train RTCNet-M

yolo/config/gelan_config.py

@@ -141,7 +141,7 @@ class GElanCConfig(GElanBaseConfig):
         super().__init__()
         self.backbone = 'gelan'
         self.use_pretrained = True
-        self.scale = "l"
+        self.scale = "c"
      
         # ---------------- Data process config ----------------
         self.mosaic_prob = 1.0

yolo/train.py

@@ -196,7 +196,7 @@ def train():
         trainer.eval(model_eval)
         return
 
-    # garbage = torch.randn(640, 1024, 73, 73).to(device) # 15 G
+    garbage = torch.randn(640, 1024, 73, 73).to(device) # 15 G
 
     # ---------------------------- Train pipeline ----------------------------
     trainer.train(model)