`ultralytics 8.0.145` Windows URL fix and Pose MPS warning (#4034)

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

docker/Dockerfile-jetson

@@ -43,5 +43,5 @@ ENV OMP_NUM_THREADS=1
 # Run
 # t=ultralytics/ultralytics:latest-jetson && sudo docker run -it --ipc=host $t
 
-# Pull and Run with local volume mounted
-# t=ultralytics/ultralytics:jetson && sudo docker pull $t && sudo docker run -it --runtime=nvidia $t
+# Pull and Run with NVIDIA runtime
+# t=ultralytics/ultralytics:latest-jetson && sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.144'
+__version__ = '8.0.145'
 
 from ultralytics.hub import start
 from ultralytics.models import RTDETR, SAM, YOLO

ultralytics/data/utils.py

@@ -244,7 +244,7 @@ def check_det_dataset(dataset, autodownload=True):
         val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])]  # val path
         if not all(x.exists() for x in val):
             name = clean_url(dataset)  # dataset name with URL auth stripped
-            m = f"\nDataset '{name}' images not found ⚠️, missing paths %s" % [str(x) for x in val if not x.exists()]
+            m = f"\nDataset '{name}' images not found ⚠️, missing path '{[x for x in val if not x.exists()][0]}'"
             if s and autodownload:
                 LOGGER.warning(m)
             else:

ultralytics/models/yolo/classify/train.py

@@ -135,11 +135,12 @@ class ClassificationTrainer(BaseTrainer):
 
     def plot_training_samples(self, batch, ni):
         """Plots training samples with their annotations."""
-        plot_images(images=batch['img'],
-                    batch_idx=torch.arange(len(batch['img'])),
-                    cls=batch['cls'].squeeze(-1),
-                    fname=self.save_dir / f'train_batch{ni}.jpg',
-                    on_plot=self.on_plot)
+        plot_images(
+            images=batch['img'],
+            batch_idx=torch.arange(len(batch['img'])),
+            cls=batch['cls'].view(-1),  # warning: use .view(), not .squeeze() for Classify models
+            fname=self.save_dir / f'train_batch{ni}.jpg',
+            on_plot=self.on_plot)
 
 
 def train(cfg=DEFAULT_CFG, use_python=False):

ultralytics/models/yolo/classify/val.py

@@ -74,12 +74,13 @@ class ClassificationValidator(BaseValidator):
 
     def plot_val_samples(self, batch, ni):
         """Plot validation image samples."""
-        plot_images(images=batch['img'],
-                    batch_idx=torch.arange(len(batch['img'])),
-                    cls=batch['cls'].squeeze(-1),
-                    fname=self.save_dir / f'val_batch{ni}_labels.jpg',
-                    names=self.names,
-                    on_plot=self.on_plot)
+        plot_images(
+            images=batch['img'],
+            batch_idx=torch.arange(len(batch['img'])),
+            cls=batch['cls'].view(-1),  # warning: use .view(), not .squeeze() for Classify models
+            fname=self.save_dir / f'val_batch{ni}_labels.jpg',
+            names=self.names,
+            on_plot=self.on_plot)
 
     def plot_predictions(self, batch, preds, ni):
         """Plots predicted bounding boxes on input images and saves the result."""

ultralytics/models/yolo/pose/predict.py

@@ -2,7 +2,7 @@
 
 from ultralytics.engine.results import Results
 from ultralytics.models.yolo.detect.predict import DetectionPredictor
-from ultralytics.utils import DEFAULT_CFG, ROOT, ops
+from ultralytics.utils import DEFAULT_CFG, LOGGER, ROOT, ops
 
 
 class PosePredictor(DetectionPredictor):
@@ -10,6 +10,9 @@ class PosePredictor(DetectionPredictor):
     def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
         super().__init__(cfg, overrides, _callbacks)
         self.args.task = 'pose'
+        if isinstance(self.args.device, str) and self.args.device.lower() == 'mps':
+            LOGGER.warning("WARNING ⚠️ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
+                           'See https://github.com/ultralytics/ultralytics/issues/4031.')
 
     def postprocess(self, preds, img, orig_imgs):
         """Return detection results for a given input image or list of images."""

ultralytics/models/yolo/pose/train.py

@@ -4,7 +4,7 @@ from copy import copy
 
 from ultralytics.models import yolo
 from ultralytics.nn.tasks import PoseModel
-from ultralytics.utils import DEFAULT_CFG
+from ultralytics.utils import DEFAULT_CFG, LOGGER
 from ultralytics.utils.plotting import plot_images, plot_results
 
 
@@ -18,6 +18,10 @@ class PoseTrainer(yolo.detect.DetectionTrainer):
         overrides['task'] = 'pose'
         super().__init__(cfg, overrides, _callbacks)
 
+        if isinstance(self.args.device, str) and self.args.device.lower() == 'mps':
+            LOGGER.warning("WARNING ⚠️ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
+                           'See https://github.com/ultralytics/ultralytics/issues/4031.')
+
     def get_model(self, cfg=None, weights=None, verbose=True):
         """Get pose estimation model with specified configuration and weights."""
         model = PoseModel(cfg, ch=3, nc=self.data['nc'], data_kpt_shape=self.data['kpt_shape'], verbose=verbose)

ultralytics/models/yolo/pose/val.py

@@ -19,6 +19,9 @@ class PoseValidator(DetectionValidator):
         super().__init__(dataloader, save_dir, pbar, args, _callbacks)
         self.args.task = 'pose'
         self.metrics = PoseMetrics(save_dir=self.save_dir, on_plot=self.on_plot)
+        if isinstance(self.args.device, str) and self.args.device.lower() == 'mps':
+            LOGGER.warning("WARNING ⚠️ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
+                           'See https://github.com/ultralytics/ultralytics/issues/4031.')
 
     def preprocess(self, batch):
         """Preprocesses the batch by converting the 'keypoints' data into a float and moving it to the device."""

ultralytics/utils/__init__.py

@@ -824,7 +824,7 @@ def deprecation_warn(arg, new_arg, version=None):
 
 def clean_url(url):
     """Strip auth from URL, i.e. https://url.com/file.txt?auth -> https://url.com/file.txt."""
-    url = str(Path(url)).replace(':/', '://')  # Pathlib turns :// -> :/
+    url = Path(url).as_posix().replace(':/', '://')  # Pathlib turns :// -> :/, as_posix() for Windows
     return urllib.parse.unquote(url).split('?')[0]  # '%2F' to '/', split https://url.com/file.txt?auth