`ultralytics 8.0.140` improved robustness to model path spaces (#3879)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lukas Hennies <45569834+Gornoka@users.noreply.github.com>

.github/workflows/ci.yaml

@@ -112,22 +112,22 @@ jobs:
         shell: python
         run: |
           from ultralytics.utils.benchmarks import benchmark
-          benchmark(model='${{ matrix.model }}.pt', imgsz=160, half=False, hard_fail=0.26)
+          benchmark(model='path with spaces/${{ matrix.model }}.pt', imgsz=160, half=False, hard_fail=0.26)
       - name: Benchmark SegmentationModel
         shell: python
         run: |
           from ultralytics.utils.benchmarks import benchmark
-          benchmark(model='${{ matrix.model }}-seg.pt', imgsz=160, half=False, hard_fail=0.30)
+          benchmark(model='path with spaces/${{ matrix.model }}-seg.pt', imgsz=160, half=False, hard_fail=0.30)
       - name: Benchmark ClassificationModel
         shell: python
         run: |
           from ultralytics.utils.benchmarks import benchmark
-          benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.36)
+          benchmark(model='path with spaces/${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.36)
       - name: Benchmark PoseModel
         shell: python
         run: |
           from ultralytics.utils.benchmarks import benchmark
-          benchmark(model='${{ matrix.model }}-pose.pt', imgsz=160, half=False, hard_fail=0.17)
+          benchmark(model='path with spaces/${{ matrix.model }}-pose.pt', imgsz=160, half=False, hard_fail=0.17)
       - name: Benchmark Summary
         run: |
           cat benchmarks.log
@@ -141,12 +141,10 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         python-version: ['3.11']
-        model: [yolov8n]
         torch: [latest]
         include:
           - os: ubuntu-latest
             python-version: '3.8'  # torch 1.7.0 requires python >=3.6, <=3.8
-            model: yolov8n
             torch: '1.8.0'  # min torch version CI https://pypi.org/project/torchvision/
     steps:
       - uses: actions/checkout@v3

.gitignore

@@ -136,7 +136,6 @@ dmypy.json
 datasets/
 runs/
 wandb/
-
 .DS_Store
 
 # Neural Network weights -----------------------------------------------------------------------------------------------
@@ -154,3 +153,6 @@ weights/
 *_web_model/
 *_openvino_model/
 *_paddle_model/
+
+# Autogenerated files for tests
+/ultralytics/assets/

tests/test_python.py

@@ -12,7 +12,7 @@ from ultralytics import RTDETR, YOLO
 from ultralytics.data.build import load_inference_source
 from ultralytics.utils import LINUX, ONLINE, ROOT, SETTINGS
 
-MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n.pt'
+MODEL = Path(SETTINGS['weights_dir']) / 'path with spaces' / 'yolov8n.pt'  # test spaces in path
 CFG = 'yolov8n.yaml'
 SOURCE = ROOT / 'assets/bus.jpg'
 SOURCE_GREYSCALE = Path(f'{SOURCE.parent / SOURCE.stem}_greyscale.jpg')

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.139'
+__version__ = '8.0.140'
 
 from ultralytics.engine.model import YOLO
 from ultralytics.hub import start

ultralytics/engine/exporter.py

@@ -68,7 +68,7 @@ from ultralytics.utils import (ARM64, DEFAULT_CFG, LINUX, LOGGER, MACOS, ROOT, W
                                colorstr, get_default_args, yaml_save)
 from ultralytics.utils.checks import check_imgsz, check_requirements, check_version
 from ultralytics.utils.downloads import attempt_download_asset, get_github_assets
-from ultralytics.utils.files import file_size
+from ultralytics.utils.files import file_size, spaces_in_path
 from ultralytics.utils.ops import Profile
 from ultralytics.utils.torch_utils import get_latest_opset, select_device, smart_inference_mode
 
