Format

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

set-detect-notify/__main__.py

@@ -50,9 +50,11 @@ def main():
         help="The scale to run the detection at, default is 0.25",
     )
     argparser.add_argument(
-    '--view-scale',
+        "--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
+        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",
     )
@@ -188,7 +190,9 @@ 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
@@ -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(
                     {

set-detect-notify/utils/utils.py

@@ -1,5 +1,7 @@
 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,
@@ -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