standalone val (#56)

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

ultralytics/yolo/v8/classify/val.py

@@ -1,5 +1,8 @@
+import hydra
 import torch
 
+from ultralytics.yolo.data import build_classification_dataloader
+from ultralytics.yolo.engine.trainer import DEFAULT_CONFIG
 from ultralytics.yolo.engine.validator import BaseValidator
 
 
@@ -24,6 +27,21 @@ class ClassificationValidator(BaseValidator):
         top1, top5 = acc.mean(0).tolist()
         return {"top1": top1, "top5": top5, "fitness": top5}
 
+    def get_dataloader(self, dataset_path, batch_size):
+        return build_classification_dataloader(path=dataset_path, imgsz=self.args.img_size, batch_size=batch_size)
+
     @property
     def metric_keys(self):
         return ["top1", "top5"]
+
+
+@hydra.main(version_base=None, config_path=DEFAULT_CONFIG.parent, config_name=DEFAULT_CONFIG.name)
+def val(cfg):
+    cfg.data = cfg.data or "imagenette160"
+    cfg.model = cfg.model or "resnet18"
+    validator = ClassificationValidator(args=cfg)
+    validator(model=cfg.model)
+
+
+if __name__ == "__main__":
+    val()