Move argparse code to `cli_args.py`
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8EC1D9D9286C2B17
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@ -1,17 +1,14 @@
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# import face_recognition
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import cv2
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import dotenv
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from pathlib import Path
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import os
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import cv2
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# import hjson as json
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import torch
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from ultralytics import YOLO
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import argparse
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from .utils import notify
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from .utils import utils
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from .utils import notify, utils
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from .utils.cli_args import argparser
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DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
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args = None
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@ -27,136 +24,6 @@ def main():
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global args
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# RUN_BY_COMPOSE = os.getenv("RUN_BY_COMPOSE") # Replace this with code to check for gpu
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if Path(".env").is_file():
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dotenv.load_dotenv()
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print("Loaded .env file")
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else:
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print("No .env file found")
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# TODO: If possible, move the argparse stuff to a separate file
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# It's taking up too many lines in this file
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argparser = argparse.ArgumentParser(
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prog="Wyzely Detect",
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description="Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices", # noqa: E501
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epilog=":)",
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)
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# required='RUN_SCALE' not in os.environ,
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argparser.add_argument(
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"--run-scale",
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# Set it to the env RUN_SCALE if it isn't blank, otherwise set it to 0.25
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default=os.environ["RUN_SCALE"]
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if "RUN_SCALE" in os.environ and os.environ["RUN_SCALE"] != ""
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# else 0.25,
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else 1,
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type=float,
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help="The scale to run the detection at, default is 0.25",
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)
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argparser.add_argument(
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"--view-scale",
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# Set it to the env VIEW_SCALE if it isn't blank, otherwise set it to 0.75
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default=os.environ["VIEW_SCALE"]
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if "VIEW_SCALE" in os.environ and os.environ["VIEW_SCALE"] != ""
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# else 0.75,
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else 1,
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type=float,
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help="The scale to view the detection at, default is 0.75",
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)
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argparser.add_argument(
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"--no-display",
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default=os.environ["NO_DISPLAY"]
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if "NO_DISPLAY" in os.environ and os.environ["NO_DISPLAY"] != ""
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else False,
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action="store_true",
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help="Don't display the video feed",
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)
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argparser.add_argument(
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"--confidence-threshold",
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default=os.environ["CONFIDENCE_THRESHOLD"]
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if "CONFIDENCE_THRESHOLD" in os.environ
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and os.environ["CONFIDENCE_THRESHOLD"] != ""
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else 0.6,
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type=float,
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help="The confidence threshold to use",
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)
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argparser.add_argument(
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"--faces-directory",
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default=os.environ["FACES_DIRECTORY"]
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if "FACES_DIRECTORY" in os.environ and os.environ["FACES_DIRECTORY"] != ""
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else "faces",
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type=str,
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help="The directory to store the faces. Can either contain images or subdirectories with images, the latter being the preferred method", # noqa: E501
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)
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argparser.add_argument(
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"--detect-object",
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nargs="*",
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default=[],
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type=str,
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help="The object(s) to detect. Must be something the model is trained to detect",
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)
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stream_source = argparser.add_mutually_exclusive_group()
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stream_source.add_argument(
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"--url",
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default=os.environ["URL"]
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if "URL" in os.environ and os.environ["URL"] != ""
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else None, # noqa: E501
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type=str,
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help="The URL of the stream to use",
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)
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stream_source.add_argument(
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"--capture-device",
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default=os.environ["CAPTURE_DEVICE"]
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if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != ""
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else 0, # noqa: E501
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type=int,
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help="The capture device to use. Can also be a url.",
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)
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# Defaults for the stuff here and down are already set in notify.py.
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# Setting them here just means that argparse will display the default values as defualt
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# TODO: Perhaps just remove the default parameter and just add to the help message that the default is set is x
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# TODO: Make ntfy optional in ntfy.py. Currently, unless there is a local or LAN instance of ntfy, this can't run offline
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notifcation_services = argparser.add_argument_group("Notification Services")
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notifcation_services.add_argument(
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"--ntfy-url",
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default=os.environ["NTFY_URL"]
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if "NTFY_URL" in os.environ and os.environ["NTFY_URL"] != ""
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else "https://ntfy.sh/wyzely-detect",
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type=str,
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help="The URL to send notifications to",
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)
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timers = argparser.add_argument_group("Timers")
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timers.add_argument(
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"--detection-duration",
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default=os.environ["DETECTION_DURATION"]
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if "DETECTION_DURATION" in os.environ and os.environ["DETECTION_DURATION"] != ""
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else 2,
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type=int,
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help="The duration (in seconds) that an object must be detected for before sending a notification",
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)
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timers.add_argument(
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"--detection-window",
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default=os.environ["DETECTION_WINDOW"]
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if "DETECTION_WINDOW" in os.environ and os.environ["DETECTION_WINDOW"] != ""
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else 15,
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type=int,
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help="The time (seconds) before the detection duration resets",
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)
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timers.add_argument(
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"--notification-window",
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default=os.environ["NOTIFICATION_WINDOW"]
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if "NOTIFICATION_WINDOW" in os.environ
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and os.environ["NOTIFICATION_WINDOW"] != ""
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else 30,
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type=int,
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help="The time (seconds) before another notification can be sent",
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)
