async def _get(url, JSON, original=False, once=False):
start_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
print("start " + start_time)
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
req = await response.text()
get_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S.%f')
print("req " + get_time)
eel.info(
"要求已得到",
"送出時間:" + start_time + "\n取得時間:" + get_time,
"console",
)
if (JSON == True):
try:
req = json.loads(req)
except:
print("error!req is not JSON\n")
pass
if (not once):
if (original != False):
data.append({"req": req, "org": original})
else:
data.append({"req": req})
else: #once
if (original != False):
return {"req": req, "org": original}
else:
return req
def handleinput(name):
#name = input("Enter the classifier name\n")
path = "images/" + name
if not os.path.isdir('images'):
os.mkdir('images')
try:
os.mkdir(path)
print("Folder created for : ", name, "\n")
except:
pass
cap = cv2.VideoCapture(0)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))
eel.info("Press Q to stop taking pictures")
while (cap.isOpened()):
ret, frame = cap.read()
if ret == True:
frame = cv2.flip(frame, 1)
out.write(frame)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
out.release()
cv2.destroyAllWindows()
vidcap = cv2.VideoCapture('output.avi')
success, image = vidcap.read()
count = 0
success = True
while success:
success, image = vidcap.read()
if (success == True):
cv2.imwrite('images/' + name + '/frame%d.jpg' % count,
image) # save frame as JPEG file
print('Read a new frame: ', success)
count += 1
else:
pass # Expose this function to Javascript
eel.info("succesfully saved for " + name)
def detect_faces():
print('detection started')
eel.info("Press ESC to stop")
size = 4
webcam = cv2.VideoCapture(0)
while True:
(rval, im) = webcam.read()
im = cv2.flip(im, 1, 0)
mini = cv2.resize(im,
(int(im.shape[1] / size), int(im.shape[0] / size)))
cv2.imwrite('testimage.jpg', im)
testimage = "testimage.jpg"
text = label_image.main(testimage)
text = text.title()
font = cv2.FONT_HERSHEY_TRIPLEX
cv2.putText(im, text, (100, 100), font, 2, (0, 255, 0), 2)
cv2.imshow('Capture', im)
key = cv2.waitKey(10)
if key == 27:
break
def train_images():
eel.info("Seat Back and wait.....")
eel.mSpinner()
try:
os.system(
'python3 retrain.py --output_graph=retrained_graph.pb --output_labels=retrained_labels.txt --architecture=MobileNet_1.0_224 --image_dir=images'
)
eel.info("Training is completed")
eel.mSpinner()
eel.mAddTick()
except:
eel.info("connect to internet..")
for name, file in mods.items():
globals()[name] = file
loaded_time = time.process_time()
#================================================
_app_is_done = True
main.start()
info("all done")
load_time = str((done_time - start_time) * 1000)
all_done_time = str((loaded_time - start_time) * 1000)
eel.sleep(3)
eel.info(
"調試訊息", '啟動時間:' + str(load_time) + "ms\n總加載時間:" + str(all_done_time) +
"ms\n使用端口:" + str(ge["port"]), "console")
while True:
#設置定時執行
eel.sleep(15)
#設置config索引
user_path = path + "data/user_config/"
config_users_list = os.listdir(user_path)
app_users_list = list(main.app_setting("user_config_index").values())
if (config_users_list != app_users_list):
print("set user config index")
index_file = {}
for account in config_users_list:
def login(steamid, lock=False, _app=False, force=False):
eel.info("使用模擬登入",
"steamid:" + steamid + "\n強制模式:" + ("是" if force else "否"),
"console")
acc = call_info(steamid)
if (force == False and (steamid in get_client_users())):
eel.info("模式切換", "偵測到快取模式\n轉為快取模式", "console")
auto_login(steamid, acc["name"], lock)
return
if (acc == False):
eel.info("無帳號", "", "error")
if (lock != False):
lock.release()
return "no_account"
key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, "SOFTWARE\Valve\Steam", 0,
winreg.KEY_QUERY_VALUE)
exe, t = winreg.QueryValueEx(key, "SteamExe")
winreg.CloseKey(key)
si = subprocess.STARTUPINFO()
si.dwFlags |= subprocess.STARTF_USESHOWWINDOW
if (_app == False): #如果沒有到拾取app
eel.info("關閉steam", "", "console")
close_steam(exe, si)
# str replace
password = str.replace(acc["password"], "{", "{{}")
password = str.replace(password, " ", "{SPACE}")
password = str.replace(password, "+", "{+}")
