PyUpgrade 3.8 updates (#15941)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/data/converter.py

@@ -490,7 +490,7 @@ def convert_dota_to_yolo_obb(dota_root_path: str):
                 normalized_coords = [
                     coords[i] / image_width if i % 2 == 0 else coords[i] / image_height for i in range(8)
                 ]
-                formatted_coords = ["{:.6g}".format(coord) for coord in normalized_coords]
+                formatted_coords = [f"{coord:.6g}" for coord in normalized_coords]
                 g.write(f"{class_idx} {' '.join(formatted_coords)}\n")
 
     for phase in ["train", "val"]:

ultralytics/data/dataset.py

@@ -296,7 +296,7 @@ class GroundingDataset(YOLODataset):
         """Loads annotations from a JSON file, filters, and normalizes bounding boxes for each image."""
         labels = []
         LOGGER.info("Loading annotation file...")
-        with open(self.json_file, "r") as f:
+        with open(self.json_file) as f:
             annotations = json.load(f)
         images = {f'{x["id"]:d}': x for x in annotations["images"]}
         img_to_anns = defaultdict(list)

ultralytics/data/split_dota.py

@@ -193,7 +193,7 @@ def crop_and_save(anno, windows, window_objs, im_dir, lb_dir, allow_background_i
 
             with open(Path(lb_dir) / f"{new_name}.txt", "w") as f:
                 for lb in label:
-                    formatted_coords = ["{:.6g}".format(coord) for coord in lb[1:]]
+                    formatted_coords = [f"{coord:.6g}" for coord in lb[1:]]
                     f.write(f"{int(lb[0])} {' '.join(formatted_coords)}\n")