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update == 04.20.2019 == (#242)

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* superb improved fanseg

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* added FANseg extractor for src and dst faces to use it in training

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* update to 'partial' func

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* trained FANSeg_256_full_face.h5,
new experimental models: AVATAR, RecycleGAN

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* fix for TCC mode cards(tesla), was conflict with plaidML initialization.

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* update manuals

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This commit is contained in:
iperov 2019-04-20 08:23:08 +04:00 • committed by GitHub
parent 7be2fd67f5
commit 046649e6be
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32 changed files with 1152 additions and 329 deletions
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29
samplelib/SampleProcessor.py
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@ -13,18 +13,18 @@ class SampleProcessor(object):
WARPED_TRANSFORMED = 0x00000004,
TRANSFORMED = 0x00000008,
LANDMARKS_ARRAY = 0x00000010, #currently unused
RANDOM_CLOSE = 0x00000020, #currently unused
MORPH_TO_RANDOM_CLOSE = 0x00000040, #currently unused
FACE_TYPE_HALF = 0x00000100,
FACE_TYPE_FULL = 0x00000200,
FACE_TYPE_HEAD = 0x00000400, #currently unused
FACE_TYPE_AVATAR = 0x00000800, #currently unused
FACE_MASK_FULL = 0x00001000,
FACE_MASK_EYES = 0x00002000, #currently unused
MODE_BGR = 0x00010000, #BGR
MODE_G = 0x00020000, #Grayscale
MODE_GGG = 0x00040000, #3xGrayscale
@ -35,7 +35,7 @@ class SampleProcessor(object):
class Options(object):
#motion_blur = [chance_int, range] - chance 0..100 to apply to face (not mask), and range [1..3] where 3 is highest power of motion blur
def __init__(self, random_flip = True, normalize_tanh = False, rotation_range=[-10,10], scale_range=[-0.05, 0.05], tx_range=[-0.05, 0.05], ty_range=[-0.05, 0.05], motion_blur=None ):
self.random_flip = random_flip
self.normalize_tanh = normalize_tanh
@ -49,11 +49,11 @@ class SampleProcessor(object):
chance = np.clip(chance, 0, 100)
range = [3,5,7,9][ : np.clip(range, 0, 3)+1 ]
self.motion_blur = (chance, range)
@staticmethod
def process (sample, sample_process_options, output_sample_types, debug):
SPTF = SampleProcessor.TypeFlags
sample_bgr = sample.load_bgr()
h,w,c = sample_bgr.shape
@ -113,7 +113,7 @@ class SampleProcessor(object):
target_face_type = FaceType.HEAD
elif f & SPTF.FACE_TYPE_AVATAR != 0:
target_face_type = FaceType.AVATAR
apply_motion_blur = f & SPTF.OPT_APPLY_MOTION_BLUR != 0
if img_type == 4:
@ -170,9 +170,16 @@ class SampleProcessor(object):
if np.random.randint(100) < chance :
dim = mb_range[ np.random.randint(len(mb_range) ) ]
img = imagelib.LinearMotionBlur (img, dim, np.random.randint(180) )
if face_mask_type == 1:
mask = LandmarksProcessor.get_image_hull_mask (img.shape, cur_sample.landmarks, cur_sample.ie_polys)
mask = cur_sample.load_fanseg_mask() #using fanseg_mask if exist
if mask is None:
mask = LandmarksProcessor.get_image_hull_mask (img.shape, cur_sample.landmarks)
if cur_sample.ie_polys is not None:
cur_sample.ie_polys.overlay_mask(mask)
img = np.concatenate( (img, mask ), -1 )
elif face_mask_type == 2:
mask = LandmarksProcessor.get_image_eye_mask (img.shape, cur_sample.landmarks)
@ -202,7 +209,7 @@ class SampleProcessor(object):
img_mask = img[...,3:4]
if f & SPTF.MODE_BGR != 0:
img = img
img = img_bgr
elif f & SPTF.MODE_BGR_SHUFFLE != 0:
img_bgr = np.take (img_bgr, np.random.permutation(img_bgr.shape[-1]), axis=-1)
img = np.concatenate ( (img_bgr,img_mask) , -1 )