diff --git a/pyproject.toml b/pyproject.toml
index 63206e5..5adaef4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -57,3 +57,7 @@ ipykernel = "^6.25.2"
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
 
+
+[tool.ruff]
+# More than the default (88) of `black` to make comments less of a headache
+line-length = 120
diff --git a/set-detect-notify/__main__.py b/set-detect-notify/__main__.py
index 9f166ec..defefac 100644
--- a/set-detect-notify/__main__.py
+++ b/set-detect-notify/__main__.py
@@ -50,11 +50,13 @@ def main():
         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",
+        "--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",
     )
 
     argparser.add_argument(
@@ -188,8 +190,10 @@ def main():
                 # If it isn't, print a warning
                 for obj in args.detect_object:
                     if obj not in object_names:
-                        print(f"Warning: {obj} is not in the list of objects the model can detect!")
-                    
+                        print(
+                            f"Warning: {obj} is not in the list of objects the model can detect!"
+                        )
+
             for box in r.boxes:
                 # Get the name of the object
                 class_id = r.names[box.cls[0].item()]
@@ -205,13 +209,14 @@ def main():
                 # print("---")
 
                 # Now do stuff (if conf > 0.5)
-                if conf < args.confidence_threshold or (class_id not in args.detect_object and args.detect_object != []):
+                if conf < args.confidence_threshold or (
+                    class_id not in args.detect_object and args.detect_object != []
+                ):
                     # If the confidence is too low
                     # or if the object is not in the list of objects to detect and the list of objects to detect is not empty
                     # then skip this iteration
                     continue
 
-
                 # Add the object to the list of objects to plot
                 plot_boxes.append(
                     {
@@ -303,7 +308,7 @@ def main():
                 run_scale=args.run_scale,
                 view_scale=args.view_scale,
             )
-            
+
             # Display the resulting frame
             # cv2.imshow("", r)
             cv2.imshow(f"Video{i}", frame_to_show)
diff --git a/set-detect-notify/utils/utils.py b/set-detect-notify/utils/utils.py
index 5e58f31..82cac73 100644
--- a/set-detect-notify/utils/utils.py
+++ b/set-detect-notify/utils/utils.py
@@ -1,17 +1,19 @@
 import cv2
 import numpy as np
+
+
 def plot_label(
-        # list of dicts with each dict containing a label, x1, y1, x2, y2
-        boxes: list = None,
-        # opencv image
-        full_frame: np.ndarray = None,
-        # run_scale is the scale of the image that was used to run the model
-        # So the coordinates will be scaled up to the view frame size
-        run_scale: float = None, 
-        # view_scale is the scale of the image, in relation to the full frame
-        # So the coordinates will be scaled appropriately when coming from run_frame
-        view_scale: float = None,
-        font: int = cv2.FONT_HERSHEY_SIMPLEX,
+    # list of dicts with each dict containing a label, x1, y1, x2, y2
+    boxes: list = None,
+    # opencv image
+    full_frame: np.ndarray = None,
+    # run_scale is the scale of the image that was used to run the model
+    # So the coordinates will be scaled up to the view frame size
+    run_scale: float = None,
+    # view_scale is the scale of the image, in relation to the full frame
+    # So the coordinates will be scaled appropriately when coming from run_frame
+    view_scale: float = None,
+    font: int = cv2.FONT_HERSHEY_SIMPLEX,
 ):
     view_frame = cv2.resize(full_frame, (0, 0), fx=view_scale, fy=view_scale)
     for thing in boxes:
@@ -19,9 +21,15 @@ def plot_label(
             # Image
             view_frame,
             # Start point
-            (int(thing["x1"] * (run_scale/view_scale)), int(thing["y1"] * (run_scale/view_scale))),
+            (
+                int(thing["x1"] * (run_scale / view_scale)),
+                int(thing["y1"] * (run_scale / view_scale)),
+            ),
             # End point
-            (int(thing["x2"] * (run_scale/view_scale)), int(thing["y2"] * (run_scale/view_scale))),
+            (
+                int(thing["x2"] * (run_scale / view_scale)),
+                int(thing["y2"] * (run_scale / view_scale)),
+            ),
             # Color
             (0, 255, 0),
             # Thickness
@@ -33,7 +41,10 @@ def plot_label(
             # Text
             thing["label"],
             # Origin
-            (int(thing["x1"] * (run_scale/view_scale)), int(thing["y1"] * (run_scale/view_scale))),
+            (
+                int(thing["x1"] * (run_scale / view_scale)),
+                int(thing["y1"] * (run_scale / view_scale)),
+            ),
             # Font
             font,
             # Font Scale
@@ -41,6 +52,6 @@ def plot_label(
             # Color
             (0, 255, 0),
             # Thickness
-            1
+            1,
         )
-    return view_frame
\ No newline at end of file
+    return view_frame