@@ -112,7 +112,7 @@ def try_export(inner_func):
         try:
             with Profile() as dt:
                 f, model = inner_func(*args, **kwargs)
-            LOGGER.info(f'{prefix} export success ✅ {dt.t:.1f}s, saved as {f} ({file_size(f):.1f} MB)')
+            LOGGER.info(f"{prefix} export success ✅ {dt.t:.1f}s, saved as '{f}' ({file_size(f):.1f} MB)")
             return f, model
         except Exception as e:
             LOGGER.info(f'{prefix} export failure ❌ {dt.t:.1f}s: {e}')
@@ -230,7 +230,7 @@ class Exporter:
         if model.task == 'pose':
             self.metadata['kpt_shape'] = model.model[-1].kpt_shape
 
-        LOGGER.info(f"\n{colorstr('PyTorch:')} starting from {file} with input shape {tuple(im.shape)} BCHW and "
+        LOGGER.info(f"\n{colorstr('PyTorch:')} starting from '{file}' with input shape {tuple(im.shape)} BCHW and "
                     f'output shape(s) {self.output_shape} ({file_size(file):.1f} MB)')
 
         # Exports
@@ -340,7 +340,7 @@ class Exporter:
                 import onnxsim
 
                 LOGGER.info(f'{prefix} simplifying with onnxsim {onnxsim.__version__}...')
-                # subprocess.run(f'onnxsim {f} {f}', shell=True)
+                # subprocess.run(f'onnxsim "{f}" "{f}"', shell=True)
                 model_onnx, check = onnxsim.simplify(model_onnx)
                 assert check, 'Simplified ONNX model could not be validated'
             except Exception as e:
@@ -410,7 +410,7 @@ class Exporter:
 
         LOGGER.info(f'\n{prefix} starting export with ncnn {ncnn.__version__}...')
         f = Path(str(self.file).replace(self.file.suffix, f'_ncnn_model{os.sep}'))
-        f_ts = str(self.file.with_suffix('.torchscript'))
+        f_ts = self.file.with_suffix('.torchscript')
 
         pnnx_filename = 'pnnx.exe' if WINDOWS else 'pnnx'
         if Path(pnnx_filename).is_file():
@@ -434,7 +434,7 @@ class Exporter:
 
         cmd = [
             str(pnnx),
-            f_ts,
+            str(f_ts),
             f'pnnxparam={f / "model.pnnx.param"}',
             f'pnnxbin={f / "model.pnnx.bin"}',
             f'pnnxpy={f / "model_pnnx.py"}',
@@ -586,8 +586,8 @@ class Exporter:
 
         # Export to TF
         int8 = '-oiqt -qt per-tensor' if self.args.int8 else ''
-        cmd = f'onnx2tf -i {f_onnx} -o {f} -nuo --non_verbose {int8}'
+        cmd = f'onnx2tf -i "{f_onnx}" -o "{f}" -nuo --non_verbose {int8}'
-        LOGGER.info(f"\n{prefix} running '{cmd.strip()}'")
+        LOGGER.info(f"\n{prefix} running '{cmd}'")
         subprocess.run(cmd, shell=True)
         yaml_save(f / 'metadata.yaml', self.metadata)  # add metadata.yaml
 
@@ -659,9 +659,9 @@ class Exporter:
         LOGGER.info(f'\n{prefix} starting export with Edge TPU compiler {ver}...')
         f = str(tflite_model).replace('.tflite', '_edgetpu.tflite')  # Edge TPU model
 
-        cmd = f'edgetpu_compiler -s -d -k 10 --out_dir {Path(f).parent} {tflite_model}'
+        cmd = f'edgetpu_compiler -s -d -k 10 --out_dir "{Path(f).parent}" "{tflite_model}"'
         LOGGER.info(f"{prefix} running '{cmd}'")
-        subprocess.run(cmd.split(), check=True)
+        subprocess.run(cmd, shell=True)
         self._add_tflite_metadata(f)
         return f, None
 
@@ -674,7 +674,7 @@ class Exporter:
 
         LOGGER.info(f'\n{prefix} starting export with tensorflowjs {tfjs.__version__}...')
         f = str(self.file).replace(self.file.suffix, '_web_model')  # js dir
-        f_pb = self.file.with_suffix('.pb')  # *.pb path
+        f_pb = str(self.file.with_suffix('.pb'))  # *.pb path
 
         gd = tf.Graph().as_graph_def()  # TF GraphDef
         with open(f_pb, 'rb') as file:
@@ -682,8 +682,13 @@ class Exporter:
         outputs = ','.join(gd_outputs(gd))
         LOGGER.info(f'\n{prefix} output node names: {outputs}')
 
