`ultralytics 8.0.103` minor fixes (#2634)

Co-authored-by: kssion <appplus@icloud.com>
Co-authored-by: Eli Spizzichino <diramazioni@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: xbkaishui <xxkaishui@gmail.com>

docker/Dockerfile-jetson

@@ -28,11 +28,6 @@ RUN python3 -m pip install --upgrade pip wheel
 RUN pip install --no-cache tqdm matplotlib pyyaml psutil thop pandas onnx "numpy==1.23"
 RUN pip install --no-cache -e .
 
-# Resolve duplicate OpenCV installation issues in https://github.com/ultralytics/ultralytics/issues/2407
-RUN apt_packages=$(dpkg -l | grep opencv | awk '{print $2}') && [ -n "$apt_packages" ] && apt-get remove -y $apt_packages || true
-RUN pip uninstall -y opencv-python
-RUN pip install "opencv-python<4.7"
-
 # Set environment variables
 ENV OMP_NUM_THREADS=1
 

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.101'
+__version__ = '8.0.103'
 
 from ultralytics.hub import start
 from ultralytics.vit.rtdetr import RTDETR

ultralytics/nn/modules/head.py

@@ -346,7 +346,7 @@ class RTDETRDecoder(nn.Module):
         bs, _, _ = memory.shape
         # prepare input for decoder
         anchors, valid_mask = self._generate_anchors(spatial_shapes, dtype=memory.dtype, device=memory.device)
-        memory = torch.where(valid_mask, memory, torch.tensor(0.))
+        memory = torch.where(valid_mask, memory, 0)
         output_memory = self.enc_output(memory)
 
         enc_outputs_class = self.enc_score_head(output_memory)  # (bs, h*w, nc)

ultralytics/yolo/data/augment.py

@@ -128,7 +128,7 @@ class Mosaic(BaseMixTransform):
         n (int, optional): The grid size, either 4 (for 2x2) or 9 (for 3x3).
     """
 
-    def __init__(self, dataset, imgsz=640, p=1.0, n=9):
+    def __init__(self, dataset, imgsz=640, p=1.0, n=4):
         """Initializes the object with a dataset, image size, probability, and border."""
         assert 0 <= p <= 1.0, f'The probability should be in range [0, 1], but got {p}.'
         assert n in (4, 9), 'grid must be equal to 4 or 9.'

ultralytics/yolo/data/dataset_wrappers.py

@@ -44,8 +44,7 @@ class MixAndRectDataset:
                 indexes = transform.get_indexes(self.dataset)
                 if not isinstance(indexes, collections.abc.Sequence):
                     indexes = [indexes]
-                mix_labels = [deepcopy(self.dataset[index]) for index in indexes]
+                labels['mix_labels'] = [deepcopy(self.dataset[index]) for index in indexes]
-                labels['mix_labels'] = mix_labels
             if self.dataset.rect and isinstance(transform, LetterBox):
                 transform.new_shape = self.dataset.batch_shapes[self.dataset.batch[index]]
             labels = transform(labels)

ultralytics/yolo/utils/__init__.py

@@ -242,13 +242,13 @@ if WINDOWS:  # emoji-safe logging
     LOGGER.addFilter(EmojiFilter())
 
 
-def yaml_save(file='data.yaml', data=None):
+def yaml_save(file='data.yaml', data={}):
     """
     Save YAML data to a file.
 
     Args:
         file (str, optional): File name. Default is 'data.yaml'.
-        data (dict, optional): Data to save in YAML format. Default is None.
+        data (dict): Data to save in YAML format.
 
     Returns:
         None: Data is saved to the specified file.
@@ -261,7 +261,7 @@ def yaml_save(file='data.yaml', data=None):
     # Convert Path objects to strings
     for k, v in data.items():
         if isinstance(v, Path):
-            dict[k] = str(v)
+            data[k] = str(v)
 
     # Dump data to file in YAML format
     with open(file, 'w') as f: