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Use TQDM class (#18846)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2025-01-23 13:57:08 +01:00 • committed by GitHub
parent d29023f85f
commit ad23a913df
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2 changed files with 5 additions and 5 deletions
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6
ultralytics/data/split_dota.py
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@ -8,9 +8,9 @@ from pathlib import Path
import cv2 import cv2
import numpy as np import numpy as np
from PIL import Image from PIL import Image
from tqdm import tqdm
from ultralytics.data.utils import exif_size, img2label_paths from ultralytics.data.utils import exif_size, img2label_paths
from ultralytics.utils import TQDM
from ultralytics.utils.checks import check_requirements 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) lb_dir.mkdir(parents=True, exist_ok=True)
annos = load_yolo_dota(data_root, split=split) 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) windows = get_windows(anno["ori_size"], crop_sizes, gaps)
window_objs = get_window_obj(anno, windows) window_objs = get_window_obj(anno, windows)
crop_and_save(anno, windows, window_objs, str(im_dir), str(lb_dir)) 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" im_dir = Path(data_root) / "images" / "test"
assert im_dir.exists(), f"Can't find {im_dir}, please check your data root." assert im_dir.exists(), f"Can't find {im_dir}, please check your data root."
im_files = glob(str(im_dir / "*")) 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)) w, h = exif_size(Image.open(im_file))
windows = get_windows((h, w), crop_sizes=crop_sizes, gaps=gaps) windows = get_windows((h, w), crop_sizes=crop_sizes, gaps=gaps)
im = cv2.imread(im_file) im = cv2.imread(im_file)

4
ultralytics/utils/__init__.py
View file

@ -23,8 +23,8 @@ import cv2
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import torch import torch
import tqdm
import yaml import yaml
from tqdm import tqdm as tqdm_original
from ultralytics import __version__ 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 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. A custom TQDM progress bar class that extends the original tqdm functionality.