Yolov5: What's the Focus layer?

[maykulkarni]

I see a focus layer after the input

class Focus(nn.Module):
    # Focus wh information into c-space
    def __init__(self, c1, c2, k=1):
        super(Focus, self).__init__()
        self.conv = Conv(c1 * 4, c2, k, 1)

    def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
        return self.conv(torch.cat([x[..., ::2, ::2],
                                    x[..., 1::2, ::2],
                                    x[..., ::2, 1::2],
                                    x[..., 1::2, 1::2]], 1))

Which transforms:

[[[[ 0,  1,  2,  3],
   [ 4,  5,  6,  7],
   [ 8,  9, 10, 11],
   [12, 13, 14, 15]]]]

to 

[[[[ 0,  2],
   [ 8, 10]],

  [[ 4,  6],
  [12, 14]],

  [[ 1,  3],
   [9, 11]],

  [[5,  7],
  [13, 15]]]]

Which sort of seems like a downsample, but why not use DownSample directly? What does this accomplish and is there any literature I can read about this technique?

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[bonlime]

check TResNet paper. p2. They call it SpaceToDepth

[seekFire]

@maykulkarni I think It is the inverse operation of pixelshuffle