
web.setModal(False)
web.setWindowTitle(_translate("Face_Verification", "比对结果", None))
# if self.pic_time != None and (datetime.datetime.now() - self.pic_time).seconds > pic_time:
# self.image_clear()
for i in range(probe_image.qsize()):
image1 = probe_image.get()
#image1 = cv2.imread('./card/2.jpg') # 加载图片测试
if image1 is not None:
print('get image')
image1 = cv2.flip(image1, 1)
width = int(image1.shape[1] / 2)
height = int(image1.shape[0] / 2)
image = cv2.resize(image1.copy(), (width, height))
try:
#total_start = time.time()
bboxs = self.naivedlib.getALLFaces(image)
#bbox_end = time.time()
print('bbox detect took ')
bboxs = [dlib.rectangle(int(bbox.left() * downsample_ratio), int(bbox.top() * downsample_ratio),
int(bbox.right() * downsample_ratio), int(bbox.bottom() * downsample_ratio))
for bbox in bboxs]
facenum = len(bboxs)
#print(facenum)#人脸数
# index_list = []
#idname = [] # 可显示id照片的编号列表
if bboxs is not None:
print(time.strftime('%H:%M:%S', time.localtime(time.time())))
for bbox in bboxs:
# 对每个人脸进行操作
print('bbox is detected')
query = []
left_eye, right_eye = self.naivedlib.get_eyes(image1, bbox)
start = time.time()
save_croped, crop_image = crop_rotate_part(image1[:, :, ::-1], bbox, left_eye, right_eye,
bbox.width() * 0.895)
save_croped = cv2.cvtColor(save_croped, cv2.COLOR_BGR2RGB)
# bbox_temp = [bbox.left(),bbox.top(),bbox.right(),bbox.bottom()]
# crop_image = crop_only(image1,bbox_temp)
# cv2.imwrite('image.jpg',crop_image)
end = time.time()
print('\tpreprocess took {}'.format(end - start))
flip_image = cv2.flip(crop_image.copy(), 1)
crop_image = proc_img(crop_image, is_whiten=False)
flip_image = proc_img(flip_image, is_whiten=False)
query.append(crop_image[0])
query.append(flip_image[0])
prob_image = np.asarray(query)
start = time.time()
feature = self.extractor.extract_feature(prob_image)
end = time.time()
print('\textract feature took {}'.format(end - start))
feature = feature / np.linalg.norm(feature)
idx_list = self.search_eign.search(feature) # 获取搜索后的排列
idx_list = [idx_list[0][i] for i in range(idx_list.shape[1])]
score_list = []
name_list = []
for idx in idx_list:
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx)])
name = {value: key for key, value in self.index_dict.items()}[int(idx)]
score_list.append(score)
name_list.append(name)
print(name_list)
print(score_list)
#person_list = [name.split('_')[0] for name in name_list]
#person_set = list(set(person_list))
#person_num = len(person_set)
#print(person_num)
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx_list[0])])
thresh = float(thresh)
print(thresh)
if score > thresh:
knownflag = 1
name = name_list[0]
if self.knownum == 0:
self.knownum = 1
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime,
name),
save_croped)
idname.append(name) #当前帧中的已知访客name
print("欢迎" + name)
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
img_list = os.listdir(self.known_pic_path) # 返回指定的文件夹包含的文件或文件夹的名字的列表
knownlist = [item.split('.')[0] for item in img_list]
knownlist = [item.split('_')[1] for item in knownlist]
if name not in knownlist:
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime,
name),
save_croped)
idname.append(name) #当前帧中的已知访客name
self.knownum = self.knownum + 1
print("欢迎" + name)
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
unknownflag = 1
if self.unknownum == 0:
print("第一个未知人员")
currentunknownum = currentunknownum + 1
self.unknownum = 1
#self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime,
self.unknownum),save_croped)
self.unknownfeature = feature[np.newaxis, :]
else:
unthresh = 0.6
