mirror of
https://github.com/THU-MIG/yolov10.git
synced 2025-05-23 05:24:22 +08:00
ultralytics 8.0.157
fix unzip_file()
bug (#4407)
Co-authored-by: Nadim Bou Alwan <64587372+nadinator@users.noreply.github.com>
This commit is contained in:
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4885538693
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aaba14e6b2
@ -198,7 +198,7 @@ The ideal scenario is for all class ratios to be reasonably similar for each spl
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with open(dataset_yaml, 'w') as ds_y:
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yaml.safe_dump({
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'path': save_path.as_posix(),
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'path': split_dir.as_posix(),
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'train': 'train',
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'val': 'val',
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'names': classes
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@ -53,14 +53,6 @@ keywords: Ultralytics, data utils, YOLO, img2label_paths, exif_size, polygon2mas
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## ::: ultralytics.data.utils.compress_one_image
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<br><br>
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---
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## ::: ultralytics.data.utils.delete_dsstore
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<br><br>
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---
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## ::: ultralytics.data.utils.zip_directory
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<br><br>
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---
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## ::: ultralytics.data.utils.autosplit
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<br><br>
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@ -13,6 +13,10 @@ keywords: Ultralytics, YOLO, download utilities, is_url, check_disk_space, get_g
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## ::: ultralytics.utils.downloads.is_url
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<br><br>
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---
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## ::: ultralytics.utils.downloads.delete_dsstore
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<br><br>
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---
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## ::: ultralytics.utils.downloads.zip_directory
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<br><br>
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@ -7,7 +7,7 @@ import pytest
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from ultralytics.utils import ROOT, SETTINGS
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WEIGHT_DIR = Path(SETTINGS['weights_dir'])
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WEIGHTS_DIR = Path(SETTINGS['weights_dir'])
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TASK_ARGS = [
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('detect', 'yolov8n', 'coco8.yaml'),
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('segment', 'yolov8n-seg', 'coco8-seg.yaml'),
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@ -40,17 +40,17 @@ def test_train(task, model, data):
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@pytest.mark.parametrize('task,model,data', TASK_ARGS)
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def test_val(task, model, data):
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run(f'yolo val {task} model={WEIGHT_DIR / model}.pt data={data} imgsz=32')
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run(f'yolo val {task} model={WEIGHTS_DIR / model}.pt data={data} imgsz=32')
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@pytest.mark.parametrize('task,model,data', TASK_ARGS)
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def test_predict(task, model, data):
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run(f"yolo predict model={WEIGHT_DIR / model}.pt source={ROOT / 'assets'} imgsz=32 save save_crop save_txt")
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run(f"yolo predict model={WEIGHTS_DIR / model}.pt source={ROOT / 'assets'} imgsz=32 save save_crop save_txt")
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@pytest.mark.parametrize('model,format', EXPORT_ARGS)
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def test_export(model, format):
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run(f'yolo export model={WEIGHT_DIR / model}.pt format={format} imgsz=32')
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run(f'yolo export model={WEIGHTS_DIR / model}.pt format={format} imgsz=32')
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def test_rtdetr(task='detect', model='yolov8n-rtdetr.yaml', data='coco8.yaml'):
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@ -59,7 +59,7 @@ def test_rtdetr(task='detect', model='yolov8n-rtdetr.yaml', data='coco8.yaml'):
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run(f"yolo predict {task} model={model} source={ROOT / 'assets/bus.jpg'} imgsz=640 save save_crop save_txt")
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def test_fastsam(task='segment', model=WEIGHT_DIR / 'FastSAM-s.pt', data='coco8-seg.yaml'):
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def test_fastsam(task='segment', model=WEIGHTS_DIR / 'FastSAM-s.pt', data='coco8-seg.yaml'):
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source = ROOT / 'assets/bus.jpg'
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run(f'yolo segment val {task} model={model} data={data} imgsz=32')
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@ -95,7 +95,7 @@ def test_mobilesam():
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from ultralytics import SAM
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# Load the model
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model = SAM(WEIGHT_DIR / 'mobile_sam.pt')
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model = SAM(WEIGHTS_DIR / 'mobile_sam.pt')
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# Source
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source = ROOT / 'assets/zidane.jpg'
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@ -26,7 +26,7 @@ TMP = (ROOT / '../tests/tmp').resolve() # temp directory for test files
