def demo_mode():
try:
points = ImageRandomiser(IMAGE_NAME, IMAGE_SIZE, IMAGE_SIZE, PIXEL_SIZE, CAMERA)
demo.run(args.time, points, DISPLAY, KEYBOARD)
except Exception as e:
LOGGER.info(str(e))
KEYBOARD.close()
DISPLAY.stop()
def bibi(self):
url = "https://passport.bilibili.com/login"
self.browser.get(url)
xpath = '//*[@id="login-username"]'
self.wait.until(EC.presence_of_element_located(
(By.XPATH, xpath))).send_keys('Python')
xpath = '//*[@id="login-passwd"]'
self.wait.until(EC.presence_of_element_located(
(By.XPATH, xpath))).send_keys('Python')
xpath = '//*[@id="geetest-wrap"]/div/div[5]/a[1]'
self.click(xpath)
xpath = '/html/body/div[2]/div[2]/div[6]/div/div/div[2]/div[1]/div/div[2]/img'
logo = self.wait.until(
EC.presence_of_element_located((By.XPATH, xpath)))
f = logo.get_attribute('src')
if f:
res = requests.get(f)
res = res.content
with open(f"bilbil.jpg", 'wb') as f:
f.write(res)
res = demo.run("bilbil.jpg")
plan = demo.to_selenium(res)
# xpath = "/html/body/div[2]/div[2]/div[6]/div/div/div[2]/div[1]/div/div[2]"
# logo = self.wait.until(EC.presence_of_element_located(
# (By.XPATH, xpath)))
print(logo.location)
print(logo.size)
X, Y = logo.location['x'], logo.location['y']
print(X, Y)
lan_x = 259 / 334
lan_y = 290 / 384
# print(X+x, Y+y)
time.sleep(1)
# ActionChains(self.browser).move_by_offset(200, 0).click().perform()
for p in plan:
x, y = p['place']
print(x, y)
ActionChains(self.browser).move_by_offset(
X - 40 + x * lan_x, Y + y * lan_y).click().perform()
ActionChains(self.browser).move_by_offset(
-(X - 40 + x * lan_x),
-(Y + y * lan_y)).perform() # 将鼠标位置恢复到移动前
time.sleep(1)
xpath = "/html/body/div[2]/div[2]/div[6]/div/div/div[3]/a/div"
self.click(xpath)
print(res)
print(plan)
time.sleep(1000)
"metric (object appearance).",
type=float,
default=0.2)
parser.add_argument("--nn_budget",
help="Maximum size of the appearance descriptors "
"gallery. If None, no budget is enforced.",
type=int,
default=100)
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
os.makedirs(args.output_dir, exist_ok=True)
sequences = os.listdir(args.mot_dir)
for sequence in sequences:
print("Running sequence %s" % sequence)
sequence_dir = os.path.join(args.mot_dir, sequence)
detection_file = os.path.join(args.detection_dir, "%s.npy" % sequence)
output_file = os.path.join(args.output_dir, "%s.txt" % sequence)
demo.run(sequence_dir,
detection_file,
output_file,
args.min_confidence,
args.nms_max_overlap,
args.min_detection_height,
args.max_cosine_distance,
args.nn_budget,
display=False)
from demo import run, get_args
parser = argparse.ArgumentParser()
parser.add_argument('--gpuid', type=int, default=0,
help="Negative value means cpu-only")
parser.add_argument('--loss', type=str, default='CCL', choices=['KCL', 'CCL'],
help="The clustering criteria. Default: CCL")
parser.add_argument('--num_cluster', type=int, default=100,
help="The number of cluster. Default: 100 (unknown number of cluster)")
config = parser.parse_args()
print('STEP1: Train SPN on Omniglot background set')
if not os.path.isfile('outputs/Omniglot_VGGS_DPS.model.pth'):
argv = '--loss DPS --dataset Omniglot --model_type vgg --model_name VGGS --schedule 30 40 --epochs 50'.split(' ')
run(get_args(argv))
print('STEP1: Done')
omniglot_evaluation_alphabet_set = [
'Angelic',
'Atemayar_Qelisayer',
'Atlantean',
'Aurek',
'Avesta',
'Ge_ez',
'Glagolitic',
'Gurmukhi',
'Kannada',
'Keble',
'Malayalam',
import demo demo.run() exit()
type=str,
default='train',
help='train, test or demo.')
