42 lines
2.0 KiB
Python
42 lines
2.0 KiB
Python
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# NVIDIA CORPORATION and its licensors retain all intellectual property
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# and proprietary rights in and to this software, related documentation
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# and any modifications thereto. Any use, reproduction, disclosure or
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# distribution of this software and related documentation without an express
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# license agreement from NVIDIA CORPORATION is strictly prohibited.
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"""Frechet Inception Distance (FID) from the paper
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"GANs trained by a two time-scale update rule converge to a local Nash
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equilibrium". Matches the original implementation by Heusel et al. at
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https://github.com/bioinf-jku/TTUR/blob/master/fid.py"""
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import numpy as np
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import scipy.linalg
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from . import metric_utils
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#----------------------------------------------------------------------------
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def compute_fid(opts, max_real, num_gen):
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# Direct TorchScript translation of http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz
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detector_url = 'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/metrics/inception-2015-12-05.pkl'
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detector_kwargs = dict(return_features=True) # Return raw features before the softmax layer.
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mu_real, sigma_real = metric_utils.compute_feature_stats_for_dataset(
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opts=opts, detector_url=detector_url, detector_kwargs=detector_kwargs,
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rel_lo=0, rel_hi=0, capture_mean_cov=True, max_items=max_real).get_mean_cov()
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mu_gen, sigma_gen = metric_utils.compute_feature_stats_for_generator(
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opts=opts, detector_url=detector_url, detector_kwargs=detector_kwargs,
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rel_lo=0, rel_hi=1, capture_mean_cov=True, max_items=num_gen).get_mean_cov()
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if opts.rank != 0:
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return float('nan')
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m = np.square(mu_gen - mu_real).sum()
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s, _ = scipy.linalg.sqrtm(np.dot(sigma_gen, sigma_real), disp=False) # pylint: disable=no-member
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fid = np.real(m + np.trace(sigma_gen + sigma_real - s * 2))
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return float(fid)
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#----------------------------------------------------------------------------
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