password = str.replace(password, "^", "{^}")
password = str.replace(password, "%", "{%}")
# set RememberPassword
key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, "SOFTWARE\Valve\Steam", 0,
winreg.KEY_SET_VALUE)
winreg.SetValueEx(key, "RememberPassword", 0, winreg.REG_DWORD, 0x00000001)
winreg.SetValueEx(key, "AutoLoginUser", 0, winreg.REG_SZ, "")
winreg.CloseKey(key)
# auto login
if (_app == False):
app = APP().start(exe)
else:
app = _app
login_gui = app.window(title_re='Steam [^Guard].*',
class_name='vguiPopupWindow')
try:
login_gui.wait("ready", 30)
except timings.TimeoutError:
eel.info("等待超時", "", "console")
del app
if (lock != False):
lock.release()
return "error"
eel.info("自動登入", "登入頁面 已就緒\n開始自動輸入", "console")
login_gui.set_focus()
sleep(.1)
if (_app == False):
eel.info("自動輸入名稱 [未輸入名稱]", "", "console")
keyboard.send_keys(acc["name"] + """{TAB}""")
eel.info("自動輸入密碼", "", "console")
keyboard.send_keys(password)
keyboard.send_keys("""{TAB}{ENTER}""")
if (acc["se"] == False): #guard
eel.info("無guard", "跳過guard登入頁面", "console")
else:
eel.info("等待guard", "已添加guard\n自動輸入guard", "console")
sa = guard.SteamAuthenticator(acc["se"])
guard_gui = app.window(title_re='Steam Guard - .*',
class_name='vguiPopupWindow')
guard_gui.wait("ready")
guard_gui.set_focus()
sleep(.1)
code = sa.get_code()
keyboard.send_keys(code + """{ENTER}""")
eel.info("等待登入頁面被關閉", "", "console")
login_gui.wait_not("visible", 60000)
eel.info("登入完成", "", "console")
del app
if (lock != False):
lock.release()
def auto_login(steamid, name, lock):
eel.info("使用快取登入", "使用者名稱:" + name + "\nsteamid:" + steamid, "console")
key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, "SOFTWARE\Valve\Steam", 0,
winreg.KEY_ALL_ACCESS)
winreg.SetValueEx(key, "AutoLoginUser", 0, winreg.REG_SZ, name)
winreg.SetValueEx(key, "RememberPassword", 0, winreg.REG_DWORD, 0x00000001)
exe, t = winreg.QueryValueEx(key, "SteamExe")
winreg.CloseKey(key)
si = subprocess.STARTUPINFO()
si.dwFlags |= subprocess.STARTF_USESHOWWINDOW
eel.info("關閉Steam", "", "console")
close_steam(exe, si)
eel.info("啟動steam", "", "console")
app = APP().start(exe)
login_gui = app.window(title_re='Steam [^Guard].*',
class_name='vguiPopupWindow')
eel.info("等待 '主頁面'", "", "console")
wait_time = app_setting("wait_steam_start")
eel.info("容許等待時間" + wait_time, "", "console")
eel.sleep(int(wait_time))
try:
login_gui.wait_not("ready", wait_time) #等待介面
except:
eel.info("注意!", "無法使用快取登入\n將使用模擬登入", "console")
login(steamid, lock, app, True)
else:
del app
lock.release()
eel.info("登入成功", "", "console")
def startLabel(movie_lang, gpu_support, display_frame):
global video_path
try:
if video_path != '':
eel.mSpinner()
eel.info("Movie statutory labeling started")
else:
eel.info("select video path")
os.system('ffmpeg -i ' + video_path +
' -ab 160k -ac 2 -ar 44100 -vn Audio/' +
Path(video_path).stem + '-audio.wav')
print(video_path, movie_lang, gpu_support, display_frame)
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument(
"-m",
"--model",
type=str,
default='./human-activity/resnet-34_kinetics.onnx',
help="path to trained human activity recognition model")
ap.add_argument(
"-c",
"--classes",
type=str,
default='./human-activity/action_recognition_kinetics.txt',
help="path to class labels file")
ap.add_argument("-vo",
"--output",
type=str,
default="./output.avi",
help="Video output name")
args = vars(ap.parse_args())
# load the contents of the class labels file, then define the sample
# duration (i.e., # of frames for classification) and sample size
# (i.e., the spatial dimensions of the frame)
CLASSES = open(args["classes"]).read().strip().split("\n")
SAMPLE_DURATION = 32
SAMPLE_SIZE = 112
labels = [
'tasting beer', 'smoking', 'drinking beer', 'driving car',
'driving tractor', 'riding a bike', 'riding scooter',
'smoking hookah', 'riding mountain bike', 'motorcycling'
]
riding = [
'motorcycling', 'riding a bike', 'riding scooter',
'riding mountain bike'
]
smoking = ['smoking', 'smoking hookah']
alcohol = ['tasting beer', 'drinking beer']
driving = ['driving car', 'driving tractor']
# load the human activity recognition model
print("[INFO] loading human activity recognition model...")
