From c56d7c86fc6e5cbafbb5653c94e0125491026961 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 1 Oct 2023 19:56:40 -0500
Subject: [PATCH] Simple object detection

---
 .gitignore                |    3 +-
 .python-version           |    1 +
 environment.yml           |  Bin 5060 -> 0 bytes
 main.py                   |  209 ----
 poetry.lock               | 2275 +++++++++++++++++++++++++++++++++++++
 pyproject.toml            |   58 +
 requirements.txt          |   11 -
 src/__init__.py           |    0
 src/__main__.py           |  129 +++
 src/utils/__init__.py     |    0
 src/utils/config_utils.py |    4 +
 src/utils/notify.py       |   38 +
 12 files changed, 2507 insertions(+), 221 deletions(-)
 create mode 100644 .python-version
 delete mode 100644 environment.yml
 delete mode 100644 main.py
 create mode 100644 poetry.lock
 create mode 100644 pyproject.toml
 delete mode 100644 requirements.txt
 create mode 100644 src/__init__.py
 create mode 100644 src/__main__.py
 create mode 100644 src/utils/__init__.py
 create mode 100644 src/utils/config_utils.py
 create mode 100644 src/utils/notify.py

diff --git a/.gitignore b/.gitignore
index 29ea3ea..6194c0c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
 .env
-config/
\ No newline at end of file
+config/
+using_yolov8.ipynb
\ No newline at end of file
diff --git a/.python-version b/.python-version
new file mode 100644
index 0000000..c84ccce
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.10.5
diff --git a/environment.yml b/environment.yml
deleted file mode 100644
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diff --git a/main.py b/main.py
deleted file mode 100644
index e899d59..0000000
--- a/main.py
+++ /dev/null
@@ -1,209 +0,0 @@
-import datetime
-import face_recognition
-import cv2
-import numpy as np
-from dotenv import load_dotenv
-import os
-import json
-import pathlib
-import requests
-import time
-
-
-load_dotenv()
-URL = os.getenv("URL")
-RUN_SCALE = os.getenv("RUN_SCALE")
-VIEW_SCALE = os.getenv("VIEW_SCALE")
-DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
-# RUN_SCALE = 0.25
-# VIEW_SCALE = 0.75
-DISPLAY = False
-RUN_BY_COMPOSE = os.getenv("RUN_BY_COMPOSE")
-NTFY_URL = os.getenv("NTFY_URL")
-
-
-def find_face_from_name(name):
-    for face in config["faces"]:
-        if config["faces"][face]["name"] == name:
-            return face
-    return None
-
-
-def write_config():
-    with open(config_path, "w") as config_file:
-        json.dump(config, config_file, indent=4)
-
-
-print("Hello, world!")
-
-# Initialize some variables
-face_locations = []
-face_encodings = []
-face_names = []
-known_face_encodings = []
-known_face_names = []
-process_this_frame = True
-
-# Load the config file, if it does not exist or is blank, create it
-config = {
-    # If RUN_BY_COMPOSE is true, set url to rtsp://wyze-bridge:8554/wyze_cam_name, otherwise set it to "rtsp://localhost:8554/wyze_cam_name"
-    "URL": "rtsp://localhost:8554/wyze_cam_name"
-    if not RUN_BY_COMPOSE
-    else "rtsp://bridge:8554/wyze_cam_name",
-    "run_scale": "0.25",
-    "view_scale": "0.75",
-    "faces": {
-        "example1": {"image": "config/example1.jpg", "last_seen": ""},
-        "example2": {"image": "config/example2.jpg", "last_seen": ""},
-    },
-    "ntfy_url": "https://ntfy.sh/example",
-    "display": True,
-}
-config_path = pathlib.Path("config/config.json")
-if config_path.exists():
-    with open(config_path, "r") as config_file:
-        config = json.load(config_file)
-else:
-    with open(config_path, "w") as config_file:
-        json.dump(config, config_file, indent=4)
-    print("Config file created, please edit it and restart the program")
-    print("For relative paths, use the format config/example.jpg")
-    exit()
-
-
-if URL:
-    config["URL"] = URL
-else:
-    URL = config["URL"]
-if RUN_SCALE:
-    config["RUN_SCALE"] = RUN_SCALE
-else:
-    RUN_SCALE = float(config["RUN_SCALE"])
-if VIEW_SCALE:
-    config["VIEW_SCALE"] = VIEW_SCALE
-else:
-    VIEW_SCALE = float(config["VIEW_SCALE"])
-if DISPLAY:
-    config["DISPLAY"] = DISPLAY
-else:
-    DISPLAY = config["display"]
-if NTFY_URL:
-    config["ntfy_url"] = NTFY_URL
-else:
-    NTFY_URL = config["ntfy_url"]
-print(f"Current config: {config}")
-
-for face in config["faces"]:
-    # Load a sample picture and learn how to recognize it.
