def saveFile(self):
file, _ = QFileDialog.getSaveFileName(self, "Save File", os.getcwd(), "Visual Model Project (*.vmp)")
saved_data = {}
saved_data["imagePath"] = self.imagecard.image_filename
saved_data["videoPath"] = self.videocard.video_path
if file != "":
save.save_file(file, saved_data)
print(file)
def save():
try:
word = request.args.get('word')
if not word:
raise Exception()
word = word.lower()
jobs = db.get(word)
if not jobs:
raise Exception()
save_file(jobs, word)
return save_file(f"job-{word}.csv", attachment_filename=f"job-{word}.csv", as_attachment = True)
except:
return redirect("/")
from py_indeed import get_jobs as get_indeed_jobs from save import save_file indeed_jobs = get_indeed_jobs() jobs = indeed_jobs save_file(jobs) # https://kr.indeed.com/jobs?q=python&limit=50&radius=25&start=50
from scraper import get_reviews from save import save_file reviews = get_reviews() save_file(reviews)
dataFile_postfix='.csv',
task_description=
'', # it's been set in config_other_parameter(), parameter_config.py
global_parameter_dict={})
config.set_additional_parameters(hyper_parameter_dict,
data_parameter_obj._args)
data_parameter_dict = data_parameter_obj._args
model_parameter_obj = Parameters(
train_num=hyper_parameter_dict['train_num'],
rollTest_num=data_parameter_dict['rollTest_num'],
batch_size=512 * 2,
nb_classes=4,
nb_input=10,
evaluate_batch_size=128,
evaluate_verbose=0,
#filter_row =2 , filter_col =1, filter_num = 16,
loss='categorical_crossentropy',
optimizer='rmsprop',
loss_weights='loss_weights',
metrics=['accuracy'],
modelFile_directoryName='models/',
modelFile_postfix='',
)
roll_result_dict = roll.get_roll_start(data_parameter_obj,
model_parameter_obj)
save.save_file(data_parameter_obj, roll_result_dict)
save.save_figure(data_parameter_obj, roll_result_dict)
elapsed = (time.time() - start)
print("Time used(minute): ", float(elapsed) / 60)