self.search_eign_unknown = Search_engin(self.unknownfeature) # 未知访客搜索
self.search_eign_unknown.train()
unknown_idx = self.search_eign_unknown.search(feature)
unknown_idx = [unknown_idx[0][i] for i in range(unknown_idx.shape[1])]
print(unknown_idx)
uscore = 1 - spatial.distance.cosine(feature, self.unknownfeature[int(unknown_idx[0])])
print(uscore)
if uscore < unthresh: # 当天第一次识别出该未知人员
self.unknownum = self.unknownum + 1
currentunknownum = currentunknownum + 1
#self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime,
self.unknownum), save_croped)
self.unknownfeature = np.vstack((self.unknownfeature, feature))
#print("第二个")
#print(time.strftime('%H:%M:%S', time.localtime(time.time())))
if knownflag == 1:
#print(idname)
currentknownum = len(idname) # 当前帧已知访客数量
#self.knownum = self.knownum + currentknownum
for i in range(currentknownum):
self.id_image = cv2.imread('./user_pic/{}.bmp'.format(idname[i]))
self.display_id_image(self.knownum)
if unknownflag == 1:
print("未知人总数:{}".format(self.unknownum))
# print("当前帧未知人数:{}".format(currentunknownum))
with open(self.unknownfeature_path, 'wb') as f:
self.unknownfeature = np.asarray(self.unknownfeature)
np.save(f, self.unknownfeature)
for i in range(currentunknownum):
self.id_image2 = cv2.imread('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime, self.unknownum))
self.display_id_image2(self.unknownum)
#print(time.strftime('%H:%M:%S', time.localtime(time.time())))
else:
web.write_result("未检测到人脸", 'red')
web.exec_()
except:
pass
else:
pass
class Ui_Face_Verification(object): #主界面
def __init__(self):
ext_model_path = './model/facenet/inception-ring-1024.pb'
#self.video_capture = cv2.VideoCapture(camera_Id)
#self.video_capture = cv2.VideoCapture(HKcam)
self.is_camera_on = True
self.id_image = None
self.id_image2 = None
self.id_image1_2 = None
self.probe_image = None
self.ID_label = 0
self.count = 0
self.ID_lib = {}
self.ID_name = {}
self.feature_data = None
self.index_dict = None
self.unknownum = 0 #当天未知人员总数
self.knownum = 0
#self.unknownfeature = np.asarray([]) #当天保存的未知访客的特征
self.datetime = datetime.now().strftime('%Y_%m_%d')
self.unknown_feature_read()
#self.persontime = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
self.naivedlib = NaiveDlib()
self.extractor = Extractor(ext_model_path, gpu_fraction=0)#gpu_fraction显存占用比例
temp = np.ones((5, 112, 96, 1))
self.extractor.extract_feature(im_arr=temp)
self.query = deque(maxlen=2)
self.search_train()
self.start()
self.start_verify()
def setupUi(self, Face_Verification):
Face_Verification.setObjectName(_fromUtf8("Face_Verification"))
# Face_Verification.setEnabled(True)
# Face_Verification.resize(1301, 810)
Face_Verification.setFixedSize(1300, 810) # 界面固定大小
Face_Verification.setStyleSheet(_fromUtf8("background-color: rgb(240, 248, 255);")) # 界面背景色
# Face_Verification.setStyleSheet(_fromUtf8("background-color: rgb(255, 222, 173);"))
self.centralwidget = QtGui.QWidget(Face_Verification)
self.centralwidget.setObjectName(_fromUtf8("centralwidget"))
self.horizontalLayoutWidget = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget.setGeometry(QtCore.QRect(20, 40, 131, 161))
self.horizontalLayoutWidget.setObjectName(_fromUtf8("horizontalLayoutWidget"))
self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)
self.horizontalLayout.setObjectName(_fromUtf8("horizontalLayout"))
self.ID_photo1 = QtGui.QLabel(self.horizontalLayoutWidget)
self.ID_photo1.setText(_fromUtf8(""))
self.ID_photo1.setObjectName(_fromUtf8("ID_photo1"))
self.ID_photo1.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout.addWidget(self.ID_photo1)