-    image = face_recognition.load_image_file(config["faces"][face]["image"])
-    face_encoding = face_recognition.face_encodings(image)[0]
-    known_face_encodings.append(face_encoding)
-    # Append the key to the list of known face names
-    known_face_names.append(face)
-
-video_capture = cv2.VideoCapture(URL)
-# Eliminate lag by setting the buffer size to 1
-# This makes it so that the video capture will only grab the most recent frame
-# However, this means that the video may be choppy
-video_capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)
-
-# Print the resolution of the video
-print(
-    f"Video resolution: {video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)}x{video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)}"
-)
-
-print("Beginning video capture...")
-while True:
-    # Grab a single frame of video
-    ret, frame = video_capture.read()
-    # Only process every other frame of video to save time
-    # Resize frame of video to a smaller size for faster face recognition processing
-    run_frame = cv2.resize(frame, (0, 0), fx=RUN_SCALE, fy=RUN_SCALE)
-    view_frame = cv2.resize(frame, (0, 0), fx=VIEW_SCALE, fy=VIEW_SCALE)
-    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
-    rgb_run_frame = run_frame[:, :, ::-1]
-    # Find all the faces and face encodings in the current frame of video
-    # model cnn is gpu accelerated, but hog is cpu only
-    face_locations = face_recognition.face_locations(
-        rgb_run_frame, model="hog"
-    )  # This crashes the program without output on my laptop when it's running without Docker compose
-    face_encodings = face_recognition.face_encodings(rgb_run_frame, face_locations)
-    face_names = []
-    for face_encoding in face_encodings:
-        # See if the face is a match for the known face(s)
-        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
-        name = "Unknown"
-        # Or instead, use the known face with the smallest distance to the new face
-        face_distances = face_recognition.face_distance(
-            known_face_encodings, face_encoding
-        )
-        best_match_index = np.argmin(face_distances)
-        if matches[best_match_index]:
-            name = known_face_names[best_match_index]
-            last_seen = config["faces"][name]["last_seen"]
-            # If it's never been seen, set the last seen time to x+5 seconds ago so it will be seen
-            # Kind of a hacky way to do it, but it works... hopefully
-            if last_seen == "":
-                print(f"{name} has been seen for the first time")
-                config["faces"][name]["last_seen"] = (
-                    datetime.datetime.now() - datetime.timedelta(seconds=15)
-                ).strftime(DATETIME_FORMAT)
-                write_config()
-            # Check if the face has been seen in the last 5 seconds
-            if datetime.datetime.now() - datetime.datetime.strptime(
-                last_seen, DATETIME_FORMAT
-            ) > datetime.timedelta(seconds=10):
-                print(f"{name} has been seen")
-                # Send a notification
-                print(f"Sending notification to{NTFY_URL}")
-                requests.post(
-                    NTFY_URL,
-                    data=f'"{name}" has been seen',
-                    headers={
-                        "Title": "Face Detected",
-                        "Priority": "default",
-                        "Tags": "neutral_face",
-                    },
-                )
-            # Update the last seen time
-            config["faces"][name]["last_seen"] = datetime.datetime.now().strftime(
-                DATETIME_FORMAT
-            )
-            # print("Writing config...")
