def run(self):
# 计数器初始化
count = 0
# 读取配置
data = read_config.read()
cap, ok, frame, length = read_frame.cam_init(self.address)
# 背景减除器初始化
fgbg = frame_background.background_init()
tracker_list = []
detect_list = []
result_list = []
while True:
ret, frame = cap.read()
if ret:
rgbImage = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
h, w, ch = rgbImage.shape
bytesPerLine = ch * w
convertToQtFormat = QImage(rgbImage.data, w, h, bytesPerLine, QImage.Format_RGB888)
p = convertToQtFormat.scaled(640, 480, Qt.KeepAspectRatio)
self.changePixmap.emit(p)
if self.method:
# https://stackoverflow.com/a/55468544/6622587
step = 10
diff = frame_background.process(fgbg, frame, count, step)
if diff is not 0:
# 当前帧的目标检测
detect_list, detected_img, contour = frame_detection.detectobj(diff, frame)
new_detect_list = frame_tracker.list_compare(detect_list, result_list)
Added_tracker_list = frame_tracker.init_tracker(frame, new_detect_list)
tracker_list += Added_tracker_list
tracked_img, result_list = frame_tracker.update_tracker(frame, tracker_list)
frame = detected_img
rgbImage = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
h, w, ch = rgbImage.shape
bytesPerLine = ch * w
convertToQtFormat = QImage(rgbImage.data, w, h, bytesPerLine, QImage.Format_RGB888)
p = convertToQtFormat.scaled(640, 480, Qt.KeepAspectRatio)
self.detected.emit(p)
frame = tracked_img
rgbImage = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
h, w, ch = rgbImage.shape
bytesPerLine = ch * w
convertToQtFormat = QImage(rgbImage.data, w, h, bytesPerLine, QImage.Format_RGB888)
p = convertToQtFormat.scaled(640, 480, Qt.KeepAspectRatio)
self.tracked.emit(p)
def aciLogIn(apic=None):
"""Log in to ACI."""
# Get the credentials
config = read_config.read()
# If an existing session wasn't supplied, make a new session
if not isinstance(apic, Node):
try:
apic = Node(config['ACI APIC']['url'])
except MetaError as err:
# This implies that the meta hasn't been downloaded yet
raise Exception("The ACI Meta information hasn't been "\
"downloaded from the controller. To fix this, run:"\
"\nrmetagen.py -u admin 10.43.40.11") from err
log.info('APIC Login: {}'.format(
apic.methods.Login(config['ACI APIC']['username'],
config['ACI APIC']['password']).POST()))
return apic
#!/usr/bin/env python
'''Documentation to be written'''
# '%(folder_url)sjob/%(short_name)s/nextbuildnumber/submit
import read_config
import sys
import requests
import json
#####################
# Checking the configuration
#####################
cfg = read_config.read()
if cfg:
j_url = cfg['jenkins_url']
user = cfg['user']
token = cfg['token']
else:
print('Missing some mandatory parameters')
sys.exit(1)
def set_b_num(url, num):
print(num)
r = requests.post(url, auth=(user, token), data={'nextBuildNumber': num})
print(json.loads(r.text)['nextBuildNumber'])
def learn_b_num(url):
r = requests.get(url, auth=(user, token))
return json.loads(r.text)['nextBuildNumber']
import score_py3
import drawing
#%% Input Arguments
parser = argparse.ArgumentParser(
description=
'Experiment10(VGG16): Train the model for diagnosing the heart disease by the ECG.'
