diff --git a/ultralytics/data/split_dota.py b/ultralytics/data/split_dota.py
index a8f17d41..1d1ca310 100644
--- a/ultralytics/data/split_dota.py
+++ b/ultralytics/data/split_dota.py
@@ -8,9 +8,9 @@ from pathlib import Path
 import cv2
 import numpy as np
 from PIL import Image
-from tqdm import tqdm
 
 from ultralytics.data.utils import exif_size, img2label_paths
+from ultralytics.utils import TQDM
 from ultralytics.utils.checks import check_requirements
 
 
@@ -221,7 +221,7 @@ def split_images_and_labels(data_root, save_dir, split="train", crop_sizes=(1024
     lb_dir.mkdir(parents=True, exist_ok=True)
 
     annos = load_yolo_dota(data_root, split=split)
-    for anno in tqdm(annos, total=len(annos), desc=split):
+    for anno in TQDM(annos, total=len(annos), desc=split):
         windows = get_windows(anno["ori_size"], crop_sizes, gaps)
         window_objs = get_window_obj(anno, windows)
         crop_and_save(anno, windows, window_objs, str(im_dir), str(lb_dir))
@@ -281,7 +281,7 @@ def split_test(data_root, save_dir, crop_size=1024, gap=200, rates=(1.0,)):
     im_dir = Path(data_root) / "images" / "test"
     assert im_dir.exists(), f"Can't find {im_dir}, please check your data root."
     im_files = glob(str(im_dir / "*"))
-    for im_file in tqdm(im_files, total=len(im_files), desc="test"):
+    for im_file in TQDM(im_files, total=len(im_files), desc="test"):
         w, h = exif_size(Image.open(im_file))
         windows = get_windows((h, w), crop_sizes=crop_sizes, gaps=gaps)
         im = cv2.imread(im_file)
diff --git a/ultralytics/utils/__init__.py b/ultralytics/utils/__init__.py
index 4ff46044..f3aee7b5 100644
--- a/ultralytics/utils/__init__.py
+++ b/ultralytics/utils/__init__.py
@@ -23,8 +23,8 @@ import cv2
 import matplotlib.pyplot as plt
 import numpy as np
 import torch
+import tqdm
 import yaml
-from tqdm import tqdm as tqdm_original
 
 from ultralytics import __version__
 
@@ -133,7 +133,7 @@ os.environ["TORCH_CPP_LOG_LEVEL"] = "ERROR"  # suppress "NNPACK.cpp could not in
 os.environ["KINETO_LOG_LEVEL"] = "5"  # suppress verbose PyTorch profiler output when computing FLOPs
 
 
-class TQDM(tqdm_original):
+class TQDM(tqdm.tqdm):
     """
     A custom TQDM progress bar class that extends the original tqdm functionality.