-            write_config()
-        face_names.append(name)
-    # Display the results
-    # Iterate over each face found in the frame to draw a box around it
-    # Zip is used to iterate over two lists at the same time
-    for (top, right, bottom, left), name in zip(face_locations, face_names):
-        # print(f"Face found at {top}, {right}, {bottom}, {left} with name {name}")
-        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
-        top = int(top * (VIEW_SCALE / RUN_SCALE))
-        right = int(right * (VIEW_SCALE / RUN_SCALE))
-        bottom = int(bottom * (VIEW_SCALE / RUN_SCALE))
-        left = int(left * (VIEW_SCALE / RUN_SCALE))
-
-        # Draw a box around the face
-        cv2.rectangle(view_frame, (left, top), (right, bottom), (0, 0, 255), 2)
-
-        # Draw a label with a name below the face
-        cv2.rectangle(
-            view_frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED
-        )
-        font = cv2.FONT_HERSHEY_DUPLEX
-        cv2.putText(
-            view_frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1
-        )
-
-    # Display the resulting image if DISPLAY is set to true
-    if config["display"]:
-        cv2.imshow("Scaled View", view_frame)
-
-    # Hit 'q' on the keyboard to quit!
-    if cv2.waitKey(1) & 0xFF == ord("q"):
-        break
-
-# Release handle to the webcam
-print("Releasing video capture")
-video_capture.release()
-cv2.destroyAllWindows()
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..16d123f
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,2275 @@
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+
+[[package]]
+name = "anyio"
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+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "anyio-4.0.0.tar.gz", hash = "sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.22)"]
+
+[[package]]
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = "*"
+files = [
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+
+[[package]]
+name = "asttokens"
+version = "2.4.0"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = "*"
+files = [
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+[package.dependencies]
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+
+[package.extras]
+test = ["astroid", "pytest"]
+
+[[package]]
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+version = "0.2.0"
+description = "Specifications for callback functions passed in to an API"
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+python-versions = "*"
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+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:9dc4444c0defcd3929d5c1eb5706cbe1b116e762ff3e0deca8b715d14bf6ec17"},
+    {file = "tornado-6.3.3-cp38-abi3-win32.whl", hash = "sha256:65ceca9500383fbdf33a98c0087cb975b2ef3bfb874cb35b8de8740cf7f41bd3"},
+    {file = "tornado-6.3.3-cp38-abi3-win_amd64.whl", hash = "sha256:22d3c2fa10b5793da13c807e6fc38ff49a4f6e1e3868b0a6f4164768bb8e20f5"},
+    {file = "tornado-6.3.3.tar.gz", hash = "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe"},
+]
+
+[[package]]
+name = "tqdm"
+version = "4.66.1"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
+    {file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
+[[package]]
+name = "traitlets"
+version = "5.10.1"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "traitlets-5.10.1-py3-none-any.whl", hash = "sha256:07ab9c5bf8a0499fd7b088ba51be899c90ffc936ffc797d7b6907fc516bcd116"},
+    {file = "traitlets-5.10.1.tar.gz", hash = "sha256:db9c4aa58139c3ba850101913915c042bdba86f7c8a0dda1c6f7f92c5da8e542"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.5.1)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
+
+[[package]]
+name = "typing-extensions"
+version = "4.8.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"},
+    {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
+]
+
+[[package]]
+name = "tzdata"
+version = "2023.3"
+description = "Provider of IANA time zone data"
+optional = false
+python-versions = ">=2"
+files = [
+    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
+    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+]
+
+[[package]]
+name = "ultralytics"
+version = "8.0.190"
+description = "Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "ultralytics-8.0.190-py3-none-any.whl", hash = "sha256:5414bbf741b92cac438238c3b5608b57521e56f25e2e6297a7447b451954a413"},
+    {file = "ultralytics-8.0.190.tar.gz", hash = "sha256:ebbd60108dad6c713755f3d456b35fbd6640a73c4c870140d2c8f02626ba6105"},
+]
+
+[package.dependencies]
