updates

models/yolo.py

@@ -122,7 +122,7 @@ def parse_model(md, ch):  # model_dict, input_channels(3)
                 pass
 
         n = max(round(n * gd), 1) if n > 1 else n  # depth gain
-        if m in [nn.Conv2d, Conv, Bottleneck, SPP, DWConv, MixConv2d, Focus, ConvPlus, BottleneckCSP, BottleneckCSPF, BottleneckLight]:
+        if m in [nn.Conv2d, Conv, Bottleneck, SPP, DWConv, MixConv2d, Focus, ConvPlus, BottleneckCSP, BottleneckLight]:
             c1, c2 = ch[f], args[0]
 
             # Normal
@@ -143,8 +143,8 @@ def parse_model(md, ch):  # model_dict, input_channels(3)
             #     c2 = make_divisible(c2, 8) if c2 != no else c2
 
             args = [c1, c2, *args[1:]]
-            if m in [BottleneckCSP, BottleneckCSPF]:
-                args += [n]
+            if m is BottleneckCSP:
+                args.insert(2, n)
                 n = 1
         elif m is nn.BatchNorm2d:
             args = [ch[f]]
@@ -170,7 +170,7 @@ def parse_model(md, ch):  # model_dict, input_channels(3)
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument('--cfg', type=str, default='yolov5s.yaml', help='model.yaml')
+    parser.add_argument('--cfg', type=str, default='yolov5s_csp.yaml', help='model.yaml')
     parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
     opt = parser.parse_args()
     opt.cfg = glob.glob('./**/' + opt.cfg, recursive=True)[0]  # find file