self.horizontalLayoutWidget_13 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_13.setGeometry(QtCore.QRect(1050, 10, 151, 151))
self.horizontalLayoutWidget_13.setObjectName(_fromUtf8("horizontalLayoutWidget_13"))
self.horizontalLayout_13 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_13)
self.horizontalLayout_13.setObjectName(_fromUtf8("horizontalLayout_13"))
self.logo = QtGui.QLabel(self.horizontalLayoutWidget_13)
self.logo.setText(_fromUtf8(""))
self.logo.setObjectName(_fromUtf8("logo"))
self.logo.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_13.addWidget(self.logo)
self.horizontalLayoutWidget_2 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(160, 40, 131, 161))
self.horizontalLayoutWidget_2.setObjectName(_fromUtf8("horizontalLayoutWidget_2"))
self.horizontalLayout_2 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_2)
self.horizontalLayout_2.setObjectName(_fromUtf8("horizontalLayout_2"))
self.ID_photo2 = QtGui.QLabel(self.horizontalLayoutWidget_2)
self.ID_photo2.setText(_fromUtf8(""))
self.ID_photo2.setObjectName(_fromUtf8("ID_photo2"))
self.ID_photo2.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_2.addWidget(self.ID_photo2)
self.horizontalLayoutWidget_3 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(300, 40, 131, 161))
self.horizontalLayoutWidget_3.setObjectName(_fromUtf8("horizontalLayoutWidget_3"))
self.horizontalLayout_3 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_3)
self.horizontalLayout_3.setObjectName(_fromUtf8("horizontalLayout_3"))
self.ID_photo3 = QtGui.QLabel(self.horizontalLayoutWidget_3)
self.ID_photo3.setText(_fromUtf8(""))
self.ID_photo3.setObjectName(_fromUtf8("ID_photo3"))
self.ID_photo3.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_3.addWidget(self.ID_photo3)
self.horizontalLayoutWidget_4 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(20, 210, 131, 161))
self.horizontalLayoutWidget_4.setObjectName(_fromUtf8("horizontalLayoutWidget_4"))
self.horizontalLayout_4 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_4)
self.horizontalLayout_4.setObjectName(_fromUtf8("horizontalLayout_4"))
self.ID_photo4 = QtGui.QLabel(self.horizontalLayoutWidget_4)
self.ID_photo4.setText(_fromUtf8(""))
self.ID_photo4.setObjectName(_fromUtf8("ID_photo4"))
self.ID_photo4.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_4.addWidget(self.ID_photo4)
self.horizontalLayoutWidget_5 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_5.setGeometry(QtCore.QRect(160, 210, 131, 161))
self.horizontalLayoutWidget_5.setObjectName(_fromUtf8("horizontalLayoutWidget_5"))
self.horizontalLayout_5 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_5)
self.horizontalLayout_5.setObjectName(_fromUtf8("horizontalLayout_5"))
self.ID_photo5 = QtGui.QLabel(self.horizontalLayoutWidget_5)
self.ID_photo5.setText(_fromUtf8(""))
self.ID_photo5.setObjectName(_fromUtf8("ID_photo5"))
self.ID_photo5.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_5.addWidget(self.ID_photo5)
self.horizontalLayoutWidget_6 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(300, 210, 131, 161))
self.horizontalLayoutWidget_6.setObjectName(_fromUtf8("horizontalLayoutWidget_6"))
self.horizontalLayout_6 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_6)
self.horizontalLayout_6.setObjectName(_fromUtf8("horizontalLayout_6"))
self.ID_photo6 = QtGui.QLabel(self.horizontalLayoutWidget_6)
self.ID_photo6.setText(_fromUtf8(""))
self.ID_photo6.setObjectName(_fromUtf8("ID_photo6"))
