💚 [Pass] format check and refactor code

yolo/tools/data_augmentation.py

@@ -67,7 +67,7 @@ class PadAndResize:
         scale = min(self.target_width / img_width, self.target_height / img_height)
         new_width, new_height = int(img_width * scale), int(img_height * scale)
 
-        resized_image = image.resize((new_width, new_height), Image.LANCZOS)
+        resized_image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
 
         pad_left = (self.target_width - new_width) // 2
         pad_top = (self.target_height - new_height) // 2

yolo/tools/solver.py

@@ -48,8 +48,9 @@ class ValidateModel(BaseModel):
         batch_size, images, targets, rev_tensor, img_paths = batch
         H, W = images.shape[2:]
         predicts = self.post_process(self.ema(images), image_size=[W, H])
-        self.metric.update([to_metrics_format(predict) for predict in predicts],
-                           [to_metrics_format(target) for target in targets])
+        self.metric.update(
+            [to_metrics_format(predict) for predict in predicts], [to_metrics_format(target) for target in targets]
+        )
         return predicts
 
     def on_validation_epoch_end(self):

yolo/utils/dataset_utils.py

@@ -104,13 +104,8 @@ def scale_segmentation(
         if "segmentation" in anno:
             seg_list = [item for sublist in anno["segmentation"] for item in sublist]
         elif "bbox" in anno:
-            x,y,width,height = anno["bbox"]
-            seg_list = [
-                x, y,  # Top-left corner
-                x + width, y,  # Top-right corner
-                x + width, y + height,  # Bottom-right corner
-                x, y + height  # Bottom-left corner
-            ]
+            x, y, width, height = anno["bbox"]
+            seg_list = [x, y, x + width, y, x + width, y + height, x, y + height]
 
         scaled_seg_data = (
             np.array(seg_list).reshape(-1, 2) / [w, h]