+matplotlib = ">=3.3.0"
+numpy = ">=1.22.2"
+opencv-python = ">=4.6.0"
+pandas = ">=1.1.4"
+pillow = ">=7.1.2"
+psutil = "*"
+py-cpuinfo = "*"
+pyyaml = ">=5.3.1"
+requests = ">=2.23.0"
+scipy = ">=1.4.1"
+seaborn = ">=0.11.0"
+thop = ">=0.1.1"
+torch = ">=1.8.0"
+torchvision = ">=0.9.0"
+tqdm = ">=4.64.0"
+
+[package.extras]
+dev = ["check-manifest", "coverage", "ipython", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.27)", "mkdocstrings[python]", "pytest", "pytest-cov"]
+export = ["coremltools (>=7.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs"]
+
+[[package]]
+name = "urllib3"
+version = "2.0.5"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "urllib3-2.0.5-py3-none-any.whl", hash = "sha256:ef16afa8ba34a1f989db38e1dbbe0c302e4289a47856990d0682e374563ce35e"},
+    {file = "urllib3-2.0.5.tar.gz", hash = "sha256:13abf37382ea2ce6fb744d4dad67838eec857c9f4f57009891805e0b5e123594"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.8"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
+    {file = "wcwidth-0.2.8-py2.py3-none-any.whl", hash = "sha256:77f719e01648ed600dfa5402c347481c0992263b81a027344f3e1ba25493a704"},
+    {file = "wcwidth-0.2.8.tar.gz", hash = "sha256:8705c569999ffbb4f6a87c6d1b80f324bd6db952f5eb0b95bc07517f4c1813d4"},
+]
+
+[extras]
+cuda = []
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.10"
+content-hash = "499ba7db34c4f338fdafb61e1bed488e252c8d637226a63a3e5eb367b2d132bc"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..821d232
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,58 @@
+[tool.poetry]
+name = "detect-it"
+version = "0.1.0"
+description = "Detect all the things"
+authors = ["slashtechno <77907286+slashtechno@users.noreply.github.com>"]
+license = "MIT"
+readme = "README.md"
+packages = [{include = "detect_it"}]
+
+[tool.poetry.dependencies]
+python = "^3.10"
+python-dotenv = "^1.0.0"
+httpx = "^0.25.0"
+opencv-python = "^4.8.1.78"
+ultralytics = "^8.0.190"
+hjson = "^3.1.0"
+numpy = "^1.23.2"
+torch = [
+  { version = "^2.0.0+cu118", source = "torch_cu118", markers = "extra=='cuda'" },
+  { version = "^2.0.0+cpu", source = "torch_cpu", markers = "extra!='cuda'" },
+]
+torchaudio = [
+  { version = "^2.0.0+cu118", source = "torch_cu118", markers = "extra=='cuda'" },
+  { version = "^2.0.0+cpu", source = "torch_cpu", markers = "extra!='cuda'" },
+]
+torchvision = [
+  { version = "^0.15+cu118", source = "torch_cu118", markers = "extra=='cuda'" },
+  { version = "^0.15+cpu", source = "torch_cpu", markers = "extra!='cuda'" },
+]
+
+
+[tool.poetry.group.dev.dependencies]
+black = "^23.9.1"
+ruff = "^0.0.291"
+ipykernel = "^6.25.2"
+
+
+[[tool.poetry.source]]
+name = "torch_cpu"
+url = "https://download.pytorch.org/whl/cpu"
+priority = "supplemental"
+
+[[tool.poetry.source]]
+name = "torch_cu118"
+url = "https://download.pytorch.org/whl/cu118"
+priority = "supplemental"
+
+[tool.poetry.extras]
+cuda = []
+
+[[tool.poetry.source]]
+name = "PyPI"
+priority = "primary"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 1a8bd33..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,11 +0,0 @@
-# certifi @ file:///croot/certifi_1665076670883/work/certifi
-click==8.1.3
-dlib==19.24.0
-face-recognition==1.3.0
-face-recognition-models==0.3.0
-numpy==1.23.5
-opencv-python==4.6.0.66
-Pillow==9.3.0
-python-dotenv==0.21.0
-urllib3==1.26.13
-requests==2.31.0
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/__main__.py b/src/__main__.py
new file mode 100644
index 0000000..e47f822
--- /dev/null
+++ b/src/__main__.py
@@ -0,0 +1,129 @@
+# import face_recognition
+import cv2
+import numpy as np
+import dotenv
+from pathlib import Path
+import os
+import time
+# import hjson as json
+import torch
+from ultralytics import YOLO
+
+import argparse
+
+from .utils import notify, config_utils
+
+DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
+args = None
+
+def main():
+    global args
+    # RUN_BY_COMPOSE = os.getenv("RUN_BY_COMPOSE") # Replace this with code to check for gpu
+
+    if Path(".env").is_file():
+        dotenv.load_dotenv()
+        print("Loaded .env file")
+    else:
+        print("No .env file found")
+
+    argparser = argparse.ArgumentParser(
+        prog="Detect It",
+        description="Detect it all!",
+        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,  # noqa: E501
+    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,  # noqa: E501
+    # type=float,
+    # help="The scale to view the detection at, default is 0.75",
+    # )
+
+    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."
