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fix bug with samples that were not clipped after tanh-untanh transformations, upd README.md

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iperov 2019-02-10 10:45:51 +04:00
parent 51a13c90d1
commit 854ab11de3
3 changed files with 16 additions and 8 deletions
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7
models/Model_SAE/Model.py
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@ -345,10 +345,10 @@ class SAEModel(ModelBase):
test_B_m = sample[1][2][0:4]
if self.options['learn_mask']:
S, D, SS, DD, SD, SDM = [ x / 2 + 0.5 for x in ([test_A,test_B] + self.AE_view ([test_A, test_B]) ) ]
S, D, SS, DD, SD, SDM = [ np.clip(x / 2 + 0.5, 0.0, 1.0) for x in ([test_A,test_B] + self.AE_view ([test_A, test_B]) ) ]
SDM, = [ np.repeat (x, (3,), -1) for x in [SDM] ]
else:
S, D, SS, DD, SD, = [ x / 2 + 0.5 for x in ([test_A,test_B] + self.AE_view ([test_A, test_B]) ) ]
S, D, SS, DD, SD, = [ np.clip(x / 2 + 0.5, 0.0, 1.0) for x in ([test_A,test_B] + self.AE_view ([test_A, test_B]) ) ]
st = []
for i in range(0, len(test_A)):
@ -360,7 +360,8 @@ class SAEModel(ModelBase):
return [ ('SAE', np.concatenate (st, axis=0 )), ]
def predictor_func (self, face):
face_tanh = face * 2.0 - 1.0
face_tanh = np.clip(face * 2.0 - 1.0, -1.0, 1.0)
face_bgr = face_tanh[...,0:3]
prd = [ (x[0] + 1.0) / 2.0 for x in self.AE_convert ( [ np.expand_dims(face_bgr,0) ] ) ]