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transfercolor via lab converter now implemented by tensorflow-cpu, which is x2 faster than skimage.

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We cannot use GPU for lab converter in converter multiprocesses, because almost all VRAM ate by model process, so even 300Mb free VRAM not enough for tensorflow lab converter.
Removed skimage dependency.
Refactorings.
This commit is contained in:
iperov 2018-12-01 12:11:54 +04:00
parent 6f0d38d171
commit 5c43f4245e
7 changed files with 229 additions and 67 deletions
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22
models/ConverterMasked.py
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@ -38,7 +38,8 @@ class ConverterMasked(ConverterBase):
self.erode_mask_modifier = erode_mask_modifier
self.blur_mask_modifier = blur_mask_modifier
self.output_face_scale = np.clip(1.0 + output_face_scale_modifier*0.01, 0.5, 1.0)
self.transfercolor = transfercolor
self.transfercolor = transfercolor
self.TFLabConverter = None
self.final_image_color_degrade_power = np.clip (final_image_color_degrade_power, 0, 100)
self.alpha = alpha
@ -199,14 +200,14 @@ class ConverterMasked(ConverterBase):
new_out = cv2.warpAffine( new_out_face_bgr, face_mat, img_size, img_bgr.copy(), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
out_img = np.clip( img_bgr*(1-img_mask_blurry_aaa) + (new_out*img_mask_blurry_aaa) , 0, 1.0 )
if self.transfercolor: #making transfer color from original DST image to fake
from skimage import io, color
lab_clr = color.rgb2lab(img_bgr) #original DST, converting RGB to LAB color space
lab_bw = color.rgb2lab(out_img) #fake, converting RGB to LAB color space
tmp_channel, a_channel, b_channel = cv2.split(lab_clr) #taking color channel A and B from original dst image
l_channel, tmp2_channel, tmp3_channel = cv2.split(lab_bw) #taking lightness channel L from merged fake
img_LAB = cv2.merge((l_channel,a_channel, b_channel)) #merging light and color
out_img = color.lab2rgb(img_LAB) #converting LAB to RGB
if self.transfercolor:
if self.TFLabConverter is None:
self.TFLabConverter = image_utils.TFLabConverter()
img_lab_l, img_lab_a, img_lab_b = np.split ( self.TFLabConverter.bgr2lab (img_bgr), 3, axis=-1 )
out_img_lab_l, out_img_lab_a, out_img_lab_b = np.split ( self.TFLabConverter.bgr2lab (out_img), 3, axis=-1 )
out_img = self.TFLabConverter.lab2bgr ( np.concatenate([out_img_lab_l, img_lab_a, img_lab_b], axis=-1) )
if self.final_image_color_degrade_power != 0:
if debug:
@ -234,4 +235,5 @@ class ConverterMasked(ConverterBase):
debugs += [out_img.copy()]
return debugs if debug else out_img