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>

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'