43 lines
1.0 KiB
Python
43 lines
1.0 KiB
Python
# The following code is modified from https://github.com/shelhamer/clockwork-fcn
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import numpy as np
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def get_out_scoremap(net):
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return net.blobs['score'].data[0].argmax(axis=0).astype(np.uint8)
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def feed_net(net, in_):
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"""
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Load prepared input into net.
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"""
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net.blobs['data'].reshape(1, *in_.shape)
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net.blobs['data'].data[...] = in_
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def segrun(net, in_):
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feed_net(net, in_)
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net.forward()
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return get_out_scoremap(net)
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def fast_hist(a, b, n):
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k = np.where((a >= 0) & (a < n))[0]
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bc = np.bincount(n * a[k].astype(int) + b[k], minlength=n**2)
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if len(bc) != n**2:
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# ignore this example if dimension mismatch
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return 0
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return bc.reshape(n, n)
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def get_scores(hist):
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# Mean pixel accuracy
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acc = np.diag(hist).sum() / (hist.sum() + 1e-12)
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# Per class accuracy
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cl_acc = np.diag(hist) / (hist.sum(1) + 1e-12)
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# Per class IoU
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iu = np.diag(hist) / (hist.sum(1) + hist.sum(0) - np.diag(hist) + 1e-12)
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return acc, np.nanmean(cl_acc), np.nanmean(iu), cl_acc, iu
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