new check_dataset functions (#43)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/utils/__init__.py

@@ -7,7 +7,7 @@ from pathlib import Path
 
 # Constants
 FILE = Path(__file__).resolve()
-ROOT = FILE.parents[2]  # YOLOv5 root directory
+ROOT = FILE.parents[2]  # YOLO
 RANK = int(os.getenv('RANK', -1))
 DATASETS_DIR = ROOT.parent / 'datasets'  # YOLOv5 datasets directory
 NUM_THREADS = min(8, max(1, os.cpu_count() - 1))  # number of YOLOv5 multiprocessing threads

ultralytics/yolo/utils/checks.py

@@ -116,13 +116,10 @@ def check_file(file, suffix=''):
             torch.hub.download_url_to_file(url, file)
             assert Path(file).exists() and Path(file).stat().st_size > 0, f'File download failed: {url}'  # check
         return file
-    elif file.startswith('clearml://'):  # ClearML Dataset ID
-        assert 'clearml' in sys.modules, "Can not use ClearML dataset. Run 'pip install clearml' to install"
-        return file
     else:  # search
         files = []
-        for d in 'data', 'models', 'utils':  # search directories
-            files.extend(glob.glob(str(ROOT / d / '**' / file), recursive=True))  # find file
+        for d in 'data', 'v8', 'utils':  # search directories
+            files.extend(glob.glob(str(ROOT / "yolo" / d / '**' / file), recursive=True))  # find file
         assert len(files), f'File not found: {file}'  # assert file was found
         assert len(files) == 1, f"Multiple files match '{file}', specify exact path: {files}"  # assert unique
         return files[0]  # return file

ultralytics/yolo/utils/files.py

@@ -1,6 +1,7 @@
 import contextlib
 import os
 from pathlib import Path
+from zipfile import ZipFile
 
 import yaml
 
@@ -44,3 +45,19 @@ def save_yaml(file='data.yaml', data=None):
     # Single-line safe yaml saving
     with open(file, 'w') as f:
         yaml.safe_dump({k: str(v) if isinstance(v, Path) else v for k, v in data.items()}, f, sort_keys=False)
+
+
+def yaml_load(file='data.yaml'):
+    # Single-line safe yaml loading
+    with open(file, errors='ignore') as f:
+        return yaml.safe_load(f)
+
+
+def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX')):
+    # Unzip a *.zip file to path/, excluding files containing strings in exclude list
+    if path is None:
+        path = Path(file).parent  # default path
+    with ZipFile(file) as zipObj:
+        for f in zipObj.namelist():  # list all archived filenames in the zip
+            if all(x not in f for x in exclude):
+                zipObj.extract(f, path=path)

ultralytics/yolo/utils/modeling/__init__.py

@@ -118,9 +118,3 @@ def get_model(model='s.pt', pretrained=True):
         return torchvision.models.__dict__[model](weights='IMAGENET1K_V1' if pretrained else None)
     else:  # Ultralytics assets
         return torch.load(attempt_download(f"{model}.pt"), map_location='cpu')
-
-
-def yaml_load(file='data.yaml'):
-    # Single-line safe yaml loading
-    with open(file, errors='ignore') as f:
-        return yaml.safe_load(f)

ultralytics/yolo/utils/modeling/autobackend.py

@@ -32,7 +32,8 @@ class AutoBackend(nn.Module):
         #   TensorFlow Lite:                *.tflite
         #   TensorFlow Edge TPU:            *_edgetpu.tflite
         #   PaddlePaddle:                   *_paddle_model
-        from ultralytics.yolo.utils.modeling import attempt_load_weights, yaml_load
+        from ultralytics.yolo.utils.files import yaml_load
+        from ultralytics.yolo.utils.modeling import attempt_load_weights
 
         super().__init__()
         w = str(weights[0] if isinstance(weights, list) else weights)
@@ -315,7 +316,7 @@ class AutoBackend(nn.Module):
 
     @staticmethod
     def _load_metadata(f=Path('path/to/meta.yaml')):
-        from ultralytics.yolo.utils.modeling import yaml_load
+        from ultralytics.yolo.utils.files import yaml_load
 
         # Load metadata from meta.yaml if it exists
         if f.exists():