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ultralytics 8.0.103 minor fixes (#2634)

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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>
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Glenn Jocher 2023-05-16 01:39:52 +02:00 committed by GitHub
parent e2e3e367a2
commit 7884098857
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6 changed files with 7 additions and 13 deletions
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5
docker/Dockerfile-jetson
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@ -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 tqdm matplotlib pyyaml psutil thop pandas onnx "numpy==1.23"
RUN pip install --no-cache -e . 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 # Set environment variables
ENV OMP_NUM_THREADS=1 ENV OMP_NUM_THREADS=1

2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = '8.0.101' __version__ = '8.0.103'
from ultralytics.hub import start from ultralytics.hub import start
from ultralytics.vit.rtdetr import RTDETR from ultralytics.vit.rtdetr import RTDETR

2
ultralytics/nn/modules/head.py
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@ -346,7 +346,7 @@ class RTDETRDecoder(nn.Module):
bs, _, _ = memory.shape bs, _, _ = memory.shape
# prepare input for decoder # prepare input for decoder
anchors, valid_mask = self._generate_anchors(spatial_shapes, dtype=memory.dtype, device=memory.device) 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) output_memory = self.enc_output(memory)
enc_outputs_class = self.enc_score_head(output_memory) # (bs, h*w, nc) enc_outputs_class = self.enc_score_head(output_memory) # (bs, h*w, nc)

2
ultralytics/yolo/data/augment.py
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@ -128,7 +128,7 @@ class Mosaic(BaseMixTransform):
n (int, optional): The grid size, either 4 (for 2x2) or 9 (for 3x3). 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.""" """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 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.' assert n in (4, 9), 'grid must be equal to 4 or 9.'

3
ultralytics/yolo/data/dataset_wrappers.py
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@ -44,8 +44,7 @@ class MixAndRectDataset:
indexes = transform.get_indexes(self.dataset) indexes = transform.get_indexes(self.dataset)
if not isinstance(indexes, collections.abc.Sequence): if not isinstance(indexes, collections.abc.Sequence):
indexes = [indexes] 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): if self.dataset.rect and isinstance(transform, LetterBox):
transform.new_shape = self.dataset.batch_shapes[self.dataset.batch[index]] transform.new_shape = self.dataset.batch_shapes[self.dataset.batch[index]]
labels = transform(labels) labels = transform(labels)

6
ultralytics/yolo/utils/__init__.py
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@ -242,13 +242,13 @@ if WINDOWS: # emoji-safe logging
LOGGER.addFilter(EmojiFilter()) LOGGER.addFilter(EmojiFilter())
def yaml_save(file='data.yaml', data=None): def yaml_save(file='data.yaml', data={}):
""" """
Save YAML data to a file. Save YAML data to a file.
Args: Args:
file (str, optional): File name. Default is 'data.yaml'. 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: Returns:
None: Data is saved to the specified file. 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 # Convert Path objects to strings
for k, v in data.items(): for k, v in data.items():
if isinstance(v, Path): if isinstance(v, Path):
dict[k] = str(v) data[k] = str(v)
# Dump data to file in YAML format # Dump data to file in YAML format
with open(file, 'w') as f: with open(file, 'w') as f: