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44 lines
1.5 KiB
44 lines
1.5 KiB
import torch
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import torch.nn as nn
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import torch.nn.functional as F
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class DistanceMap(nn.Module):
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"""Generate a distance map from a origin center location.
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args:
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num_bins: Number of bins in the map.
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bin_displacement: Displacement of the bins.
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"""
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def __init__(self, num_bins, bin_displacement=1.0):
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super().__init__()
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self.num_bins = num_bins
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self.bin_displacement = bin_displacement
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torch.cuda.empty_cache()
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def forward(self, center, output_sz):
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"""Create the distance map.
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args:
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center: Torch tensor with (y,x) center position. Dims (batch, 2)
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output_sz: Size of output distance map. 2-dimensional tuple."""
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torch.cuda.empty_cache()
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center = center.view(-1,2)
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bin_centers = torch.arange(self.num_bins, dtype=torch.float32, device=center.device).view(1, -1, 1, 1)
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k0 = torch.arange(output_sz[0], dtype=torch.float32, device=center.device).view(1,1,-1,1)
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k1 = torch.arange(output_sz[1], dtype=torch.float32, device=center.device).view(1,1,1,-1)
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d0 = k0 - center[:,0].view(-1,1,1,1)
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d1 = k1 - center[:,1].view(-1,1,1,1)
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dist = torch.sqrt(d0*d0 + d1*d1)
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bin_diff = dist / self.bin_displacement - bin_centers
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bin_val = torch.cat((F.relu(1.0 - torch.abs(bin_diff[:,:-1,:,:]), inplace=True),
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(1.0 + bin_diff[:,-1:,:,:]).clamp(0, 1)), dim=1)
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return bin_val
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