train YOLOv8-N on COCO

config/data_config/transform_config.py

@@ -72,7 +72,7 @@ yolov5_small_trans_config = {
     'hsv_v': 0.4,
     # Mosaic & Mixup
     'mosaic_prob': 1.0,
-    'mixup_prob': 0.05,
+    'mixup_prob': 0.0,
     'mosaic_type': 'yolov5_mosaic',
     'mixup_type': 'yolov5_mixup',
     'mixup_scale': [0.5, 1.5]   # "mixup_scale" is not used for YOLOv5MixUp
@@ -91,7 +91,7 @@ yolov5_nano_trans_config = {
     'hsv_v': 0.4,
     # Mosaic & Mixup
     'mosaic_prob': 1.0,
-    'mixup_prob': 0.05,
+    'mixup_prob': 0.0,
     'mosaic_type': 'yolov5_mosaic',
     'mixup_type': 'yolov5_mixup',
     'mixup_scale': [0.5, 1.5]   # "mixup_scale" is not used for YOLOv5MixUp

models/detectors/yolov8/yolov8_basic.py

@@ -124,7 +124,7 @@ class Yolov8StageBlock(nn.Module):
 
     def forward(self, x):
         # Input proj
-        x1, x2 = torch.split(self.input_proj(x), self.inter_dim, dim=1)
+        x1, x2 = torch.chunk(self.input_proj(x), 2, dim=1)
         out = list([x1, x2])
 
         # Bottlenecl