def worker(req, proxy_port, verbose):
global progress
global progressbar
while True:
item = q.get()
if item is None:
break
progressbar.update(queue_max_size - q.qsize())
#function to be filled
do_work(req, item)
#send the request
if proxy_port:
response = req.send_request(proxy_port)
else:
response = req.send_request(0)
# function to be filled
process_response(response)
if verbose:
req.display_state()
print("Response:", response.read())
q.task_done()
def background_thread_check():
global checker_thread, dic_min_error_rev, thread_lock
try:
dic_min_error_rev = main.do_auto_check(dic_min_error_rev)
file = open("./dic_min_error_rev", "w")
file.write(json.dumps(dic_min_error_rev))
file.close()
except Exception as ex:
# Get current system exception
ex_type, ex_value, ex_traceback = sys.exc_info()
# Extract unformatter stack traces as tuples
trace_back = traceback.extract_tb(ex_traceback)
# Format stacktrace
stack_trace = list()
for trace in trace_back:
stack_trace.append(
"File : %s , Line : %d, Func.Name : %s, Message : %s" %
(trace[0], trace[1], trace[2], trace[3]))
printer.errprint("Exception type : %s " % ex_type.__name__)
printer.errprint("Exception message : %s" % ex_value)
printer.errprint("Stack trace : %s" % stack_trace)
printer.errprint("检查意外结束")
progressbar.update(0, 0)
with thread_lock:
print("线程结束")
checker_thread = None
socketio.emit('checker_state', 0)
def convert_excel_to_dict(wb, sheet_name, progressbar=None):
"""
:param wb: class:`openpyxl.workbook.Workbook`
:param sheet_name: characters
:return: list of dict
"""
header = []
kpi_sum = []
try:
sheet_ranges = wb[sheet_name]
for index, row in enumerate(sheet_ranges.iter_rows(row_offset=0)):
if progressbar is not None:
progressbar.update(index)
sum_element = {'INDEX': index}
for i in range(len(row)):
if index == 0:
# header
if row[i].value is not None:
header.append(row[i].value.strip().upper())
else:
# add expected data to kpi sum dictionary
if i < len(header):
sum_element[header[i]] = row[i].value
if index > 0:
kpi_sum.append(sum_element)
except KeyError as keyerror:
print(str(keyerror))
return kpi_sum
def on_stop_check():
global checker_thread, thread_lock
with thread_lock:
if checker_thread is not None:
printer.errprint('客户停止了自检\n')
stop_thread(checker_thread)
checker_thread = None
socketio.emit('checker_state', 0)
progressbar.update(0, 0)
else:
printer.errprint('后台并没有正在自检\n')
def downloadVideos(self, downloadUrl, pathToStoreTheFile):
"""This function downloads all the videos and save those to the path provided """
requiredATag = []
self.logger.info("In downloadVideos() function of class NPTEL Video Downloader.........")
soup = self.getSoup(downloadUrl)
self.logger.info("=======>Getting soup for given downloadUrl link is successfull")
try:
rows = soup.find_all("a")
for requiredRows in rows:
if "mp4" in str(requiredRows):
requiredATag.append(requiredRows)
self.logger.info("=======>Number of Files to Download: "+str(len(requiredATag)))
print("Number of Files to Download: "+str(len(requiredATag)))
pbar = tqdm(total=len(requiredATag))
except:
self.logger.error("=======>Error in retrieving download urls of video files")
return None
self.logger.info("=======>Started Downloading Videos...")
