def start():
while True:
start_app = input("""
1 Start
2 Registration in Credo
3 Send old detection files
-- Press h to get help --
-- Press e to exit --""" + '\n')
if start_app == "1":
break
elif start_app == "h":
os.system("reset")
help_file = open(local_path + "/help.text", 'r')
context = help_file.read()
print(context)
continue
elif start_app == "2":
os.system("reset")
registration()
elif start_app == "3":
os.system("reset")
old_detection_file()
print("Done")
continue
elif start_app == "e":
exit()
else:
continue
def start_detection():
global last_ping
global last_detection_time
last_ping = linux_time()
last_detection_time = 0
cam_read = cv2.VideoCapture(int(cam_number))
sample_number = sample_save = 0
print("Start sampling...")
time.sleep(2)
os.system("reset")
while True:
try:
time_dat = datetime.now().strftime("%Y-%m-%d %H:%M:%S:%f")[:-3]
detection_time = linux_time()
sample_number += 1
ret, frame = cam_read.read()
data = np.array(frame)
print('\r',
"Sample:",
sample_number,
"|",
"Saved",
sample_save,
"|",
"Press Ctrl + c to exit",
end='')
time.sleep(0.000001)
counter = 0
xy_coordinates = []
if np.max(data) >= int(threshold):
all_coordinate_x = list(np.where(data >= int(threshold))[1])
all_coordinate_y = list(np.where(data >= int(threshold))[0])
all_ziped = list(zip(all_coordinate_x, all_coordinate_y))
all_ziped.sort()
while counter < len(all_ziped):
if len(all_ziped) == 1:
xy_coordinates.append(all_ziped[0])
break
elif counter == 0:
xy_coordinates.append(all_ziped[counter])
counter += 1
elif all_ziped[counter][0] - 10 < all_ziped[counter -
1][0]:
counter += 1
else:
xy_coordinates.append(all_ziped[counter])
counter += 1
multi_detection = 0
for x, y in xy_coordinates:
if x >= 11 and y >= 11:
img_crop = data[y - 10:y + 10, x - 10:x + 10]
r = 50.0 / img_crop.shape[1]
dim = (50, int(img_crop.shape[0] * r))
sample_save = sample_save + 1
if img_crop is None:
pass
else:
print(time_dat,
sample_number,
x,
y,
round(np.average(data), 4),
np.max(data),
sep=',',
file=open(str(path) + "/Report.txt", "a"))
img_zoom = cv2.resize(img_crop,
dim,
interpolation=cv2.INTER_AREA)
gray_img_zoom = cv2.cvtColor(
img_zoom, cv2.COLOR_BGR2GRAY)
cv2.imwrite(
str(path) + "/" + str(time_dat) +
" Sample no. %i:%i.png" %
(sample_number, multi_detection),
gray_img_zoom)
picture = open(
str(path) + "/" + str(time_dat) +
" Sample no. %i:%i.png" %
(sample_number, multi_detection), 'rb')
picture_read = picture.read()
base64_picture = str(
base64.b64encode(picture_read))[2:]
credo_detection(base64_picture, int(x), int(y),
detection_time)
last_detection_time = linux_time()
old_detection_file()
multi_detection += 1
else:
pass
if linux_time() - last_ping >= 600000:
credo_ping(last_ping, last_detection_time)
last_ping = linux_time()
except KeyboardInterrupt:
cam_read.release()
exit()
def start_detection():
global last_ping
global last_detection_time
last_ping = linux_time()
last_detection_time = 0
cam_read = cv2.VideoCapture(int(cam_number))
sample_number = sample_save = 0
print("Start sampling...")
time.sleep(2)
os.system("reset")
while True:
try:
time_dat = datetime.now().strftime("%Y-%m-%d %H:%M:%S:%f")[:-3]
sample_number += 1
ret, frame = cam_read.read()
data = np.array(frame)
print('\r',
"Sample:",
sample_number,
"|",
"Saved",
sample_save,
"|",
"Press Ctrl + c to exit",
end='')
time.sleep(0.000001)
if np.max(data) >= int(threshold):
all_coordinate_x = (np.where(data == np.max(data))[1])
all_coordinate_y = (np.where(data == np.max(data))[0])
chosen_coordinate_x = all_coordinate_x[0] - 10
chosen_coordinate_y = all_coordinate_y[0] - 10
if chosen_coordinate_x >= 11 and chosen_coordinate_y >= 11:
img_crop = data[chosen_coordinate_y:chosen_coordinate_y +
20,
chosen_coordinate_x:chosen_coordinate_x +
20]
r = 50.0 / img_crop.shape[1]
dim = (50, int(img_crop.shape[0] * r))
sample_save = sample_save + 1
if img_crop is None:
pass
else:
print(time_dat,
sample_number,
chosen_coordinate_x,
chosen_coordinate_y,
round(np.average(data), 4),
np.max(data),
sep=',',
file=open(str(path) + "/Report.txt", "a"))
img_zoom = cv2.resize(img_crop,
dim,
interpolation=cv2.INTER_AREA)
gray_img_zoom = cv2.cvtColor(img_zoom,
cv2.COLOR_BGR2GRAY)
cv2.imwrite(
str(path) + "/" + str(time_dat) +
" Sample no. %i.png" % sample_number,
gray_img_zoom)
picture = open(
str(path) + "/" + str(time_dat) +
" Sample no. %i.png" % sample_number, 'rb')
picture_read = picture.read()
base64_picture = str(
base64.b64encode(picture_read))[2:]
credo_detection(base64_picture,
int(chosen_coordinate_x),
int(chosen_coordinate_y))
last_detection_time = linux_time()
old_detection_file()
else:
pass
if linux_time() - last_ping >= 600000:
credo_ping(last_ping, last_detection_time)
last_ping = linux_time()
except KeyboardInterrupt:
cam_read.release()
exit()