parser.add_argument('--demo_path',
type=str,
default='demo/inputs/1',
help='Please specify the demo path.')
return parser.parse_args()
if __name__ == '__main__':
args = parse_args()
cfg = CONFIG(args.config)
cfg.update_config(args.__dict__)
from net_utils.utils import initiate_environment
initiate_environment(cfg.config)
'''Configuration'''
cfg.log_string('Loading configurations.')
cfg.log_string(cfg.config)
cfg.write_config()
'''Run'''
if cfg.config['mode'] == 'train':
import train
train.run(cfg)
if cfg.config['mode'] == 'test':
import test
test.run(cfg)
if cfg.config['mode'] == 'demo':
import demo
demo.run(cfg)
self.emit("click", date_time)
def get_click_count(self):
return self.invoke("getClickCount")
class SimpleDemo(demo.DemoApp):
def __init__(self):
self._web_widget = SimpleWebWidget()
self._web_widget.connect("click", self._on_click)
def get_title(self):
return "Simple Demo"
def get_description(self):
return """Demonstrates message passing between Python and JavaScript in an embedded HTML page.
Click events are logged in the console."""
def get_content(self):
return self._web_widget
def _on_click(self, widget, date_time):
print "clicked: ", date_time
print "click count: " , self._web_widget.get_click_count()
if __name__ == '__main__':
demo = SimpleDemo()
demo.build_ui()
demo.run()
def main():
try:
import demo
demo.run()
except ImportError:
print("Warning: demo.py not found.")
import demo
if __name__ == '__main__':
#min_learning_rate = 0.0001
demo.run(0.0001)
for i in range(55, 100):
demo.run(float(i)/1000000)
#new_err = (demo.run(0.0001)
#if (float(new_err) < float(min_err)):
#min_err = new_err
#min_learning_rate = i
#print(min_err)
#print(min_learning_rate)
"""finding the min here is difficult due to float limitations.
Python Decimals may be too slow."""
if frame_number % 80 == 0:
if i == 1:
name = "img/" + str(frame_number) + '.jpg'
cv2.imwrite(name, face)
else:
name = "img/" + str(frame_number) + '_' + str(i) + '.jpg'
cv2.imwrite(name, face)
i += 1
score = 0
index = 0
for n in range(len(known_faces_name)):
path = "face/" + known_faces_name[n] + ".png"
score_new = demo.run(appid=APPID,
apisecret=APISECRET,
apikey=APIKEY,
img1_path=path,
img2_path=name)
if (score < score_new) and (score_new > 0.5):
score = score_new
index = n
face_names.append(known_faces_name[index])
else:
face_names.append("")
for n in range(len(known_faces_name)):
if frame_number <= frame_last_number[n]:
frame = cv2ImgAddText(frame, known_faces_name[n], frame_left[n],
frame_top[n], (255, 0, 0), 50)
frame = cv2ImgAddText(frame, contents[n], frame_left[n],
frame_top[n] + 100, (255, 0, 0), 25)
def __init__(self):
save_files = session.query(Player).filter_by(id=1).all()
# save_files = []
while True:
print("[N]ew Game")
if save_files:
print("[C]ontinue")
else:
cprint("[C]ontinue", "grey")
choice = input()
if choice.lower() == 'n':
for each in views.intro:
print (each)
print(views.cont)
input()
print("Do-do-do-do-da-dodo")
print("Not Golden Sun")
new = Player(gender = views.gender(self),
name = views.name(),
level = 10,
hp = 50,
max_hp = 50,
mp = 9,
max_mp = 9,
strength = 50,
fortitude = 50,
agility = 45,
skill_points = 0,
gold = 20,
poisoned = False
)
skills = []
print("*TEST*"*5, "\nWhat skills do you want?")
for each in session.query(Skill).all():
while True:
# output = each.name, str(index)
print(each.name, "\ny/n")
choice = input()
if choice == 'y':
skills.append(each)
break
elif choice == 'n':
break
break
elif choice.lower() == 'c':
if save_files:
for index, each in enumerate(save_files, start=1):
print(index, each.name)
choice = input()
if int(choice) in range(1, len(save_files)+1):
new = save_files[int(choice)-1]
skills = [session.query(Skill).filter_by(id = each.skill_id).all()[0] for each in session.query(SkillOwnership).filter_by(player_id = new.id).all()]
break
else:
print("You have no saved games.")
