ultralytics 8.0.65 YOLOv8 Pose models (#1347)
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@ -54,3 +54,17 @@ class BboxLoss(nn.Module):
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wr = 1 - wl # weight right
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return (F.cross_entropy(pred_dist, tl.view(-1), reduction='none').view(tl.shape) * wl +
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F.cross_entropy(pred_dist, tr.view(-1), reduction='none').view(tl.shape) * wr).mean(-1, keepdim=True)
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class KeypointLoss(nn.Module):
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def __init__(self, sigmas) -> None:
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super().__init__()
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self.sigmas = sigmas
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def forward(self, pred_kpts, gt_kpts, kpt_mask, area):
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d = (pred_kpts[..., 0] - gt_kpts[..., 0]) ** 2 + (pred_kpts[..., 1] - gt_kpts[..., 1]) ** 2
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kpt_loss_factor = (torch.sum(kpt_mask != 0) + torch.sum(kpt_mask == 0)) / (torch.sum(kpt_mask != 0) + 1e-9)
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# e = d / (2 * (area * self.sigmas) ** 2 + 1e-9) # from formula
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e = d / (2 * self.sigmas) ** 2 / (area + 1e-9) / 2 # from cocoeval
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return kpt_loss_factor * ((1 - torch.exp(-e)) * kpt_mask).mean()
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