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If using mask, scale the masked portion of image

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This commit is contained in:
Jeremy Hummel 2019-08-13 23:45:29 -07:00
commit 390a9638d5
2 changed files with 40 additions and 37 deletions
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17
imagelib/color_transfer.py
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@ -77,11 +77,11 @@ def reinhard_color_transfer(source, target, clip=False, preserve_paper=False, so
a += aMeanTar
b += bMeanTar
# clip/scale the pixel intensities to [0, 255] if they fall
# outside this range
l = _scale_array(l, 0, 100, clip=clip)
a = _scale_array(a, -127, 127, clip=clip)
b = _scale_array(b, -127, 127, clip=clip)
# clip/scale the pixel intensities if they fall
# outside the ranges for LAB
l = _scale_array(l, 0, 100, clip=clip, mask=source_mask)
a = _scale_array(a, -127, 127, clip=clip, mask=source_mask)
b = _scale_array(b, -127, 127, clip=clip, mask=source_mask)
# merge the channels together and convert back to the RGB color
transfer = cv2.merge([l, a, b])
@ -180,7 +180,7 @@ def _min_max_scale(arr, new_range=(0, 255)):
return scaled
def _scale_array(arr, mn, mx, clip=True):
def _scale_array(arr, mn, mx, clip=True, mask=None):
"""
Trim NumPy array values to be in [0, 255] range with option of
clipping or scaling.
@ -197,7 +197,10 @@ def _scale_array(arr, mn, mx, clip=True):
if clip:
scaled = np.clip(arr, mn, mx)
else:
scale_range = (max([arr.min(), mn]), min([arr.max(), mx]))
if mask is not None:
scale_range = (max([np.min(mask * arr), mn]), min([np.max(mask * arr), mx]))
else:
scale_range = (max([np.min(arr), mn]), min([np.max(arr), mx]))
scaled = _min_max_scale(arr, new_range=scale_range)
return scaled

60
imagelib/test/color_transfer.py
View file

@ -15,44 +15,44 @@ class ColorTranfer(unittest.TestCase):
src_samples = SampleLoader.load(SampleType.FACE, './test_src', None)
dst_samples = SampleLoader.load(SampleType.FACE, './test_dst', None)
src_sample = src_samples[2]
src_img = src_sample.load_bgr()
src_mask = src_sample.load_mask()
for src_sample in src_samples:
src_img = src_sample.load_bgr()
src_mask = src_sample.load_mask()
# Toggle to see masks
show_masks = False
# Toggle to see masks
show_masks = False
grid = []
for ct_sample in dst_samples:
print(src_sample.filename, ct_sample.filename)
ct_img = ct_sample.load_bgr()
ct_mask = ct_sample.load_mask()
grid = []
for ct_sample in dst_samples:
print(src_sample.filename, ct_sample.filename)
ct_img = ct_sample.load_bgr()
ct_mask = ct_sample.load_mask()
lct_img = linear_color_transfer(src_img, ct_img)
rct_img = reinhard_color_transfer(src_img, ct_img)
rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True)
rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True)
rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True)
lct_img = linear_color_transfer(src_img, ct_img)
rct_img = reinhard_color_transfer(src_img, ct_img)
rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True)
rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True)
rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True)
masked_rct_img = reinhard_color_transfer(src_img, ct_img, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img = reinhard_color_transfer(src_img, ct_img, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
masked_rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
results = [lct_img, rct_img, rct_img_clip, rct_img_paper, rct_img_paper_clip,
masked_rct_img, masked_rct_img_clip, masked_rct_img_paper, masked_rct_img_paper_clip]
results = [lct_img, rct_img, rct_img_clip, rct_img_paper, rct_img_paper_clip,
masked_rct_img, masked_rct_img_clip, masked_rct_img_paper, masked_rct_img_paper_clip]
if show_masks:
results = [src_mask * im for im in results]
src_img *= src_mask
ct_img *= ct_mask
if show_masks:
results = [src_mask * im for im in results]
src_img *= src_mask
ct_img *= ct_mask
results = np.concatenate((src_img, ct_img, *results), axis=1)
grid.append(results)
results = np.concatenate((src_img, ct_img, *results), axis=1)
grid.append(results)
cv2.namedWindow('test output', cv2.WINDOW_NORMAL)
cv2.imshow('test output', np.concatenate(grid, axis=0))
cv2.waitKey(0)
cv2.namedWindow('test output', cv2.WINDOW_NORMAL)
cv2.imshow('test output', np.concatenate(grid, axis=0))
cv2.waitKey(0)
cv2.destroyAllWindows()