for i in range(1,len(requiredATag)+1):
fileName = None
try:
requiredDownloadUrl = requiredATag[i-1].get("href")
fileName = requiredDownloadUrl.split("=")[-1]
requiredDownloadUrl = "https://nptel.ac.in" + requiredDownloadUrl
self.logger.info("=======>Downloading video number "+str(i)+" ["+fileName+"]")
r = req.get(requiredDownloadUrl, stream=True)
if pathToStoreTheFile[-1]!='/':
pathToStoreTheFile += '/'
fileName = str(i)+" "+fileName
with open(pathToStoreTheFile+fileName+".mp4", 'wb') as f:
for chunk in r.iter_content(chunk_size=1024 * 1024):
if chunk:
f.write(chunk)
pbar.update(1)
self.logger.info("=======>Succesfully downloaded video number " + str(i) + " [" + fileName + "]")
except:
self.logger.error("=======>Error in Downloading video number " + str(i) + " [" + fileName + "]")
return None
self.logger.info("All videos downloaded successfully to the path: "+pathToStoreTheFile)
def main():
args = handle_args()
input_path = args.i[0]
output_path = args.o[0]
rotation = args.r[0]
output_width = int(args.c[0].split('x')[0])
output_height = int(args.c[0].split('x')[1])
frame_rate = args.f[0]
frame_skip_rate = args.k[0]
recognize_scale = 0.2
predictor = dlib.shape_predictor('../shapes/shape_predictor_68_face_landmarks.dat')
create_output_dir(output_path)
capture, video, face_cascade = setupOpenCV(input_path, output_path, frame_rate, output_width, output_height)
initGL(output_width, output_height)
total_frames = toolbox.getTotalFrames(input_path)
frame_count = 0
progressbar.init()
last_params = None
while True:
success, frame = capture.read()
if success and frame is not None:
frame, points, last_params = processFrame(frame, rotation, frame_skip_rate, face_cascade, predictor, recognize_scale, output_width, output_height, last_params)
if frame is not None:
if points is not None:
frame = getGLFrame(frame, points, output_width, output_height)
video.write(frame)
frame_count += 1
progress = frame_count / total_frames
progressbar.update(progress)
if progress >= 0.5:
break
else:
break
else:
break
quit(capture, video)
def on_connect():
global cur_progress, total_progress, dic_min_error_rev, checker_thread, thread_lock
print('Client connected\n')
for log in message_logs:
socketio.emit('server_log', log)
checker_state = 0
with thread_lock:
if checker_thread is not None:
checker_state = 1
checker_list = main.get_checker_name_list()
progressbar.update(cur_progress, total_progress)
data = {
'checker_list': checker_list,
'checker_state': checker_state,
'dic_err_revs': dic_min_error_rev
}
emit('ack_init_data', data)
def loop(capture, video): total_frames = toolbox.getTotalFrames(sys.argv[1]) frame_count = 0 last_eye_left = [0, 0, 0, 0] last_eye_right = [0, 0, 0, 0] while True: _, frame = capture.read() if frame is None: return gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.1, 5) for (x, y, w, h) in faces: half = int(w / 2) paddingTop = int(h * 0.2) paddingBottom = int(h * 0.45) if debug: color = (0, 255, 0) top = y+paddingTop bottom = y+h - paddingBottom cv2.rectangle(frame, (x , top), (x+half, bottom), color, 2) cv2.rectangle(frame, (x+half, top), (x+w , bottom), color, 2) def processEye(eye, ex, ey, ew, eh): if debug: cv2.rectangle(frame, (ex, ey), (ex+ew, ey+eh), (0, 0, 255), 2) eye_copy = cv2.resize(eye, (ew, eh)) roi_eye = frame[ey:ey+ew, ex:ex+ew] overlayImage(roi_eye, eye_copy) def processListOfEyes(eyes, offset, last_eye): for (ex, ey, ew, eh) in eyes: ex, ey = toolbox.getBetterPosition((ex, ey, ew, eh), last_eye) ew, eh = int(w * 0.25), int(w * 