Header perameter postion changed in evaluate function to avoide args passing issue when only evaluating any pretrained model.

Author: shubsraj

rfdetr/engine.py

@@ -182,7 +182,7 @@ def train_one_epoch(
     return {k: meter.global_avg for k, meter in metric_logger.meters.items()}
 
 
-def evaluate(model, criterion, postprocessors, data_loader, base_ds, device, header='Test', args=None):
+def evaluate(model, criterion, postprocessors, data_loader, base_ds, device, args=None, header='Eval'):
     model.eval()
     if args.fp16_eval:
         model.half()

rfdetr/main.py

@@ -362,7 +362,7 @@ def lr_lambda(current_step: int):
 
             with torch.inference_mode():
                 test_stats, coco_evaluator = evaluate(
-                    model, criterion, postprocessors, data_loader_val, base_ds, device, "Eval", args=args
+                    model, criterion, postprocessors, data_loader_val, base_ds, device, args=args, header="Test"
                 )
 
             map_regular = test_stats['coco_eval_bbox'][0]
@@ -385,7 +385,7 @@ def lr_lambda(current_step: int):
                         'n_parameters': n_parameters}
             if args.use_ema:
                 ema_test_stats, _ = evaluate(
-                    self.ema_m.module, criterion, postprocessors, data_loader_val, base_ds, device, "Eval-ema", args=args
+                    self.ema_m.module, criterion, postprocessors, data_loader_val, base_ds, device, args=args, header="Test-ema"
                 )
                 log_stats.update({f'ema_test_{k}': v for k,v in ema_test_stats.items()})
                 map_ema = ema_test_stats['coco_eval_bbox'][0]