self.ID_photo6.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_6.addWidget(self.ID_photo6)
self.verticalLayoutWidget = QtGui.QWidget(self.centralwidget)
self.verticalLayoutWidget.setGeometry(QtCore.QRect(560, 170, 681, 551))
self.verticalLayoutWidget.setObjectName(_fromUtf8("verticalLayoutWidget"))
self.verticalLayout = QtGui.QVBoxLayout(self.verticalLayoutWidget)
self.verticalLayout.setObjectName(_fromUtf8("verticalLayout"))
self.Probe_photo = QtGui.QLabel(self.verticalLayoutWidget)
self.Probe_photo.setText(_fromUtf8(""))
self.Probe_photo.setObjectName(_fromUtf8("Probe_photo"))
self.Probe_photo.setAlignment(QtCore.Qt.AlignCenter)
self.verticalLayout.addWidget(self.Probe_photo)
self.horizontalLayoutWidget_7 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(20, 410, 131, 161))
self.horizontalLayoutWidget_7.setObjectName(_fromUtf8("horizontalLayoutWidget_7"))
self.horizontalLayout_7 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_7)
self.horizontalLayout_7.setObjectName(_fromUtf8("horizontalLayout_7"))
self.ID_photo1_2 = QtGui.QLabel(self.horizontalLayoutWidget_7) # 未知照片
self.ID_photo1_2.setText(_fromUtf8(""))
self.ID_photo1_2.setObjectName(_fromUtf8("ID_photo1_2"))
self.ID_photo1_2.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_7.addWidget(self.ID_photo1_2)
self.horizontalLayoutWidget_8 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_8.setGeometry(QtCore.QRect(160, 410, 131, 161))
self.horizontalLayoutWidget_8.setObjectName(_fromUtf8("horizontalLayoutWidget_8"))
self.horizontalLayout_8 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_8)
self.horizontalLayout_8.setObjectName(_fromUtf8("horizontalLayout_8"))
self.ID_photo1_3 = QtGui.QLabel(self.horizontalLayoutWidget_8)
self.ID_photo1_3.setText(_fromUtf8(""))
self.ID_photo1_3.setObjectName(_fromUtf8("ID_photo1_3"))
self.ID_photo1_3.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_8.addWidget(self.ID_photo1_3)
self.horizontalLayoutWidget_9 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(300, 410, 131, 161))
self.horizontalLayoutWidget_9.setObjectName(_fromUtf8("horizontalLayoutWidget_9"))
self.horizontalLayout_9 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_9)
self.horizontalLayout_9.setObjectName(_fromUtf8("horizontalLayout_9"))
self.ID_photo1_4 = QtGui.QLabel(self.horizontalLayoutWidget_9)
self.ID_photo1_4.setText(_fromUtf8(""))
self.ID_photo1_4.setObjectName(_fromUtf8("ID_photo1_4"))
self.ID_photo1_4.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_9.addWidget(self.ID_photo1_4)
self.horizontalLayoutWidget_10 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(20, 580, 131, 161))
self.horizontalLayoutWidget_10.setObjectName(_fromUtf8("horizontalLayoutWidget_10"))
self.horizontalLayout_10 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_10)
self.horizontalLayout_10.setObjectName(_fromUtf8("horizontalLayout_10"))
self.ID_photo1_5 = QtGui.QLabel(self.horizontalLayoutWidget_10)
self.ID_photo1_5.setText(_fromUtf8(""))
self.ID_photo1_5.setObjectName(_fromUtf8("ID_photo1_5"))
self.ID_photo1_5.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_10.addWidget(self.ID_photo1_5)
self.horizontalLayoutWidget_11 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_11.setGeometry(QtCore.QRect(160, 580, 131, 161))
self.horizontalLayoutWidget_11.setObjectName(_fromUtf8("horizontalLayoutWidget_11"))
self.horizontalLayout_11 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_11)
self.horizontalLayout_11.setObjectName(_fromUtf8("horizontalLayout_11"))
self.ID_photo1_6 = QtGui.QLabel(self.horizontalLayoutWidget_11)
