def gen(fr):
detector = object_detector.ObjectDetector(
'ssd_mobilenet_v1_coco_2017_11_17')
#detector = ObjectDetector('mask_rcnn_inception_v2_coco_2018_01_28')
#detector = ObjectDetector('pet', label_file='data/pet_label_map.pbtxt')
#cam = camera.VideoCamera()
retry_cnt = 0
while True:
try:
frame, face_result_list = fr.get_frame_live()
#frame = cam.get_frame()
frame, obj_detect_dict = detector.detect_objects_live(
frame)
self.buffer_handle(face_result_list, obj_detect_dict)
ret, jpg = cv2.imencode('.jpg', frame)
jpg_bytes = jpg.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpg_bytes +
b'\r\n\r\n')
except:
try:
time.sleep(1)
if retry_cnt > 5:
break
fr = face_recog.FaceRecog()
except:
retry_cnt += 1
def video_feed():
return Response(gen(face_recog.FaceRecog()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_feed():
time.sleep(3)
print('3초후 시작')
return Response(gen(face_recog.FaceRecog()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def func(face_recog_m, detector):
retry_cnt = 0
insert_flag = False
insert_priv_time = time.time()
imwrite_flag = False
img_write_priv_time = time.time()
while True:
now_date = datetime.datetime.now()
self.now_date = now_date
now_str = now_date.strftime("%Y%m%d%H%M%S")
curr_time = time.time()
# db 입력 간격 측정
if curr_time - insert_priv_time >= self.db_insert_term:
insert_priv_time = curr_time
insert_flag = True
else:
insert_flag = False
# 이미지 저장 간격 측정
if curr_time - img_write_priv_time >= self.img_write_gap:
img_write_priv_time = curr_time
imwrite_flag = True
else:
imwrite_flag = False
try:
frame, face_result_list = face_recog_m.get_frame_live()
frame, obj_detection_dict = detector.detect_objects_live(
frame)
if imwrite_flag:
# 10 분마다 이미지파일 쓰기
img_write_file = self.imwrite_path + now_str + ".jpg"
cv2.imwrite(img_write_file, frame)
self.img_file_queue.put(img_write_file)
print("write img: ", img_write_file)
# 이미지 파일 개수가 1000개 이상일때 삭제
if self.img_file_queue.qsize() > self.max_img_file_cnt:
del_img_file = self.img_file_queue.get()
os.remove(del_img_file)
print("remove img: ", del_img_file)
# DB에서 2시간 이전의 데이터 삭제
self.delete_outdated_data(now_date)
for face_result in face_result_list:
face_corr = face_result[0]
face_name = face_result[1]
self.current_buffer.append((now_date, face_name))
if insert_flag:
val = (now_str, face_name, str(face_corr))
self.insert_db(val)
print("insert ", val)
for item in obj_detection_dict:
try:
obj_corr = item
class_str = obj_detection_dict[item][0]
class_list = class_str.split()
obj_class = class_list[0][:-1]
obj_score = int(class_list[1][:-1])
self.current_buffer.append((now_date, obj_class))
if insert_flag:
val = (now_str, obj_class, str(obj_corr))
self.insert_db(val)
print("insert ", val)
except:
pass
origin_len = len(self.current_buffer)
for _ in range(origin_len):
if self.check_current_max(now_date):
del self.current_buffer[0]
self.frame = frame
self.frame_cnt += 1
except Exception as err:
print(err)
try:
face_recog_m = face_recog.FaceRecog()
except:
retry_cnt += 1
if retry_cnt > 5:
break
def run_video(self):
print("run video")
import camera
face_recog_m = face_recog.FaceRecog()
detector = ObjectDetector('ssd_mobilenet_v1_coco_2017_11_17')
print("known faces: ", face_recog_m.known_face_names)
