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XSeg sample generator: additional sample augmentation for training

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iperov 2021-04-30 16:49:32 +04:00
parent 87030bdcdf
commit 081d8faa45
3 changed files with 26 additions and 7 deletions
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1
core/imagelib/__init__.py
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@ -21,6 +21,7 @@ from .SegIEPolys import *
from .blursharpen import LinearMotionBlur, blursharpen
from .filters import apply_random_rgb_levels, \
apply_random_overlay_triangle, \
apply_random_hsv_shift, \
apply_random_sharpen, \
apply_random_motion_blur, \

22
core/imagelib/filters.py
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@ -128,7 +128,29 @@ def apply_random_jpeg_compress( img, chance, mask=None, rnd_state=None ):
return result
def apply_random_overlay_triangle( img, max_alpha, mask=None, rnd_state=None ):
if rnd_state is None:
rnd_state = np.random
h,w,c = img.shape
pt1 = [rnd_state.randint(w), rnd_state.randint(h) ]
pt2 = [rnd_state.randint(w), rnd_state.randint(h) ]
pt3 = [rnd_state.randint(w), rnd_state.randint(h) ]
alpha = rnd_state.uniform()*max_alpha
tri_mask = cv2.fillPoly( np.zeros_like(img), [ np.array([pt1,pt2,pt3], np.int32) ], (alpha,)*c )
if rnd_state.randint(2) == 0:
result = np.clip(img+tri_mask, 0, 1)
else:
result = np.clip(img-tri_mask, 0, 1)
if mask is not None:
result = img*(1-mask) + result*mask
return result
def _min_resize(x, m):
if x.shape[0] < x.shape[1]:
s0 = m

10
samplelib/SampleGeneratorFaceXSeg.py
View file

@ -138,11 +138,9 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
bg_img = imagelib.apply_random_hsv_shift(bg_img)
else:
bg_img = imagelib.apply_random_rgb_levels(bg_img)
c_mask = 1.0 - (1-bg_mask) * (1-mask)
rnd = np.random.uniform()
rnd = 0.15 + np.random.uniform()*0.85
img = img*(c_mask) + img*(1-c_mask)*rnd + bg_img*(1-c_mask)*(1-rnd)
warp_params = imagelib.gen_warp_params(resolution, random_flip, rotation_range=rotation_range, scale_range=scale_range, tx_range=tx_range, ty_range=ty_range )
@ -153,15 +151,13 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
mask[mask < 0.5] = 0.0
mask[mask >= 0.5] = 1.0
mask = np.clip(mask, 0, 1)
#if np.random.randint(4) < 3:
# img = imagelib.apply_random_relight(img)
img = imagelib.apply_random_overlay_triangle(img, max_alpha=0.25, mask=sd.random_circle_faded ([resolution,resolution]))
if np.random.randint(2) == 0:
img = imagelib.apply_random_hsv_shift(img, mask=sd.random_circle_faded ([resolution,resolution]))
else:
img = imagelib.apply_random_rgb_levels(img, mask=sd.random_circle_faded ([resolution,resolution]))
if np.random.randint(2) == 0:
# random face flare