def plot_active_cases(country):
data.process_data(country)
model = Model(data.dtf)
model.forecast()
model.add_deaths(data.mortality)
result = Result(model.dtf)
return result.plot_active(model.today)
def render_output_panel(country):
data.process_data(country)
model = Model(data.dtf)
model.forecast()
model.add_deaths(data.mortality)
result = Result(model.dtf)
peak_day, num_max, total_cases_until_today, total_cases_in_30days, active_cases_today, active_cases_in_30days = result.get_panel(
)
peak_color = "white" if model.today > peak_day else "red"
panel = html.Div([
html.H4(country),
dbc.Card(body=True,
className="text-white bg-primary",
children=[
html.H6("Total cases until today:",
style={"color": "white"}),
html.H3("{:,.0f}".format(total_cases_until_today),
style={"color": "white"}),
html.H6("Total cases in 30 days:",
className="text-danger"),
html.H3("{:,.0f}".format(total_cases_in_30days),
className="text-danger"),
html.H6("Active cases today:", style={"color": "white"}),
html.H3("{:,.0f}".format(active_cases_today),
style={"color": "white"}),
html.H6("Active cases in 30 days:",
className="text-danger"),
html.H3("{:,.0f}".format(active_cases_in_30days),
className="text-danger"),
html.H6("Peak day:", style={"color": peak_color}),
html.H3(peak_day.strftime("%Y-%m-%d"),
style={"color": peak_color}),
html.H6("with {:,.0f} cases".format(num_max),
style={"color": peak_color})
])
])
return panel
import argparse
from python.model import Model
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# required
parser.add_argument("caffemodel", help="")
parser.add_argument("deploy", help="")
# optional
parser.add_argument("-m", "--mean", help="")
parser.add_argument("-l", "--labels", help="")
parser.add_argument("-g",
"--gpu",
dest="gpu",
action="store_true",
help="")
parser.set_defaults(gpu=False)
args = vars(parser.parse_args())
model = Model(caffemodel_file=args["caffemodel"],
deploy_file=args["deploy"],
mean_file=args["mean"],
labels_file=args["labels"],
gpu=args["gpu"])
print model.classify(image_path="")
parser = argparse.ArgumentParser()
# required
parser.add_argument("caffemodel", help="")
parser.add_argument("deploy", help="")
# optional
parser.add_argument("--port", type=int, help="")
parser.add_argument("--mean", help="")
parser.add_argument("--labels", help="")
parser.add_argument("--gpu", dest="gpu", action="store_true", help="")
parser.add_argument("--download_folder", help="")
parser.set_defaults(port=8080)
parser.set_defaults(gpu=False)
parser.set_defaults(download_folder="/tmp/caffe-classifier")
args = vars(parser.parse_args())
download_folder = args["download_folder"]
make_download_folder()
model = Model(caffemodel_file=args["caffemodel"],
deploy_file=args["deploy"],
mean_file=args["mean"],
labels_file=args["labels"],
gpu=args["gpu"])
start(args["port"])