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54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
import numpy as np
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from numpy.testing import (run_module_suite, assert_equal, assert_raises,
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assert_almost_equal)
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from skimage.measure import psnr, nrmse
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import skimage.data
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np.random.seed(5)
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cam = skimage.data.camera()
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sigma = 20.0
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cam_noisy = np.clip(cam + sigma * np.random.randn(*cam.shape), 0, 255)
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cam_noisy = cam_noisy.astype(cam.dtype)
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def test_PSNR_vs_IPOL():
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# Tests vs. imdiff result from the following IPOL article and code:
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# http://www.ipol.im/pub/art/2011/g_lmii/
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p_IPOL = 22.4497
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p = psnr(cam, cam_noisy)
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assert_almost_equal(p, p_IPOL, decimal=4)
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def test_PSNR_float():
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p_uint8 = psnr(cam, cam_noisy)
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p_float64 = psnr(cam/255., cam_noisy/255., dynamic_range=1)
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assert_almost_equal(p_uint8, p_float64)
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def test_PSNR_errors():
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assert_raises(ValueError, psnr, cam, cam.astype(np.float32))
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assert_raises(ValueError, psnr, cam, cam[:-1, :])
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def test_NRMSE():
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x = np.ones(4)
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y = np.asarray([0., 2., 2., 2.])
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assert_equal(nrmse(y, x, 'mean'), 1/np.mean(y))
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assert_equal(nrmse(y, x, 'Euclidean'), 1/np.sqrt(3))
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assert_equal(nrmse(y, x, 'min-max'), 1/(y.max()-y.min()))
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assert_equal(nrmse(x, x), 0)
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def test_NRMSE_errors():
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x = np.ones(4)
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assert_raises(ValueError, nrmse, x.astype(np.uint8), x.astype(np.float32))
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assert_raises(ValueError, nrmse, x[:-1], x)
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# invalid normalization name
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assert_raises(ValueError, nrmse, x, x, 'foo')
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if __name__ == "__main__":
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run_module_suite()
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