+    )
+
+    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'] != '' else None,  # noqa: E501
+        type=str,
+        help="The URL to send notifications to",
+    )
+
+    args = argparser.parse_args()
+
+    # Check if a CUDA GPU is available. If it is, set it via torch. Ff not, set it to cpu
+    # https://github.com/ultralytics/ultralytics/issues/3084#issuecomment-1732433168
+    device = "0" if torch.cuda.is_available() else "cpu"
+    if device == "0":
+        torch.cuda.set_device(0)
+        print("Set CUDA device")
+    else: 
+        print("No CUDA device available, using CPU")
+    
+    model = YOLO("yolov8n.pt")
+
+    video_capture = cv2.VideoCapture(args.capture_device)
+    # Eliminate lag by setting the buffer size to 1
+    # This makes it so that the video capture will only grab the most recent frame
+    # However, this means that the video may be choppy
+    video_capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)
+
+
+    # Print the resolution of the video
+    print(
+        f"Video resolution: {video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)}x{video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)}"  # noqa: E501
+    )
+
+    print("Beginning video capture...")
+    while True:
+        # Grab a single frame of video
+        ret, frame = video_capture.read()
+        # Only process every other frame of video to save time
+        # Resize frame of video to a smaller size for faster recognition processing
+        run_frame = cv2.resize(frame, (0, 0), fx=args.run_scale, fy=args.run_scale)
+        # view_frame = cv2.resize(frame, (0, 0), fx=args.view_scale, fy=args.view_scale)
+    
+        results = model(run_frame)
+        for r in results:
+            
+            im_array = r.plot()
+            # Scale back up the coordinates of the locations of detected objects.
+            # im_array = np.multiply(im_array, 1/args.run_scale)
+            # print(type(im_array))
+            # print(im_array)
+            # exit()
+            cv2.imshow("View", im_array)
+            
+
+        # Hit 'q' on the keyboard to quit!
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+
+    # Release handle to the webcam
+    print("Releasing video capture")
+    video_capture.release()
+    cv2.destroyAllWindows()
+
+main()
\ No newline at end of file
diff --git a/src/utils/__init__.py b/src/utils/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/utils/config_utils.py b/src/utils/config_utils.py
new file mode 100644
index 0000000..44f0f92
--- /dev/null
+++ b/src/utils/config_utils.py
@@ -0,0 +1,4 @@
+
+# def write_config():
+#     with open(config_path, "w") as config_file:
+#         json.dump(config, config_file, indent=4)
diff --git a/src/utils/notify.py b/src/utils/notify.py
new file mode 100644
index 0000000..6447d66
--- /dev/null
+++ b/src/utils/notify.py
@@ -0,0 +1,38 @@
+import datetime
+import httpx
+
+
+def construct_ntfy_headers(
+        title: str = "Object/Person Detected",
+        tag = "rotating_light", # https://docs.ntfy.sh/publish/#tags-emojis
+        priority = "default", #  https://docs.ntfy.sh/publish/#message-priority
+) -> (dict):
+     return {
+          'Title': title,
+          'Priority': priority,
+         'Tags': tag
+     }
+
+def send_notification(
+        data: str,
+        headers: dict,
+        url: str
+):
+    if url is None or data is None:
+         raise ValueError("url and data cannot be None")
+    httpx.post(url, data=data.encode('utf-8'), headers=headers)
+
+def check_last_seen(last_seen: datetime.datetime, seconds: int = 15):
+        '''
+        Check if a time is older than a given number of seconds
+        If it is, return True
+        If last_seen is empty/null, return True
+        '''
+        if (
+             datetime.datetime.now() - last_seen > datetime.timedelta(seconds=seconds)
+            or last_seen == ""
+            or last_seen is None
+            ): 
+            return True
+        else:
+            return False
\ No newline at end of file