self.ID_photo1_6.setText(_fromUtf8(""))
self.ID_photo1_6.setObjectName(_fromUtf8("ID_photo1_6"))
self.ID_photo1_6.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_11.addWidget(self.ID_photo1_6)
self.horizontalLayoutWidget_12 = QtGui.QWidget(self.centralwidget)
self.horizontalLayoutWidget_12.setGeometry(QtCore.QRect(300, 580, 131, 161))
self.horizontalLayoutWidget_12.setObjectName(_fromUtf8("horizontalLayoutWidget_12"))
self.horizontalLayout_12 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_12)
self.horizontalLayout_12.setObjectName(_fromUtf8("horizontalLayout_12"))
self.ID_photo1_7 = QtGui.QLabel(self.horizontalLayoutWidget_12)
self.ID_photo1_7.setText(_fromUtf8(""))
self.ID_photo1_7.setObjectName(_fromUtf8("ID_photo1_7"))
self.ID_photo1_7.setAlignment(QtCore.Qt.AlignCenter)
self.horizontalLayout_12.addWidget(self.ID_photo1_7)
self.label = QtGui.QLabel(self.centralwidget)
self.label.setGeometry(QtCore.QRect(20, 10, 111, 21))
font = QtGui.QFont()
font.setFamily(_fromUtf8("微软雅黑"))
font.setPointSize(10)
self.label.setFont(font)
self.label.setObjectName(_fromUtf8("label"))
self.label_2 = QtGui.QLabel(self.centralwidget)
self.label_2.setGeometry(QtCore.QRect(30, 380, 111, 21))
font = QtGui.QFont()
font.setFamily(_fromUtf8("微软雅黑"))
font.setPointSize(10)
self.label_2.setFont(font)
self.label_2.setObjectName(_fromUtf8("label_2"))
self.label_3 = QtGui.QLabel(self.centralwidget)
self.label_3.setGeometry(QtCore.QRect(760, 60, 261, 81))
font = QtGui.QFont()
font.setFamily(_fromUtf8("微软雅黑"))
font.setBold(1)
font.setPointSize(24)
self.label_3.setFont(font)
self.label_3.setObjectName(_fromUtf8("label_3"))
Face_Verification.setCentralWidget(self.centralwidget)
self.menubar = QtGui.QMenuBar(Face_Verification)
self.menubar.setGeometry(QtCore.QRect(0, 0, 1366, 23))
self.menubar.setObjectName(_fromUtf8("menubar"))
self.menu = QtGui.QMenu(self.menubar)
self.menu.setObjectName(_fromUtf8("menu"))
self.menu2 = QtGui.QMenu(self.menubar)
self.menu2.setObjectName(_fromUtf8("menu2"))
Face_Verification.setMenuBar(self.menubar)
self.statusbar = QtGui.QStatusBar(Face_Verification)
self.statusbar.setObjectName(_fromUtf8("statusbar"))
Face_Verification.setStatusBar(self.statusbar)
self.action_check = QtGui.QAction(Face_Verification)
self.action_check.setObjectName(_fromUtf8("action_check"))
self.action_thresh = QtGui.QAction(Face_Verification)
self.action_thresh.setObjectName(_fromUtf8("action_thresh"))
self.action_camera_on = QtGui.QAction(Face_Verification)
self.action_camera_on.setObjectName(_fromUtf8("action_camera_on"))
self.action_camera_off = QtGui.QAction(Face_Verification)
self.action_camera_off.setObjectName(_fromUtf8("action_camera_off"))
self.menu.addAction(self.action_check)
self.menu.addAction(self.action_thresh)
self.menubar.addAction(self.menu.menuAction())
self.menu2.addAction(self.action_camera_on)
self.menu2.addAction(self.action_camera_off)
self.menubar.addAction(self.menu2.menuAction())
self.retranslateUi(Face_Verification)
QtCore.QMetaObject.connectSlotsByName(Face_Verification)
def retranslateUi(self, Face_Verification):
# _translate = QtCore.QCoreApplication.translate
Face_Verification.setWindowTitle(_translate("Face_Verification", "智擎信息系统（上海）有限公司", None))
# Face_Verification.setWindowTitle(_translate("Face_Verification", "MainWindow", None))
self.label.setText("已登记访客")
self.label_2.setText("未知访客")
#self.label_3.setText("智擎信息系统")
self.label_3.setText(_translate("Face_Verification",
"<html><head/><body><p align=\"center\"><span style=\" font-size:24pt;\">智擎信息系统</span></p></body></html>",