# Using OpenCV to capture from device 0. If you have trouble capturing
# from a webcam, comment the line below out and use a video file
# instead.
def func(face_recog_m, detector):
retry_cnt = 0
insert_flag = False
insert_priv_time = time.time()
imwrite_flag = False
img_write_priv_time = time.time()
while True:
now_date = datetime.datetime.now()
self.now_date = now_date
now_str = now_date.strftime("%Y%m%d%H%M%S")
curr_time = time.time()
# db 입력 간격 측정
if curr_time - insert_priv_time >= self.db_insert_term:
insert_priv_time = curr_time
insert_flag = True
else:
insert_flag = False
# 이미지 저장 간격 측정
if curr_time - img_write_priv_time >= self.img_write_gap:
img_write_priv_time = curr_time
imwrite_flag = True
else:
imwrite_flag = False
try:
frame, face_result_list = face_recog_m.get_frame_live()
frame, obj_detection_dict = detector.detect_objects_live(
frame)
if imwrite_flag:
# 10 분마다 이미지파일 쓰기
img_write_file = self.imwrite_path + now_str + ".jpg"
cv2.imwrite(img_write_file, frame)
self.img_file_queue.put(img_write_file)
print("write img: ", img_write_file)
# 이미지 파일 개수가 1000개 이상일때 삭제
if self.img_file_queue.qsize() > self.max_img_file_cnt:
del_img_file = self.img_file_queue.get()
os.remove(del_img_file)
print("remove img: ", del_img_file)
# DB에서 2시간 이전의 데이터 삭제
self.delete_outdated_data(now_date)
for face_result in face_result_list:
face_corr = face_result[0]
face_name = face_result[1]
self.current_buffer.append((now_date, face_name))
if insert_flag:
val = (now_str, face_name, str(face_corr))
self.insert_db(val)
print("insert ", val)
for item in obj_detection_dict:
try:
obj_corr = item
class_str = obj_detection_dict[item][0]
class_list = class_str.split()
obj_class = class_list[0][:-1]
obj_score = int(class_list[1][:-1])
self.current_buffer.append((now_date, obj_class))
if insert_flag:
val = (now_str, obj_class, str(obj_corr))
self.insert_db(val)
print("insert ", val)
except:
pass
origin_len = len(self.current_buffer)
for _ in range(origin_len):
if self.check_current_max(now_date):
del self.current_buffer[0]
self.frame = frame
self.frame_cnt += 1
except Exception as err:
print(err)
try:
face_recog_m = face_recog.FaceRecog()
except:
retry_cnt += 1
if retry_cnt > 5:
break
th = threading.Thread(target=func, args=(face_recog_m, detector))
th.daemon = True
th.start()
return th
def make_error(status_code, sub_code, message, action):
response = jsonify({
'status': status_code,
'sub_code': sub_code,
'message': message,
'action': action
})
response.status_code = status_code
return response
app = CustomFlask(__name__)
cors = CORS(app)
faceObject = face_recog.FaceRecog()
@app.route('/')
def index():
return render_template('index.html')
@app.route('/hello')
def hello():
return "hello"
@app.route('/register')
def get_register():
return render_template('register.html')
print("get_data.py execute...")
#my_face = face_recog.FaceRecog()
kosta_student = {
'minji': '박민지',
'chaeryeong': '이채령',
'iu': '이지은',
'Chris': '크리스 햄스워스',
'Liam': '리암 햄스워스'
}
open_message = "출석확인 완료"
state_message = "입실확인 완료"
close_messate = "퇴칠확인 완료"
today = GetTime()
today_data = GetData()
face_cam = face_recog.FaceRecog()
while True:
get_date = str(today.today_object)
#print("get_date", get_date, type(get_date)) # get_date 2021-04-28 <class 'str'>
get_hour = today.get_now().hour
get_minute = today.get_now().minute
get_time = str(get_hour) + ":" + str(get_minute)
#print("get_time", get_time, type(get_time)) #get_time 16:44 <class 'str'>
#print(get_hour,"시 ", get_minute,"분") # 16 시 44 분
face_frame = face_cam.get_frame()
cv2.imshow("Frame", face_frame)
count = []
if face_cam.face_names:
name = face_cam.face_names
#print("%0.3f, %0.3f, %0.3f sec" % (time2 - time1, time3 - time2, time4 - time3))
return frame, rtn_dict
def get_jpg_bytes(self):
frame = self.get_frame()
# We are using Motion JPEG, but OpenCV defaults to capture raw images,
# so we must encode it into JPEG in order to correctly display the
# video stream.
ret, jpg = cv2.imencode('.jpg', frame)
return jpg.tobytes()
if __name__ == '__main__':
import camera
face_recog = face_recog.FaceRecog()
print(face_recog.known_face_names)
detector = ObjectDetector('ssd_mobilenet_v1_coco_2017_11_17')
#detector = ObjectDetector('mask_rcnn_inception_v2_coco_2018_01_28')
#detector = ObjectDetector('pet', label_file='data/pet_label_map.pbtxt')
# Using OpenCV to capture from device 0. If you have trouble capturing
# from a webcam, comment the line below out and use a video file
# instead.
cam = camera.VideoCamera()
print("press `q` to quit")
while True:
frame, face_result_list = face_recog.get_frame_live()
#frame = cv2.resize(frame, (640, 480))
# Only existed path is allowed
assert os.path.exists(args.train)
print('Train Path :: ', args.train)
train_path = args.train
assert os.path.exists(args.test)
print('Test Path :: ', args.test)
test_path = args.test
# Set window
winName = 'Frame'
cv.namedWindow(winName, cv.WINDOW_NORMAL)
# --image option process
if args.image:
helmet = helmet.helmet_detection()
face_recog = face_recog.FaceRecog(train_path)
for img in os.listdir(test_path):
# Extract unknown image list from directory
img_path = test_path + '/' + img
image_file = cv.imread(img_path)
small_frame = cv.resize(image_file, (0, 0), fx=0.25, fy=0.25)
face_recog_result = face_recog.get_frame(small_frame)
helmet_result = helmet.get_detection(frame=small_frame,
copy_frame=face_recog_result)
# show the frame
cv.imshow(winName, helmet_result)
key = cv.waitKey(2000) & 0xFF
# if the `q` key was pressed, break from the loop