neth = cv.dnn.readNet(args["model"])
# Load the weights and configutation to form the pretrained YOLOv3 model for smoking detection
nethelmet = cv.dnn.readNetFromDarknet(
'./yolov3-coco/yolov3-helmet.cfg',
'./yolov3-coco/helmet6000.weights')
netsmoking = cv.dnn.readNetFromDarknet(
'./yolov3-coco/yolov3-smoking.cfg',
'./yolov3-coco/yolov3hs.weights')
netseatbelt = cv.dnn.readNetFromDarknet(
'./yolov3-coco/yolov3-custom1.cfg',
'./yolov3-coco/yoloseatbelt.weights')
if gpu_support:
print("[INFO] setting preferable backend and target to CUDA...")
neth.setPreferableBackend(cv.dnn.DNN_BACKEND_CUDA)
neth.setPreferableTarget(cv.dnn.DNN_TARGET_CUDA)
print("[INFO] setting preferable backend and target to CUDA...")
nethelmet.setPreferableBackend(cv.dnn.DNN_BACKEND_CUDA)
nethelmet.setPreferableTarget(cv.dnn.DNN_TARGET_CUDA)
def activity_detect(frames):
# now that our frames array is filled we can construct our blob
blob = cv.dnn.blobFromImages(frames,
1.0, (SAMPLE_SIZE, SAMPLE_SIZE),
(114.7748, 107.7354, 99.4750),
swapRB=True,
crop=True)
blob = np.transpose(blob, (1, 0, 2, 3))
blob = np.expand_dims(blob, axis=0)
# pass the blob through the network to obtain our human activity
# recognition predictions
neth.setInput(blob)
outputs = neth.forward()
z = outputs.argsort()[-5:][0][-5:]
activityList = [CLASSES[x] for x in z]
print(activityList)
print(np.argmax(outputs))
return CLASSES[np.argmax(outputs)], activityList
def writeFrame(frame, fps):
global writer
if writer is None:
# Initialize the video writer
fourcc = cv.VideoWriter_fourcc(*"MJPG")
writer = cv.VideoWriter(args["output"], fourcc, fps,
(frame.shape[1], frame.shape[0]), True)
writer.write(frame)
def elseFrame(frames, display_frame):
for frame in frames:
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
def checkActivity(list1, list2):
check = any(item in list1 for item in list2)
return check
# grab a pointer to the input video stream
print("[INFO] accessing video stream...")