0.25) processEye(eye, x+ex+offset, y+ey+paddingTop, ew, eh) last_eye[:] = [] last_eye.extend((ex, ey, ew, eh)) # Define 2 areas for the left and right part of the face face_gray_left = gray[y+paddingTop:y+h - paddingBottom, x:x+half] face_gray_right = gray[y+paddingTop:y+h - paddingBottom, x+half:x+w] # Get 2 lists of detected eyes eyes_left = eye_cascade.detectMultiScale(face_gray_left, 1.02, 5, # minSize=(int(w / 8), int(h / 8)), # maxSize=(int(w / 3), int(h / 3)) ) eyes_right = eye_cascade.detectMultiScale(face_gray_right, 1.02, 5, # minSize=(int(w / 8), int(h / 8)), # maxSize=(int(w / 3), int(h / 3)) ) # Draw eyes from list of detected eyes processListOfEyes(eyes_left, 0, last_eye_left) processListOfEyes(eyes_right, half, last_eye_right) # If no eye was detected draw the eye from the previous frame if last_eye_left is not None and len(eyes_left) == 0: ex, ey, ew, eh = last_eye_left processEye(eye, x+ex, y+ey+paddingTop, ew, eh) if last_eye_right is not None and len(eyes_right) == 0: ex, ey, ew, eh = last_eye_right processEye(eye, x+ex+half, y+ey+paddingTop, ew, eh) # Write the frame to the output video file video.write(frame) # Update the progress bar frame_count += 1 progress = frame_count / total_frames progressbar.update(progress)
def serialize(self, serializer):
pass
if __name__ == "__main__":
import progressbar
import time
window = 8
batch_size = 10000
sequence_path = "/home/ubuntu/data/word2vec/small/jawiki-wakati-index-sequence.txt"
total_size_path = "/home/ubuntu/data/word2vec/small/total_size.pkl"
witerator = WindowIterator(window,
batch_size,
index_sequence_file_path=sequence_path,
total_size_path=total_size_path,
repeat=True)
print("witerator.total_size:{}".format(witerator.total_size))
upper_count = 1
count_scale = 100
progressbar = progressbar.ProgressBar(maxvalue=int(count_scale *
upper_count))
indices = [index for index in range(-window, window + 1) if index != 0]
for center, context in witerator:
progressbar.update(int(count_scale * witerator.epoch_detail))
if upper_count == witerator.epoch_detail:
break
pbar.Percentage(),
' ',
pbar.Counter(), '/', str(n),
' ',
Display(),
' ',
pbar.Bar(marker='-'),
' ',
pbar.AdaptiveETA(),
' ',
]
pbar = pbar.ProgressBar(widgets=widgets, maxval=n).start()
# go johnny go, go!
for i, it in enumerate(sets):
pbar.update(i)
size, storage, complexity, codec, level = it
number, repeat = number_repeats[size]
codec = codecs[codec]
codec.configure(complexity_types[complexity](dataset_sizes[size]),
storage_types[storage], level)
results['compress'][i] = reduce(vtimeit(codec.compress,
setup=codec.compress,
before=codec.clean, after=sync,
number=number, repeat=repeat))
results['ratio'][i] = codec.ratio()
codec.deconfigure()
results['decompress'][i] = reduce(vtimeit(codec.decompress,
else:
raise RuntimeError("No such size: '%s'" % size)
codec = codecs[codec]
codec.configure(entropy_types[entropy](dataset_sizes[size]),
storage_types[storage], level)
results['compress'][i] = reduce(vtimeit(codec.compress,
setup=codec.compress,
before=codec.clean, after=sync,
number=number, repeat=repeat))
results['ratio'][i] = codec.ratio()
codec.deconfigure()
results['decompress'][i] = reduce(vtimeit(codec.decompress,
setup=codec.decompress,
number=number,
repeat=repeat))
results['dc_no_cache'][i] = reduce(vtimeit(codec.decompress,
before=drop_caches,
number=number,
repeat=repeat))
codec.clean()
pbar.update(i)
pbar.finish()
success = True
result_csv = result_file_name + '.csv'
results.to_csv(result_csv)
print 'results saved to: ' + result_csv