ultralytics 8.0.30 Docker, rect, data=*.zip updates (#832)

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

ultralytics/yolo/engine/model.py

@@ -156,6 +156,7 @@ class YOLO:
             **kwargs : Any other args accepted by the validators. To see all args check 'configuration' section in docs
         """
         overrides = self.overrides.copy()
+        overrides["rect"] = True  # rect batches as default
         overrides.update(kwargs)
         overrides["mode"] = "val"
         args = get_cfg(cfg=DEFAULT_CFG, overrides=overrides)

ultralytics/yolo/engine/trainer.py

@@ -116,13 +116,16 @@ class BaseTrainer:
 
         # Model and Dataloaders.
         self.model = self.args.model
-        self.data = self.args.data
-        if self.data.endswith(".yaml"):
-            self.data = check_det_dataset(self.data)
-        elif self.args.task == 'classify':
-            self.data = check_cls_dataset(self.data)
-        else:
-            raise FileNotFoundError(emojis(f"Dataset '{self.args.data}' not found ❌"))
+        try:
+            if self.args.task == 'classify':
+                self.data = check_cls_dataset(self.args.data)
+            elif self.args.data.endswith(".yaml") or self.args.task in ('detect', 'segment'):
+                self.data = check_det_dataset(self.args.data)
+                if 'yaml_file' in self.data:
+                    self.args.data = self.data['yaml_file']  # for validating 'yolo train data=url.zip' usage
+        except Exception as e:
+            raise FileNotFoundError(emojis(f"Dataset '{self.args.data}' error ❌ {e}")) from e
+
         self.trainset, self.testset = self.get_dataset(self.data)
         self.ema = None
 

ultralytics/yolo/engine/validator.py

@@ -117,6 +117,8 @@ class BaseValidator:
 
             if self.device.type == 'cpu':
                 self.args.workers = 0  # faster CPU val as time dominated by inference, not dataloading
+            if not pt:
+                self.args.rect = False
             self.dataloader = self.dataloader or \
                               self.get_dataloader(self.data.get("val") or self.data.set("test"), self.args.batch)