`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>

README.md

@@ -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">

README.zh-CN.md

@@ -179,7 +179,7 @@ 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">
@@ -187,8 +187,8 @@ success = model.export(format="onnx")  # 将模型导出为 ONNX 格式
 </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 |
+| :--------------------------------------------------------------------------------: | :-------------------------------------------------------------------------: | :--------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------: |
+| 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>
 

ultralytics/__init__.py

@@ -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

ultralytics/yolo/data/dataset.py

@@ -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):

ultralytics/yolo/engine/model.py

@@ -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):

ultralytics/yolo/engine/trainer.py

@@ -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'