keep training YOLOX-N

demo.py

@@ -275,8 +275,7 @@ def run():
     model.to(device).eval()
 
     # transform
-    val_transform, trans_cfg = build_transform(
-        args=args, trans_config=trans_cfg, max_stride=model_cfg['max_stride'], is_train=False)
+    val_transform, trans_cfg = build_transform(args, trans_cfg, model_cfg['max_stride'], is_train=False)
 
     print("================= DETECT =================")
     # run

eval.py

@@ -139,8 +139,7 @@ if __name__ == '__main__':
     del model_copy
 
     # transform
-    val_transform, trans_cfg = build_transform(
-        args=args, trans_config=trans_cfg, max_stride=model_cfg['max_stride'], is_train=False)
+    val_transform, trans_cfg = build_transform(args, trans_cfg, model_cfg['max_stride'], is_train=False)
 
     # evaluation
     with torch.no_grad():

test.py

@@ -180,8 +180,7 @@ if __name__ == '__main__':
     trans_cfg = build_trans_config(model_cfg['trans_type'])
 
     # Transform
-    val_transform, trans_cfg = build_transform(
-        args=args, trans_config=trans_cfg, max_stride=model_cfg['max_stride'], is_train=False)
+    val_transform, trans_cfg = build_transform(args, trans_cfg, model_cfg['max_stride'], is_train=False)
 
     # Dataset
     dataset, dataset_info = build_dataset(args, data_cfg, trans_cfg, val_transform, is_train=False)

train.sh

@@ -12,7 +12,7 @@ python train.py \
         --ema \
         --fp16 \
         --multi_scale \
-        # --resume weights/coco/yolov3_t/yolov3_t_epoch_171_23.04.pth \
+        --resume weights/coco/yolox_n/yolox_n_best.pth \
         # --pretrained weights/coco/yolo_free_medium/yolo_free_medium_39.46.pth \
         # --eval_first