Fix load and resume and update autodownload endpoint (#136)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/yolo/engine/model.py

@@ -82,7 +82,7 @@ class YOLO:
         self.ckpt_path = weights
         self.task = self.model.args["task"]
         self.overrides = self.model.args
-        self.overrides["device"] = ''  # reset device
+        self._reset_ckpt_args(self.overrides)
         self.ModelClass, self.TrainerClass, self.ValidatorClass, self.PredictorClass = \
             self._guess_ops_from_task(self.task)
 
@@ -199,27 +199,6 @@ class YOLO:
 
         self.trainer.train()
 
-    def resume(self, task=None, model=None):
-        """
-        Resume a training task. Requires either `task` or `model`. `model` takes the higher precedence.
-        Args:
-            task (str): The task type you want to resume. Automatically finds the last run to resume if `model` is not specified.
-            model (str): The model checkpoint to resume from. If not found, the last run of the given task type is resumed.
-                         If `model` is specified
-        """
-        if task:
-            if task.lower() not in MODEL_MAP:
-                raise SyntaxError(f"unrecognised task - {task}. Supported tasks are {MODEL_MAP.keys()}")
-        else:
-            ckpt = torch.load(model, map_location="cpu")
-            task = ckpt["train_args"]["task"]
-            del ckpt
-        self.ModelClass, self.TrainerClass, self.ValidatorClass, self.PredictorClass = self._guess_ops_from_task(
-            task=task.lower())
-        self.trainer = self.TrainerClass(overrides={"task": task.lower(), "resume": model or True})
-
-        self.trainer.train()
-
     def to(self, device):
         self.model.to(device)
 
@@ -240,3 +219,10 @@ class YOLO:
 
     def forward(self, imgs):
         return self.__call__(imgs)
+
+    @staticmethod
+    def _reset_ckpt_args(args):
+        args.pop("device", None)
+        args.pop("project", None)
+        args.pop("name", None)
+        args.pop("batch_size", None)

ultralytics/yolo/engine/trainer.py

@@ -367,7 +367,7 @@ class BaseTrainer:
         if not pretrained:
             model = check_file(model)
         ckpt = self.load_ckpt(model) if pretrained else None
-        self.model = self.load_model(model_cfg=None if pretrained else model, weights=ckpt)  # model
+        self.model = self.load_model(model_cfg=None if pretrained else model, weights=ckpt["model"])  # model
         return ckpt
 
     def load_ckpt(self, ckpt):