Cap head scaling with `min(nc, 100)` (#3436)

ultralytics/nn/modules/head.py

@@ -34,7 +34,7 @@ class Detect(nn.Module):
         self.reg_max = 16  # DFL channels (ch[0] // 16 to scale 4/8/12/16/20 for n/s/m/l/x)
         self.no = nc + self.reg_max * 4  # number of outputs per anchor
         self.stride = torch.zeros(self.nl)  # strides computed during build
-        c2, c3 = max((16, ch[0] // 4, self.reg_max * 4)), max(ch[0], self.nc)  # channels
+        c2, c3 = max((16, ch[0] // 4, self.reg_max * 4)), max(ch[0], min(self.nc, 100))  # channels
         self.cv2 = nn.ModuleList(
             nn.Sequential(Conv(x, c2, 3), Conv(c2, c2, 3), nn.Conv2d(c2, 4 * self.reg_max, 1)) for x in ch)
         self.cv3 = nn.ModuleList(nn.Sequential(Conv(x, c3, 3), Conv(c3, c3, 3), nn.Conv2d(c3, self.nc, 1)) for x in ch)