vid = cv.VideoCapture(video_path)
fps = vid.get(cv.CAP_PROP_FPS)
print("Fps is :", fps)
firstLabel = ''
secondLabel = ''
thirdLabel = ''
# loop until we explicitly break from it
while True:
# initialize the batch of frames that will be passed through the
# model
frames = []
# loop over the number of required sample frames
for i in range(0, SAMPLE_DURATION):
# read a frame from the video stream
(grabbed, frame) = vid.read()
# if the frame was not grabbed then we've reached the end of
# the video stream so exit the script
if not grabbed:
break
# otherwise, the frame was read so resize it and add it to
# our frames list
#frame = imutils.resize(frame, width=400)
frames.append(frame)
if (len(frames) > 31):
firstLabel, activityList1 = activity_detect(frames[:16])
secondLabel, activityList2 = activity_detect(frames[16:])
print(firstLabel)
print(secondLabel)
else:
for frame in frames:
writeFrame(frame, fps)
break
if (checkActivity(labels, activityList1) and checkActivity(
labels, activityList2)) or (firstLabel == secondLabel) or (
firstLabel
== thirdLabel) or (firstLabel in alcohol) or (
secondLabel
in alcohol) or (firstLabel
in smoking) or (secondLabel
in smoking):
thirdLabel = secondLabel
print(thirdLabel)
label = firstLabel
if (label in riding):
detect = yolo_detect(frames, label, nethelmet)
if detect == 1:
eel.info("Riding without helmet detected")
for i in range(0, 130):
(grabbed, frame) = vid.read()
if not grabbed:
break
frames.append(frame)
for frame in frames:
frame = add_warning(
frame, 'Images/statutory/' + movie_lang +
'/helmet.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
else:
elseFrame(frames, display_frame)
elif (firstLabel in smoking) or (secondLabel in smoking):
detect = yolo_detect(frames, label, netsmoking)
print("detect is :", detect)
if detect == 2:
eel.info("Smoking detected")
for i in range(0, 84):
(grabbed, frame) = vid.read()
if not grabbed:
break
frames.append(frame)
for frame in frames:
frame = add_warning(
frame, 'Images/statutory/' + movie_lang +
'/smoke.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
else:
elseFrame(frames, display_frame)
elif label in alcohol:
detect = yolo_detect(frames, label, netsmoking)
for i in range(0, 84):
(grabbed, frame) = vid.read()
if not grabbed:
break
frames.append(frame)
if detect == 2:
eel.info("alcohol & smoking detected")
for frame in frames:
frame = add_warning(
frame, 'Images/statutory/' + movie_lang +
'/smokealcohol.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
else:
for frame in frames:
frame = add_warning(
frame, 'Images/statutory/' + movie_lang +
'/alcohol.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
elif label in driving:
detect = yolo_detect(frames, label, netseatbelt)
print("detect is", detect)
if detect == 3:
eel.info("driving without seatbelt detection")
for i in range(0, 84):
(grabbed, frame) = vid.read()
if not grabbed:
break
frames.append(frame)
for frame in frames:
frame = add_warning(
frame, 'Images/statutory/' + movie_lang +
'/seatbelt.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
else:
elseFrame(frames, display_frame)
else:
elseFrame(frames, display_frame)
elif (firstLabel not in smoking) and (secondLabel not in smoking):
detect = yolo_detect(frames, label, netsmoking)
print("detect is :", detect)
if detect == 2:
eel.info("Smoking detected")
for i in range(0, 84):
(grabbed, frame) = vid.read()
if not grabbed:
break
frames.append(frame)
for frame in frames:
frame = add_warning(
frame,
'Images/statutory/' + movie_lang + '/smoke.png')
if display_frame:
cv.imshow("Statutory Labeling", frame)
key = cv.waitKey(1) & 0xFF
writeFrame(frame, fps)
else:
elseFrame(frames, display_frame)
else:
elseFrame(frames, display_frame)
eel.mSpinner()
if video_path != '':
eel.mAddTick()
writer.release()
vid.release()
if display_frame:
cv.destroyWindow("Statutory Labeling")
eel.info('Output file is saved to: Video/' + Path(video_path).stem +
'-Ouput.mkv')
os.system('ffmpeg -i output.avi -i Audio/' + Path(video_path).stem +
'-audio.wav -c copy Video/' + Path(video_path).stem +
'-Ouput.mkv')
print('Output file is saved to: Video/' + Path(video_path).stem +
'-Ouput.mkv')
print("Process finished")
if (os.path.isfile('Audio/' + Path(video_path).stem + '-audio.wav')):
os.system('rm Audio/' + Path(video_path).stem + '-audio.wav')
except:
print("An error occured")
eel.mSpinner()
eel.mAddCross()
eel.info("An error occured")