None))
#self.menu.setTitle(_translate("Face_Verification", "信息查询", None))
#self.menu2.setTitle(_translate("Face_Verification", "访客登记", None))
#self.action_known.setText(_translate("Face_Verification", "已知访客", None))
#self.action_unknown.setText(_translate("Face_Verification", "未知访客", None))
self.menu.setTitle("系统管理")
self.action_check.setText("信息查询")
self.action_check.setToolTip("信息查询")
self.action_thresh.setText("阈值设定")
self.menu2.setTitle("摄像头管理")
self.action_camera_on.setText("开摄像头")
self.action_camera_off.setText("关摄像头")
pixMap1 = QtGui.QPixmap("ID_test.jpg")
self.ID_photo1.setScaledContents(True)
self.ID_photo2.setScaledContents(True)
self.ID_photo1.setPixmap(pixMap1)
self.ID_photo1_2.setScaledContents(True)
self.ID_photo1_3.setScaledContents(True)
self.ID_photo1_4.setScaledContents(True)
self.ID_photo1_5.setScaledContents(True)
self.ID_photo1_6.setScaledContents(True)
self.ID_photo1_7.setScaledContents(True)
self.ID_photo3.setScaledContents(True)
self.ID_photo4.setScaledContents(True)
self.ID_photo5.setScaledContents(True)
self.ID_photo6.setScaledContents(True)
pixmap2 = QtGui.QPixmap("logo.png")
self.logo.setScaledContents(True)
self.logo.setPixmap(pixmap2)
def display_id_image(self, i):# 显示已知访客照片，一次最多显示六张
image = cv2.cvtColor(self.id_image, cv2.COLOR_BGR2RGB)
image = QtGui.QImage(image, image.shape[1],\
image.shape[0], image.shape[1] * 3,QtGui.QImage.Format_RGB888)
pix = QtGui.QPixmap(image)
i = int(i % 6)
if i == 0:
self.ID_photo1.setPixmap(pix)
if i == 1:
self.ID_photo2.setPixmap(pix)
if i == 2:
self.ID_photo3.setPixmap(pix)
if i == 3:
self.ID_photo4.setPixmap(pix)
if i == 4:
self.ID_photo5.setPixmap(pix)
if i == 5:
self.ID_photo6.setPixmap(pix)
def display_id_image2(self, i): # 显示未知访客照片，一次最多显示六张
image = cv2.cvtColor(self.id_image2, cv2.COLOR_BGR2RGB)
image = QtGui.QImage(image, image.shape[1],\
image.shape[0], image.shape[1] * 3,QtGui.QImage.Format_RGB888)
pix = QtGui.QPixmap(image)
i = int(i % 6)
if i == 0:
self.ID_photo1_2.setPixmap(pix)
if i == 1:
self.ID_photo1_3.setPixmap(pix)
if i == 2:
self.ID_photo1_4.setPixmap(pix)
if i == 3:
self.ID_photo1_5.setPixmap(pix)
if i == 4:
self.ID_photo1_6.setPixmap(pix)
if i == 5:
self.ID_photo1_7.setPixmap(pix)
def search_train(self):#已知访客搜索初始化 后面补充一个一天的清空时加入这个为了人员信息管理时的更新
with open('./data/index_enter.pkl', 'rb') as f:
self.index_dict = pkl.load(f)
with open('./data/database_enter.npy', 'rb') as f:
self.feature_data = np.load('./data/database_enter.npy')
self.search_eign = Search_engin(self.feature_data)
self.search_eign.train()
def unknown_feature_read(self):#重启后当天的数据仍然保存（已知访客人数也在这里保存）
self.datetime = datetime.now().strftime('%Y_%m_%d')
self.unknownfeature_path = './data/unknown_feature.npy'
self.unknown_pic_path = './image_saved/{}/unknown'.format(self.datetime)
self.known_pic_path = './image_saved/{}/known'.format(self.datetime)
if os.path.exists(self.unknownfeature_path) and os.path.exists(self.unknown_pic_path):
try:
self.unknownfeature = np.load(self.unknownfeature_path)
self.unknownum = len(os.listdir(self.unknown_pic_path))
except:
self.unknownfeature = np.asarray([])
else:
self.unknownfeature = np.asarray([])
self.unknownum = 0
if os.path.exists(self.known_pic_path):
self.knownum = len(os.listdir(self.known_pic_path))
else:
self.knownum = 0
#当天数据清除和人数保存
def today_clean(self, datetime): #旧日期
number = self.unknownum + self.knownum
with open('./image_saved/{}/number.txt'.format(datetime), 'w+') as f:
f.write(str(number))
if os.path.exists(self.unknownfeature_path):
os.remove(self.unknownfeature_path)
self.search_train()