-        cmd = f'tensorflowjs_converter --input_format=tf_frozen_model --output_node_names={outputs} {f_pb} {f}'
+        with spaces_in_path(f_pb) as fpb_, spaces_in_path(f) as f_:  # exporter can not handle spaces in path
-        subprocess.run(cmd.split(), check=True)
+            cmd = f'tensorflowjs_converter --input_format=tf_frozen_model --output_node_names={outputs} "{fpb_}" "{f_}"'
+            LOGGER.info(f"{prefix} running '{cmd}'")
+            subprocess.run(cmd, shell=True)
+
+        if ' ' in str(f):
+            LOGGER.warning(f"{prefix} WARNING ⚠️ your model may not work correctly with spaces in path '{f}'.")
 
         # f_json = Path(f) / 'model.json'  # *.json path
         # with open(f_json, 'w') as j:  # sort JSON Identity_* in ascending order

ultralytics/utils/callbacks/tensorboard.py

@@ -6,7 +6,9 @@ try:
     from torch.utils.tensorboard import SummaryWriter
 
     assert not TESTS_RUNNING  # do not log pytest
-except (ImportError, AssertionError):
+
+# TypeError for handling 'Descriptors cannot not be created directly.' protobuf errors in Windows
+except (ImportError, AssertionError, TypeError):
     SummaryWriter = None
 
 writer = None  # TensorBoard SummaryWriter instance

ultralytics/utils/downloads.py

@@ -149,7 +149,7 @@ def safe_download(url,
     elif not f.is_file():  # URL and file do not exist
         assert dir or file, 'dir or file required for download'
         f = dir / url2file(url) if dir else Path(file)
-        desc = f'Downloading {clean_url(url)} to {f}'
+        desc = f"Downloading {clean_url(url)} to '{f}'"
         LOGGER.info(f'{desc}...')
         f.parent.mkdir(parents=True, exist_ok=True)  # make directory if missing
         check_disk_space(url)

ultralytics/utils/files.py

@@ -4,6 +4,8 @@ import contextlib
 import glob
 import os
 import shutil
+import tempfile
+from contextlib import contextmanager
 from datetime import datetime
 from pathlib import Path
 
@@ -25,6 +27,57 @@ class WorkingDirectory(contextlib.ContextDecorator):
         os.chdir(self.cwd)
 
 
+@contextmanager
+def spaces_in_path(path):
+    """
+    Context manager to handle paths with spaces in their names.
+    If a path contains spaces, it replaces them with underscores, copies the file/directory to the new path,
+    executes the context code block, then copies the file/directory back to its original location.
+
+    Args:
+        path (str | Path): The original path.
+
+    Yields:
+        Path: Temporary path with spaces replaced by underscores if spaces were present, otherwise the original path.
+
+    Examples:
+        with spaces_in_path('/path/with spaces') as new_path:
+            # your code here
+    """
+
+    # If path has spaces, replace them with underscores
+    if ' ' in str(path):
+        string = isinstance(path, str)  # input type
+        path = Path(path)
+
+        # Create a temporary directory and construct the new path
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            tmp_path = Path(tmp_dir) / path.name.replace(' ', '_')
+
+            # Copy file/directory
+            if path.is_dir():
+                # tmp_path.mkdir(parents=True, exist_ok=True)
+                shutil.copytree(path, tmp_path)
+            elif path.is_file():
+                tmp_path.parent.mkdir(parents=True, exist_ok=True)
+                shutil.copy2(path, tmp_path)
+
+            try:
+                # Yield the temporary path
+                yield str(tmp_path) if string else tmp_path
+
+            finally:
+                # Copy file/directory back
+                if tmp_path.is_dir():
+                    shutil.copytree(tmp_path, path, dirs_exist_ok=True)
+                elif tmp_path.is_file():
+                    shutil.copy2(tmp_path, path)  # Copy back the file
+
+    else:
+        # If there are no spaces, just yield the original path
+        yield path
+
+
 def increment_path(path, exist_ok=False, sep='', mkdir=False):
     """
     Increments a file or directory path, i.e. runs/exp --> runs/exp{sep}2, runs/exp{sep}3, ... etc.