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def test_model_forward():
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model = YOLO(CFG)
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model(SOURCE, imgsz=32)
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model(SOURCE, imgsz=32, augment=True)
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def test_model_info():
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@ -120,8 +120,8 @@ def test_train_scratch():
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def test_train_pretrained():
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model = YOLO(MODEL)
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model.train(data='coco8.yaml', epochs=1, imgsz=32, cache='ram') # test RAM caching
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model = YOLO(WEIGHTS_DIR / 'yolov8n-seg.pt')
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model.train(data='coco8-seg.yaml', epochs=1, imgsz=32, cache='ram', copy_paste=0.5, mixup=0.5) # test RAM caching
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model(SOURCE)
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@ -232,7 +232,8 @@ def test_results():
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@pytest.mark.skipif(not ONLINE, reason='environment is offline')
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def test_data_utils():
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# Test functions in ultralytics/data/utils.py
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from ultralytics.data.utils import HUBDatasetStats, autosplit, zip_directory
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from ultralytics.data.utils import HUBDatasetStats, autosplit
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from ultralytics.utils.downloads import zip_directory
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# from ultralytics.utils.files import WorkingDirectory
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# with WorkingDirectory(ROOT.parent / 'tests'):
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@ -240,7 +241,7 @@ def test_data_utils():
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download('https://github.com/ultralytics/hub/raw/master/example_datasets/coco8.zip', unzip=False)
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shutil.move('coco8.zip', TMP)
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stats = HUBDatasetStats(TMP / 'coco8.zip', task='detect')
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stats.get_json(save=False)
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stats.get_json(save=True)
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stats.process_images()
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autosplit(TMP / 'coco8')
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@ -267,3 +268,11 @@ def test_events():
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cfg = copy(DEFAULT_CFG) # does not require deepcopy
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cfg.mode = 'test'
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events(cfg)
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def test_utils_checks():
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from ultralytics.utils.checks import check_yolov5u_filename, git_describe
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check_yolov5u_filename('yolov5.pt')
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# check_imshow(warn=True)
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git_describe(ROOT)
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@ -1,6 +1,6 @@
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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__version__ = '8.0.156'
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__version__ = '8.0.157'
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from ultralytics.hub import start
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from ultralytics.models import RTDETR, SAM, YOLO
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@ -499,58 +499,6 @@ def compress_one_image(f, f_new=None, max_dim=1920, quality=50):
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cv2.imwrite(str(f_new or f), im)
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def delete_dsstore(path):
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"""
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Deletes all ".DS_store" files under a specified directory.
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Args:
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path (str, optional): The directory path where the ".DS_store" files should be deleted.
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Example:
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```python
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from ultralytics.data.utils import delete_dsstore
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delete_dsstore('path/to/dir')
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```
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Note:
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".DS_store" files are created by the Apple operating system and contain metadata about folders and files. They
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are hidden system files and can cause issues when transferring files between different operating systems.
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"""
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# Delete Apple .DS_store files
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files = list(Path(path).rglob('.DS_store'))
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LOGGER.info(f'Deleting *.DS_store files: {files}')
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for f in files:
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f.unlink()
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def zip_directory(dir, use_zipfile_library=True):
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"""
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Zips a directory and saves the archive to the specified output path. Equivalent to 'zip -r coco8.zip coco8/'
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Args:
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dir (str): The path to the directory to be zipped.
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use_zipfile_library (bool): Whether to use zipfile library or shutil for zipping.