self.knownum = 0
self.unknownum = 0
self.unknownfeature = np.asarray([])
# 识别比对
def verify(self, thresh):
global VIDEO_IMAGE
global isPass
knownflag = 0
unknownflag = 0
currentunknownum = 0
currentknownum = 0
idname = [] # 可显示id照片的编号列表
currentDate = datetime.now().strftime('%Y_%m_%d')
currentTime = datetime.now().strftime('%Y-%m-%d %H-%M-%S')
if currentDate != self.datetime: #新日期触发
self.today_clean(self.datetime)
self.datetime = currentDate
web = Web_Browser()
web.setModal(False)
web.setWindowTitle(_translate("Face_Verification", "比对结果", None))
# if self.pic_time != None and (datetime.datetime.now() - self.pic_time).seconds > pic_time:
# self.image_clear()
for i in range(probe_image.qsize()):
image1 = probe_image.get()
#image1 = cv2.imread('./card/2.jpg') # 加载图片测试
if image1 is not None:
print('get image')
image1 = cv2.flip(image1, 1)
width = int(image1.shape[1] / 2)
height = int(image1.shape[0] / 2)
image = cv2.resize(image1.copy(), (width, height))
try:
#total_start = time.time()
bboxs = self.naivedlib.getALLFaces(image)
#bbox_end = time.time()
print('bbox detect took ')
bboxs = [dlib.rectangle(int(bbox.left() * downsample_ratio), int(bbox.top() * downsample_ratio),
int(bbox.right() * downsample_ratio), int(bbox.bottom() * downsample_ratio))
for bbox in bboxs]
facenum = len(bboxs)
#print(facenum)#人脸数
# index_list = []
#idname = [] # 可显示id照片的编号列表
if bboxs is not None:
print(time.strftime('%H:%M:%S', time.localtime(time.time())))
for bbox in bboxs:
# 对每个人脸进行操作
print('bbox is detected')
query = []
left_eye, right_eye = self.naivedlib.get_eyes(image1, bbox)
start = time.time()
save_croped, crop_image = crop_rotate_part(image1[:, :, ::-1], bbox, left_eye, right_eye,
bbox.width() * 0.895)
save_croped = cv2.cvtColor(save_croped, cv2.COLOR_BGR2RGB)
# bbox_temp = [bbox.left(),bbox.top(),bbox.right(),bbox.bottom()]
# crop_image = crop_only(image1,bbox_temp)
# cv2.imwrite('image.jpg',crop_image)
end = time.time()
print('\tpreprocess took {}'.format(end - start))
flip_image = cv2.flip(crop_image.copy(), 1)
crop_image = proc_img(crop_image, is_whiten=False)
flip_image = proc_img(flip_image, is_whiten=False)
query.append(crop_image[0])
query.append(flip_image[0])
prob_image = np.asarray(query)
start = time.time()
feature = self.extractor.extract_feature(prob_image)
end = time.time()
print('\textract feature took {}'.format(end - start))
feature = feature / np.linalg.norm(feature)
idx_list = self.search_eign.search(feature) # 获取搜索后的排列
idx_list = [idx_list[0][i] for i in range(idx_list.shape[1])]
score_list = []
name_list = []
for idx in idx_list:
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx)])
name = {value: key for key, value in self.index_dict.items()}[int(idx)]
score_list.append(score)
name_list.append(name)
print(name_list)
print(score_list)
#person_list = [name.split('_')[0] for name in name_list]
#person_set = list(set(person_list))
#person_num = len(person_set)
#print(person_num)
score = 1 - spatial.distance.cosine(feature, self.feature_data[int(idx_list[0])])
thresh = float(thresh)
print(thresh)
if score > thresh:
knownflag = 1
name = name_list[0]
if self.knownum == 0:
self.knownum = 1
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime,
name),
save_croped)
idname.append(name) #当前帧中的已知访客name
print("欢迎" + name)
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
img_list = os.listdir(self.known_pic_path) # 返回指定的文件夹包含的文件或文件夹的名字的列表
knownlist = [item.split('.')[0] for item in img_list]
knownlist = [item.split('_')[1] for item in knownlist]
if name not in knownlist:
