wyzely-detect/wyzely_detect/utils/cli_args.py

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2023-10-27 16:54:36 +01:00
import argparse
import os
import dotenv
from pathlib import Path
argparser = None
def set_argparse():
global argparser
if Path(".env").is_file():
dotenv.load_dotenv()
print("Loaded .env file")
else:
print("No .env file found")
argparser = argparse.ArgumentParser(
prog="Wyzely Detect",
description="Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices", # noqa: E501
epilog=":)",
)
# required='RUN_SCALE' not in os.environ,
argparser.add_argument(
"--run-scale",
# Set it to the env RUN_SCALE if it isn't blank, otherwise set it to 0.25
default=os.environ["RUN_SCALE"]
if "RUN_SCALE" in os.environ and os.environ["RUN_SCALE"] != ""
# else 0.25,
else 1,
type=float,
help="The scale to run the detection at, default is 0.25",
)
argparser.add_argument(
"--view-scale",
# Set it to the env VIEW_SCALE if it isn't blank, otherwise set it to 0.75
default=os.environ["VIEW_SCALE"]
if "VIEW_SCALE" in os.environ and os.environ["VIEW_SCALE"] != ""
# else 0.75,
else 1,
type=float,
help="The scale to view the detection at, default is 0.75",
)
argparser.add_argument(
"--no-display",
default=os.environ["NO_DISPLAY"]
if "NO_DISPLAY" in os.environ and os.environ["NO_DISPLAY"] != ""
else False,
action="store_true",
help="Don't display the video feed",
)
argparser.add_argument(
"--confidence-threshold",
default=os.environ["CONFIDENCE_THRESHOLD"]
if "CONFIDENCE_THRESHOLD" in os.environ
and os.environ["CONFIDENCE_THRESHOLD"] != ""
else 0.6,
type=float,
help="The confidence threshold to use",
)
argparser.add_argument(
"--faces-directory",
default=os.environ["FACES_DIRECTORY"]
if "FACES_DIRECTORY" in os.environ and os.environ["FACES_DIRECTORY"] != ""
else "faces",
type=str,
help="The directory to store the faces. Can either contain images or subdirectories with images, the latter being the preferred method", # noqa: E501
)
argparser.add_argument(
"--detect-object",
nargs="*",
default=[],
type=str,
help="The object(s) to detect. Must be something the model is trained to detect",
)
stream_source = argparser.add_mutually_exclusive_group()
stream_source.add_argument(
"--url",
default=os.environ["URL"]
if "URL" in os.environ and os.environ["URL"] != ""
else None, # noqa: E501
type=str,
help="The URL of the stream to use",
)
stream_source.add_argument(
"--capture-device",
default=os.environ["CAPTURE_DEVICE"]
if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != ""
else 0, # noqa: E501
type=int,
help="The capture device to use. Can also be a url.",
)
# Defaults for the stuff here and down are already set in notify.py.
# Setting them here just means that argparse will display the default values as defualt
notifcation_services = argparser.add_argument_group("Notification Services")
notifcation_services.add_argument(
"--ntfy-url",
default=os.environ["NTFY_URL"]
if "NTFY_URL" in os.environ and os.environ["NTFY_URL"] != ""
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else None,
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type=str,
help="The URL to send notifications to",
)
timers = argparser.add_argument_group("Timers")
timers.add_argument(
"--detection-duration",
default=os.environ["DETECTION_DURATION"]
if "DETECTION_DURATION" in os.environ and os.environ["DETECTION_DURATION"] != ""
else 2,
type=int,
help="The duration (in seconds) that an object must be detected for before sending a notification",
)
timers.add_argument(
"--detection-window",
default=os.environ["DETECTION_WINDOW"]
if "DETECTION_WINDOW" in os.environ and os.environ["DETECTION_WINDOW"] != ""
else 15,
type=int,
help="The time (seconds) before the detection duration resets",
)
timers.add_argument(
"--notification-window",
default=os.environ["NOTIFICATION_WINDOW"]
if "NOTIFICATION_WINDOW" in os.environ
and os.environ["NOTIFICATION_WINDOW"] != ""
else 30,
type=int,
help="The time (seconds) before another notification can be sent",
)
# return argparser
# This will run when this file is imported
set_argparse()