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Example:
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```python
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from ultralytics.data.utils import zip_directory
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zip_directory('/path/to/dir')
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```
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"""
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delete_dsstore(dir)
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if use_zipfile_library:
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dir = Path(dir)
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with zipfile.ZipFile(dir.with_suffix('.zip'), 'w', zipfile.ZIP_DEFLATED) as zip_file:
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for file_path in dir.glob('**/*'):
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if file_path.is_file():
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zip_file.write(file_path, file_path.relative_to(dir))
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else:
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import shutil
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shutil.make_archive(dir, 'zip', dir)
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def autosplit(path=DATASETS_DIR / 'coco8/images', weights=(0.9, 0.1, 0.0), annotated_only=False):
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"""
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Automatically split a dataset into train/val/test splits and save the resulting splits into autosplit_*.txt files.
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@ -164,7 +164,6 @@ def check_latest_pypi_version(package_name='ultralytics'):
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response = requests.get(f'https://pypi.org/pypi/{package_name}/json', timeout=3)
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if response.status_code == 200:
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return response.json()['info']['version']
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return None
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def check_pip_update_available():
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@ -39,6 +39,31 @@ def is_url(url, check=True):
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return False
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def delete_dsstore(path):
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"""
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Deletes all ".DS_store" files under a specified directory.
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Args:
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path (str, optional): The directory path where the ".DS_store" files should be deleted.
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Example:
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```python
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from ultralytics.data.utils import delete_dsstore
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delete_dsstore('path/to/dir')
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```
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Note:
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".DS_store" files are created by the Apple operating system and contain metadata about folders and files. They
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are hidden system files and can cause issues when transferring files between different operating systems.
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"""
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# Delete Apple .DS_store files
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files = list(Path(path).rglob('.DS_store'))
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LOGGER.info(f'Deleting *.DS_store files: {files}')
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for f in files:
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f.unlink()
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def zip_directory(directory, compress=True, exclude=('.DS_Store', '__MACOSX'), progress=True):
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"""
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Zips the contents of a directory, excluding files containing strings in the exclude list.
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@ -62,6 +87,7 @@ def zip_directory(directory, compress=True, exclude=('.DS_Store', '__MACOSX'), p
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"""
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from zipfile import ZIP_DEFLATED, ZIP_STORED, ZipFile
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delete_dsstore(directory)
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directory = Path(directory)
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if not directory.is_dir():
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raise FileNotFoundError(f"Directory '{directory}' does not exist.")
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@ -117,20 +143,22 @@ def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX'), exist_ok=Fals
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files = [f for f in zipObj.namelist() if all(x not in f for x in exclude)]
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top_level_dirs = {Path(f).parts[0] for f in files}
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if len(top_level_dirs) > 1 or not files[0].endswith('/'):
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path = Path(path) / Path(file).stem # define new unzip directory
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if len(top_level_dirs) > 1 or not files[0].endswith('/'): # zip has multiple files at top level
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path = extract_path = Path(path) / Path(file).stem # i.e. ../datasets/coco8
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else: # zip has 1 top-level directory
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extract_path = path # i.e. ../datasets
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path = Path(path) / list(top_level_dirs)[0] # i.e. ../datasets/coco8
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# Check if destination directory already exists and contains files
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extract_path = Path(path) / list(top_level_dirs)[0]
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if extract_path.exists() and any(extract_path.iterdir()) and not exist_ok:
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if path.exists() and any(path.iterdir()) and not exist_ok:
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# If it exists and is not empty, return the path without unzipping
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LOGGER.info(f'Skipping {file} unzip (already unzipped)')
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return extract_path
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return path
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for f in tqdm(files, desc=f'Unzipping {file} to {Path(path).resolve()}...', unit='file', disable=not progress):
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zipObj.extract(f, path=path)
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zipObj.extract(f, path=extract_path)
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return extract_path # return unzip dir
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return path # return unzip dir
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def check_disk_space(url='https://ultralytics.com/assets/coco128.zip', sf=1.5, hard=True):
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