cv2.imwrite('./image_saved/{}/known/{}_{}.jpg'.format(currentDate, currentTime,
name),
save_croped)
idname.append(name) #当前帧中的已知访客name
self.knownum = self.knownum + 1
print("欢迎" + name)
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
else:
unknownflag = 1
if self.unknownum == 0:
print("第一个未知人员")
currentunknownum = currentunknownum + 1
self.unknownum = 1
#self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
if not os.path.exists('./image_saved/{}'.format(currentDate)):
os.mkdir('./image_saved/{}'.format(currentDate))
os.mkdir('./image_saved/{}/unknown'.format(currentDate))
os.mkdir('./image_saved/{}/known'.format(currentDate))
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime,
self.unknownum),save_croped)
self.unknownfeature = feature[np.newaxis, :]
else:
unthresh = 0.6
self.search_eign_unknown = Search_engin(self.unknownfeature) # 未知访客搜索
self.search_eign_unknown.train()
unknown_idx = self.search_eign_unknown.search(feature)
unknown_idx = [unknown_idx[0][i] for i in range(unknown_idx.shape[1])]
print(unknown_idx)
uscore = 1 - spatial.distance.cosine(feature, self.unknownfeature[int(unknown_idx[0])])
print(uscore)
if uscore < unthresh: # 当天第一次识别出该未知人员
self.unknownum = self.unknownum + 1
currentunknownum = currentunknownum + 1
#self.unknownlist[self.unknownum] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
cv2.imwrite('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime,
self.unknownum), save_croped)
self.unknownfeature = np.vstack((self.unknownfeature, feature))
#print("第二个")
#print(time.strftime('%H:%M:%S', time.localtime(time.time())))
if knownflag == 1:
#print(idname)
currentknownum = len(idname) # 当前帧已知访客数量
#self.knownum = self.knownum + currentknownum
for i in range(currentknownum):
self.id_image = cv2.imread('./user_pic/{}.bmp'.format(idname[i]))
self.display_id_image(self.knownum)
if unknownflag == 1:
print("未知人总数:{}".format(self.unknownum))
# print("当前帧未知人数:{}".format(currentunknownum))
with open(self.unknownfeature_path, 'wb') as f:
self.unknownfeature = np.asarray(self.unknownfeature)
np.save(f, self.unknownfeature)
for i in range(currentunknownum):
self.id_image2 = cv2.imread('./image_saved/{}/unknown/{}_{}.jpg'.format(currentDate, currentTime, self.unknownum))
self.display_id_image2(self.unknownum)
#print(time.strftime('%H:%M:%S', time.localtime(time.time())))
else:
web.write_result("未检测到人脸", 'red')
web.exec_()
except:
pass
else:
pass
def display_probe_image(self):
#ret, image1 = self.video_capture.read()
if VIDEO_IMAGE.qsize() != 0:
for i in range(VIDEO_IMAGE.qsize()):
image1 = VIDEO_IMAGE.get()
probe_image.put(image1)
self.probe_image = image1.copy()
try:
#bbox = self.naivedlib.getLargestFaceBoundingBox(image1)
bboxs = self.naivedlib.getALLFaces(image1)
image1 = self.naivedlib.drawbboxs(image1, bboxs)
except:
pass
image = cv2.cvtColor(image1, cv2.COLOR_BGR2RGB)
image = cv2.resize(image, (320 * 2, 240 * 2))
# image = cv2.flip(image,1)
image = QtGui.QImage(image, image.shape[1], \
image.shape[0], image.shape[1] * 3, QtGui.QImage.Format_RGB888)
pix = QtGui.QPixmap.fromImage(image)
self.Probe_photo.setPixmap(pix)
else:
self.probe_image = None
self.Probe_photo.setText(_translate("Face_Verification", "未读取到图片", None))
self.Probe_photo.setStyleSheet('color: red')
def start(self):
self.timer = QtCore.QTimer()
self.timer.timeout.connect(self.display_probe_image)
self.timer.start(1000./24)
def start_verify(self):
self.timer3= QtCore.QTimer()
global thresh
self.timer3.timeout.connect(lambda: self.verify(thresh))
self.timer3.start(1000)#1000ms==1s进行一次识别