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moving some files

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This commit is contained in:
Colombo 2019-10-14 09:34:44 +04:00
parent 2b264da86b
commit e013cb0f6b
14 changed files with 303 additions and 57 deletions
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28
models/Model_DEV_FANSEG/Model.py
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@ -1,9 +1,8 @@
import numpy as np
from nnlib import nnlib
from nnlib import nnlib, TernausNet
from models import ModelBase
from facelib import FaceType
from facelib import FANSegmentator
from samplelib import *
from interact import interact as io
@ -29,17 +28,18 @@ class Model(ModelBase):
#override
def onInitialize(self):
exec(nnlib.import_all(), locals(), globals())
self.set_vram_batch_requirements( {1.5:4} )
self.set_vram_batch_requirements( {1.5:4, 11:48} )
self.resolution = 256
self.face_type = FaceType.FULL if self.options['face_type'] == 'f' else FaceType.HALF
self.fan_seg = FANSegmentator(self.resolution,
FaceType.toString(self.face_type),
load_weights=not self.is_first_run(),
weights_file_root=self.get_model_root_path(),
training=True)
model_name = 'FANSeg'
model_name = 'FANCHQ'
self.fan_seg = TernausNet(model_name, self.resolution,
FaceType.toString(self.face_type),
load_weights=not self.is_first_run(),
weights_file_root=self.get_model_root_path(),
training=True)
if self.is_training_mode:
t = SampleProcessor.Types
@ -48,13 +48,13 @@ class Model(ModelBase):
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=True),
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution, 'motion_blur':(25, 5), 'border_replicate':False },
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR), 'resolution' : self.resolution, 'motion_blur':(25, 5), 'gaussian_blur':(25,5), 'border_replicate':False, 'random_hsv_shift' : True },
{ 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_M), 'resolution': self.resolution },
]),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=True ),
output_sample_types=[ { 'types': (t.IMG_TRANSFORMED , face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution},
output_sample_types=[ { 'types': (t.IMG_TRANSFORMED , face_type, t.MODE_BGR), 'resolution' : self.resolution, 'random_hsv_shift' : True},
])
])
@ -73,11 +73,14 @@ class Model(ModelBase):
#override
def onGetPreview(self, sample):
test_A = sample[0][0][0:4] #first 4 samples
test_Am = sample[0][1][0:4] #first 4 samples
test_B = sample[1][0][0:4] #first 4 samples
mAA = self.fan_seg.extract(test_A)
mBB = self.fan_seg.extract(test_B)
test_Am = np.repeat ( test_Am, (3,), -1)
mAA = np.repeat ( mAA, (3,), -1)
mBB = np.repeat ( mBB, (3,), -1)
@ -85,6 +88,7 @@ class Model(ModelBase):
for i in range(0, len(test_A)):
st.append ( np.concatenate ( (
test_A[i,:,:,0:3],
test_Am[i],
mAA[i],
test_A[i,:,:,0:3]*mAA[i],
), axis=1) )
@ -92,7 +96,7 @@ class Model(ModelBase):
st2 = []
for i in range(0, len(test_B)):
st2.append ( np.concatenate ( (
test_B[i,:,:,0:3],
test_B[i,:,:,0:3],
mBB[i],
test_B[i,:,:,0:3]*mBB[i],
), axis=1) )