input(views.cont)
else:
print(views.try_again)
input(views.cont)
choice = demo.run(new, skills)
if choice == 'battle':
battle.Battle(new, skills).encounter()
def detect(queue, lock, config):
url = 'http://10.75.4.42:10595/v1/malfunction/addMalfunctionRecord'
malfunction_topic = 'bao_malfunction_steel'
malfunction_status = False
malfunction_count = 0
malfunction_count_threshold = 40
normal_count = 0
normal_count_threshold = 30
video_duration = 5 # record for 5 seconds
video_timer = 0
video_num = 0
record_on = False
# record timer for test purpose
record_timer = 0
millis = int(round(time.time() * 1000))
servers = config.get('kafka', 'servers')
producer = KafkaProducer(bootstrap_servers=servers)
fourcc = cv2.VideoWriter_fourcc(*'avc1')
while True:
start = time.time()
# lock.acquire()
if queue.full():
logging.error('detect queue full')
if not queue.empty():
data = queue.get()
frame = data['data']
# lock.release()
print('detecting the image')
_, processed_frame, warning = demo.run(frame)
if warning:
malfunction_count += 1
# report malfunction if count > threshold
if malfunction_count > malfunction_count_threshold:
if not malfunction_status:
print('malfunction recognized')
malfunction_status = True
current_time = int(time.time())
# set a gap period of 15 minuets for recording to avoid too much testing data
if current_time - record_timer > 15 * 60:
print('recording start')
record_timer = current_time
record_on = True
file_name = 'malfunction_{0}.mp4'.format(video_num)
video_num += 1
out = cv2.VideoWriter('video/' + file_name, fourcc,
25, (1024, 576))
else:
# send the malfunction image stream to kafka
_, img_encode = cv2.imencode('.jpg', processed_frame)
img_base64 = base64.b64encode(img_encode)
msg_dict = {
"type": "卡钢",
"position": data['position'],
"timestamp": millis,
"data": str(img_base64, 'ASCII'),
"complete": 1,
"desc": data['position'] + "卡钢"
}
message = json.dumps(msg_dict).encode('utf-8')
try:
producer.send(malfunction_topic, message)
except KafkaError as e:
logging.error(e)
elif malfunction_status:
# check malfunction stop
if normal_count < normal_count_threshold:
# keep malfunction status and send the malfunction image stream to kafka
_, img_encode = cv2.imencode('.jpg', processed_frame)
img_base64 = base64.b64encode(img_encode)
msg_dict = {
"type": "卡钢",
"position": data['position'],
"timestamp": millis,
"data": str(img_base64, 'ASCII'),
"complete": 1,
"desc": data['position'] + "卡钢"
}
message = json.dumps(msg_dict).encode('utf-8')
try:
producer.send(malfunction_topic, message)
except KafkaError as e:
logging.error(e)
normal_count += 1
else:
# malfunction stop, send the last frame to kafka with complete flag of 0
_, img_encode = cv2.imencode('.jpg', processed_frame)
img_base64 = base64.b64encode(img_encode)
msg_dict = {
"type": "卡钢",
"position": data['position'],
"timestamp": millis,
"data": str(img_base64, 'ASCII'),
"complete": 0,
"desc": data['position'] + "卡钢"
}
# msg_dict['data'] = str(img_base64, 'ASCII')
message = json.dumps(msg_dict).encode('utf-8')
try:
for i in range(
2
): # Simply send two times for frontend to stop the malfunction image
producer.send(malfunction_topic, message)
except KafkaError as e:
logging.error(e)
malfunction_status = False
# print('{0} frames in this malfunction'.format(malfunction_count))
malfunction_count = 0
print('malfunction stop')
normal_count = 0
else:
malfunction_count = 0
# Record the malfunction video for a period of time
if record_on and video_timer < video_duration * 25:
out.write(processed_frame)
video_timer += 1
elif video_timer >= video_duration * 25:
# recording finished
print('recording stop')
video_timer = 0
out.release()
record_on = False
# save the malfunction record
params = {
"cameraId": 1,
"desc": data['position'] + "卡钢",
"eventTime": millis,
"position": data['position'],
"type": "卡钢",
"videoPath": file_name
}
r = requests.put(url, json=params)
response = json.loads(r.content)
if response['success']:
print('Record saved')
else:
print('Record save failed')
# else:
# lock.release()
end = time.time()
print('time for detecting {0}'.format(end - start))
