💄 Format code using isort and black

Author: ishandutta0098

mukh/detection/models/blazeface/blazeface_detector.py

@@ -46,12 +46,16 @@ def __init__(
             confidence_threshold: Minimum confidence threshold for detections
         """
         super().__init__(confidence_threshold)
-        
+
         # Use default paths from package if not provided
         if weights_path is None:
-            weights_path = resource_filename('mukh', 'detection/models/blazeface/blazeface.pth')
+            weights_path = resource_filename(
+                "mukh", "detection/models/blazeface/blazeface.pth"
+            )
         if anchors_path is None:
-            anchors_path = resource_filename('mukh', 'detection/models/blazeface/anchors.npy')
+            anchors_path = resource_filename(
+                "mukh", "detection/models/blazeface/anchors.npy"
+            )
 
         self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
         self.net = BlazeFace().to(self.device)

mukh/detection/models/ultralight/ultralight_detector.py

@@ -60,11 +60,15 @@ def __init__(
         """
         super().__init__(confidence_threshold)
 
-         # Use default paths from package if not provided
+        # Use default paths from package if not provided
         if weights_path is None:
-            weights_path = resource_filename('mukh', 'detection/models/ultralight/pretrained/version-RFB-320.pth')
+            weights_path = resource_filename(
+                "mukh", "detection/models/ultralight/pretrained/version-RFB-320.pth"
+            )
         if labels_path is None:
-            labels_path = resource_filename('mukh', 'detection/models/ultralight/voc-model-labels.txt')
+            labels_path = resource_filename(
+                "mukh", "detection/models/ultralight/voc-model-labels.txt"
+            )
 
         self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
         self.input_size = input_size