)
parser.add_argument(
'-c',
'--config',
type=str,
default='./Config/config.ini',
metavar='str',
help="the path of configure file (default: './Config/config.ini')")
Args = parser.parse_args() # the Arguments
Args = read_config.read(Args) # read configure file
#%% Main Function
if __name__ == '__main__':
#%% ########## Read Data ##########
print('read data')
ECG_data, ECG_label = read_data.extract_data(
read_data.read_data(Args)) # read data
#%% ########## Data Processing ##########
ECG_data = data_process.cut_out(ECG_data,
Args.len) # cut out the ECG signals
ECG_data = data_process.axis_change(ECG_data) # change the axis
ECG_label = data_process.label_from_0(ECG_label) # label from 0
# split data
train_x, test_x, train_y, test_y = data_process.train_test_split(
ECG_data, ECG_label, trainratio=Args.trainratio, random_state=0)
# change to Tensor
def __init__(self, *args, **kwargs):
print('Loading GUI')
super().__init__('ACI Application Deployment')
config = read_config.read()
#Definition of the forms fields
self._txt_name = ControlText('Application Name (No Spaces)')
self._auto_ip = ControlCheckBox('Automatically select IPs', default=True)
self._txt_ip = ControlText('First Prod Subnet (for Seeded IP generation) (X.X.X.X/Y)')
self._txt_ip.enabled = False
self._subnet_size = ControlText('Subnet Size (CIDR)', default='28')
self._author = ControlText('Change Implementer', default=config['DEFAULT VALUES']['Your_name'])
self._requestor = ControlText('Change Requestor')
self._change = ControlText('Change Number')
self._reserve_in_ipam = ControlCheckBox('Reserve in IPAM', default=True)
self._append = ControlCheckBox('Append to Existing Service (Overwrite Possible)', default=False)
self._cc_env = ControlCombo('Environment')
self._cc_env.add_item('(DEV) - DeployACI Lab', 'deployaci_lab')
# Populate the environment list from actual tenants
for tenant in getUsableTenants():
if tenant == 'deployaci_lab':
continue
self._cc_env.add_item(f'(PROD) - {tenant}', tenant)
self._ck_prod_client = ControlCheckBox('prod_client', default=True)
self._ck_prod_web = ControlCheckBox('prod_web', default=True)
self._ck_prod_app = ControlCheckBox('prod_app', default=True)
self._ck_prod_db = ControlCheckBox('prod_db', default=True)
self._ck_uat_client = ControlCheckBox('uat_client', default=True)
self._ck_uat_web = ControlCheckBox('uat_web', default=True)
self._ck_uat_app = ControlCheckBox('uat_app', default=True)
self._ck_uat_db = ControlCheckBox('uat_db', default=True)
self._ck_dev_client = ControlCheckBox('dev_client', default=True)
self._ck_dev_web = ControlCheckBox('dev_web', default=True)
self._ck_dev_app = ControlCheckBox('dev_app', default=True)
self._ck_dev_db = ControlCheckBox('dev_db', default=True)
self._runbutton = ControlButton('Deploy')
self._txt_ip.key_pressed_event = self._runReady
self._txt_name.key_pressed_event = self._runReady
self._subnet_size.key_pressed_event = self._runReady
self._auto_ip.changed_event = self._auto_ip_press
#Define the event that will be called when the run button is processed
self._runbutton.value = self.__runEvent
self._runbutton.enabled = False
#self._cc_env.value = self.__envEvent
#Define the organization of the Form Controls
# self._formset = [
# ('_text'),
# ('_ck_prod_client'),
# ('_ck_prod_web'),
# ('_ck_prod_app'),
# ('_ck_prod_db'),
# ('_ck_uat_client'),
# ('_ck_uat_web'),
# ('_ck_uat_app'),
# ('_ck_uat_db'),
# ('_ck_dev_client'),
# ('_ck_dev_web'),
# ('_ck_dev_app'),
# ('_ck_dev_db'),
# ('_runbutton'),
# ]
self._formset = [
('_txt_name'),
('_auto_ip'),
('_txt_ip'),
('_subnet_size'),
('_author'),
('_requestor'),
('_change'),
('_reserve_in_ipam', '_append'),
('_cc_env'),
('_ck_prod_client', '_ck_uat_client', '_ck_dev_client'),
('_ck_prod_web', '_ck_uat_web', '_ck_dev_web'),
('_ck_prod_app', '_ck_uat_app', '_ck_dev_app'),
('_ck_prod_db', '_ck_uat_db', '_ck_dev_db'),
('_runbutton'),
]
from torch.optim import lr_scheduler
from torch.utils.data import DataLoader
from sklearn.metrics import precision_recall_fscore_support
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
parser = argparse.ArgumentParser()
parser.add_argument('--config_file_path',
type=str,
default='conf_files/config')
## ===============================
# Compile and configure all the model parameters.
## ===============================
args = parser.parse_args()
config = read_config.read(args.config_file_path)
name = config['name']
total_epoch = config['total_epoch']
batch_size = config['batch_size']
class_number = config['class_number']
learning_rate = config['learning_rate']
extractor = config['extractor']
image_size = config['image_size']
target_list = config['target_list'].split(',')
constant.resume_train = bool(config['resume'])
constant.number_worker = config['number_workers']
constant.sampling = config['sampling']
constant.sampling_size = config['sampling_size']
seed = 42