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args = argparser.parse_args()
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@ -0,0 +1,142 @@
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import argparse
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import os
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import dotenv
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from pathlib import Path
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argparser = None
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def set_argparse():
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global argparser
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if Path(".env").is_file():
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dotenv.load_dotenv()
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print("Loaded .env file")
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else:
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print("No .env file found")
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argparser = argparse.ArgumentParser(
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prog="Wyzely Detect",
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description="Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices", # noqa: E501
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epilog=":)",
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)
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# required='RUN_SCALE' not in os.environ,
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argparser.add_argument(
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"--run-scale",
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# Set it to the env RUN_SCALE if it isn't blank, otherwise set it to 0.25
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default=os.environ["RUN_SCALE"]
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if "RUN_SCALE" in os.environ and os.environ["RUN_SCALE"] != ""
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# else 0.25,
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else 1,
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type=float,
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help="The scale to run the detection at, default is 0.25",
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)
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argparser.add_argument(
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"--view-scale",
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# Set it to the env VIEW_SCALE if it isn't blank, otherwise set it to 0.75
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default=os.environ["VIEW_SCALE"]
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if "VIEW_SCALE" in os.environ and os.environ["VIEW_SCALE"] != ""
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# else 0.75,
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else 1,
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type=float,
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help="The scale to view the detection at, default is 0.75",
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)
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argparser.add_argument(
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"--no-display",
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default=os.environ["NO_DISPLAY"]
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if "NO_DISPLAY" in os.environ and os.environ["NO_DISPLAY"] != ""
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else False,
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action="store_true",
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help="Don't display the video feed",
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)
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argparser.add_argument(
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"--confidence-threshold",
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default=os.environ["CONFIDENCE_THRESHOLD"]
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if "CONFIDENCE_THRESHOLD" in os.environ
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and os.environ["CONFIDENCE_THRESHOLD"] != ""
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else 0.6,
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type=float,
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help="The confidence threshold to use",
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)
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argparser.add_argument(
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"--faces-directory",
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default=os.environ["FACES_DIRECTORY"]
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if "FACES_DIRECTORY" in os.environ and os.environ["FACES_DIRECTORY"] != ""
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else "faces",
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type=str,
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help="The directory to store the faces. Can either contain images or subdirectories with images, the latter being the preferred method", # noqa: E501
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)
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argparser.add_argument(
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"--detect-object",
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nargs="*",
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default=[],
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type=str,
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help="The object(s) to detect. Must be something the model is trained to detect",
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)
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stream_source = argparser.add_mutually_exclusive_group()
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stream_source.add_argument(
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"--url",
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default=os.environ["URL"]
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if "URL" in os.environ and os.environ["URL"] != ""
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else None, # noqa: E501
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type=str,
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help="The URL of the stream to use",
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)
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stream_source.add_argument(
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"--capture-device",
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default=os.environ["CAPTURE_DEVICE"]
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if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != ""
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else 0, # noqa: E501
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type=int,
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help="The capture device to use. Can also be a url.",
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)
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# Defaults for the stuff here and down are already set in notify.py.
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# Setting them here just means that argparse will display the default values as defualt
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# TODO: Perhaps just remove the default parameter and just add to the help message that the default is set is x
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# TODO: Make ntfy optional in ntfy.py. Currently, unless there is a local or LAN instance of ntfy, this can't run offline
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notifcation_services = argparser.add_argument_group("Notification Services")
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notifcation_services.add_argument(
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"--ntfy-url",
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default=os.environ["NTFY_URL"]
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if "NTFY_URL" in os.environ and os.environ["NTFY_URL"] != ""
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else "https://ntfy.sh/wyzely-detect",
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type=str,
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help="The URL to send notifications to",
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)
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timers = argparser.add_argument_group("Timers")
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timers.add_argument(
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"--detection-duration",
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default=os.environ["DETECTION_DURATION"]
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if "DETECTION_DURATION" in os.environ and os.environ["DETECTION_DURATION"] != ""
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else 2,
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type=int,
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help="The duration (in seconds) that an object must be detected for before sending a notification",
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)
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timers.add_argument(
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"--detection-window",
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default=os.environ["DETECTION_WINDOW"]
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if "DETECTION_WINDOW" in os.environ and os.environ["DETECTION_WINDOW"] != ""
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else 15,
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type=int,
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help="The time (seconds) before the detection duration resets",
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)
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timers.add_argument(
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"--notification-window",
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default=os.environ["NOTIFICATION_WINDOW"]
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if "NOTIFICATION_WINDOW" in os.environ
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and os.environ["NOTIFICATION_WINDOW"] != ""
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else 30,
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type=int,
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help="The time (seconds) before another notification can be sent",
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)
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# return argparser
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# This will run when this file is imported
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set_argparse()
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@ -134,7 +134,7 @@ def recognize_face(
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# So we can just grab the path from there
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# iloc = Integer LOCation
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path_to_image = Path(df.iloc[-1]["identity"])
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# If the parent name is the same as the path to the database, then set label to the image name instead of the parent directory name
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# If the parent name is the same as the path to the database, then set label to the image name instead of the parent name
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if path_to_image.parent == Path(path_to_directory):
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label = path_to_image.name
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else:
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