`ultralytics 8.0.39` add ByteTracker and BoT-SORT trackers and fixes (#984)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
pull/993/head v8.0.39
Glenn Jocher 2 years ago committed by GitHub
parent ed6c54da7a
commit e799592718
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  1. 2
      README.md
  2. 8
      README.zh-CN.md
  3. 2
      ultralytics/__init__.py
  4. 6
      ultralytics/yolo/data/dataset.py
  5. 1
      ultralytics/yolo/engine/model.py
  6. 2
      ultralytics/yolo/engine/trainer.py

@ -203,7 +203,7 @@ See [Classification Docs](https://docs.ultralytics.com/tasks/classification/) fo
<a href="https://cutt.ly/yolov5-readme-clearml">
<img src="https://github.com/ultralytics/assets/raw/main/partners/logo-clearml.png" width="10%" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="15%" height="0" alt="" />
<a href="https://bit.ly/yolov5-readme-comet">
<a href="https://bit.ly/yolov5-readme-comet2">
<img src="https://github.com/ultralytics/assets/raw/main/partners/logo-comet.png" width="10%" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="15%" height="0" alt="" />
<a href="https://bit.ly/yolov5-neuralmagic">

@ -179,16 +179,16 @@ success = model.export(format="onnx") # 将模型导出为 ONNX 格式
<a href="https://cutt.ly/yolov5-readme-clearml">
<img src="https://github.com/ultralytics/assets/raw/main/partners/logo-clearml.png" width="10%" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="15%" height="0" alt="" />
<a href="https://bit.ly/yolov5-readme-comet">
<a href="https://bit.ly/yolov5-readme-comet2">
<img src="https://github.com/ultralytics/assets/raw/main/partners/logo-comet.png" width="10%" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="15%" height="0" alt="" />
<a href="https://bit.ly/yolov5-neuralmagic">
<img src="https://github.com/ultralytics/assets/raw/main/partners/logo-neuralmagic.png" width="10%" /></a>
</div>
| Roboflow | ClearML ⭐ 新 | Comet ⭐ 新 | Neural Magic ⭐ 新 |
| :--------------------------------------------------------------------------------: | :-------------------------------------------------------------------------: | :-------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------: |
| 将您的自定义数据集进行标注并直接导出到 YOLOv8 以进行训练 [Roboflow](https://roboflow.com/?ref=ultralytics) | 自动跟踪、可视化甚至远程训练 YOLOv8 [ClearML](https://cutt.ly/yolov5-readme-clearml)(开源!) | 永远免费,[Comet](https://bit.ly/yolov5-readme-comet)可让您保存 YOLOv8 模型、恢复训练以及交互式可视化和调试预测 | 使用 [Neural Magic DeepSparse](https://bit.ly/yolov5-neuralmagic),运行 YOLOv8 推理的速度最高可提高6倍 |
| Roboflow | ClearML ⭐ 新 | Comet ⭐ 新 | Neural Magic ⭐ 新 |
| :--------------------------------------------------------------------------------: | :-------------------------------------------------------------------------: | :--------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------: |
| 将您的自定义数据集进行标注并直接导出到 YOLOv8 以进行训练 [Roboflow](https://roboflow.com/?ref=ultralytics) | 自动跟踪、可视化甚至远程训练 YOLOv8 [ClearML](https://cutt.ly/yolov5-readme-clearml)(开源!) | 永远免费,[Comet](https://bit.ly/yolov5-readme-comet2)可让您保存 YOLOv8 模型、恢复训练以及交互式可视化和调试预测 | 使用 [Neural Magic DeepSparse](https://bit.ly/yolov5-neuralmagic),运行 YOLOv8 推理的速度最高可提高6倍 |
## <div align="center">Ultralytics HUB</div>

@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
__version__ = "8.0.38"
__version__ = "8.0.39"
from ultralytics.yolo.engine.model import YOLO
from ultralytics.yolo.utils.checks import check_yolo as checks

@ -45,8 +45,6 @@ class YOLODataset(BaseDataset):
def cache_labels(self, path=Path("./labels.cache")):
# Cache dataset labels, check images and read shapes
if path.exists():
path.unlink() # remove *.cache file if exists
x = {"labels": []}
nm, nf, ne, nc, msgs = 0, 0, 0, 0, [] # number missing, found, empty, corrupt, messages
desc = f"{self.prefix}Scanning {path.parent / path.stem}..."
@ -86,11 +84,13 @@ class YOLODataset(BaseDataset):
x["msgs"] = msgs # warnings
x["version"] = self.cache_version # cache version
if is_dir_writeable(path.parent):
if path.exists():
path.unlink() # remove *.cache file if exists
np.save(str(path), x) # save cache for next time
path.with_suffix(".cache.npy").rename(path) # remove .npy suffix
LOGGER.info(f"{self.prefix}New cache created: {path}")
else:
LOGGER.warning(f"{self.prefix}WARNING ⚠ Cache directory {path.parent} is not writeable") # not writeable
LOGGER.warning(f"{self.prefix}WARNING ⚠ Cache directory {path.parent} is not writeable, cache not saved.")
return x
def get_labels(self):

@ -101,6 +101,7 @@ class YOLO:
self.model, self.ckpt = weights, None
self.task = guess_model_task(weights)
self.ckpt_path = weights
self.overrides['model'] = weights
self.ModelClass, self.TrainerClass, self.ValidatorClass, self.PredictorClass = self._assign_ops_from_task()
def _check_is_pytorch_model(self):

@ -184,7 +184,7 @@ class BaseTrainer:
finally:
ddp_cleanup(self, file)
else:
self._do_train(int(os.getenv("RANK", -1)), world_size)
self._do_train(RANK, world_size)
def _setup_ddp(self, rank, world_size):
# os.environ['MASTER_ADDR'] = 'localhost'

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