mirror of
https://github.com/deepfakes/faceswap
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34945cfcd7
* Making Models as plugins * Do not reload model on each image #39 + Adding FaceFilter #53 * Adding @lukaville PR for #43 and #44 (possibly) * Training done in a separate thread * Better log for plugin load * Adding a prefetch to train.py #49 (Note that we prefetch 2 batches of images, due to the queue behavior) + More compact logging with verbose info included * correction of DirectoryProcessor signature * adding missing import * Convert with parallel preprocessing of files * Added coverage var for trainer Added a var with comment. Feel free to add it as argument * corrections * Modifying preview and normalization of image + correction * Cleanup
26 lines
1.3 KiB
Python
26 lines
1.3 KiB
Python
import numpy
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from lib.umeyama import umeyama
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mean_face_x = numpy.array([
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0.000213256, 0.0752622, 0.18113, 0.29077, 0.393397, 0.586856, 0.689483, 0.799124,
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0.904991, 0.98004, 0.490127, 0.490127, 0.490127, 0.490127, 0.36688, 0.426036,
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0.490127, 0.554217, 0.613373, 0.121737, 0.187122, 0.265825, 0.334606, 0.260918,
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0.182743, 0.645647, 0.714428, 0.793132, 0.858516, 0.79751, 0.719335, 0.254149,
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0.340985, 0.428858, 0.490127, 0.551395, 0.639268, 0.726104, 0.642159, 0.556721,
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0.490127, 0.423532, 0.338094, 0.290379, 0.428096, 0.490127, 0.552157, 0.689874,
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0.553364, 0.490127, 0.42689 ])
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mean_face_y = numpy.array([
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0.106454, 0.038915, 0.0187482, 0.0344891, 0.0773906, 0.0773906, 0.0344891,
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0.0187482, 0.038915, 0.106454, 0.203352, 0.307009, 0.409805, 0.515625, 0.587326,
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0.609345, 0.628106, 0.609345, 0.587326, 0.216423, 0.178758, 0.179852, 0.231733,
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0.245099, 0.244077, 0.231733, 0.179852, 0.178758, 0.216423, 0.244077, 0.245099,
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0.780233, 0.745405, 0.727388, 0.742578, 0.727388, 0.745405, 0.780233, 0.864805,
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0.902192, 0.909281, 0.902192, 0.864805, 0.784792, 0.778746, 0.785343, 0.778746,
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0.784792, 0.824182, 0.831803, 0.824182 ])
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landmarks_2D = numpy.stack( [ mean_face_x, mean_face_y ], axis=1 )
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def get_align_mat(face):
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return umeyama( numpy.array(face.landmarksAsXY()[17:]), landmarks_2D, True )[0:2]
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