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update SampleGeneratorFaceSkinSegDataset

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Colombo 2020-03-13 19:27:27 +04:00
parent 7c89077321
commit 144675020c
1 changed files with 80 additions and 79 deletions
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15
samplelib/SampleGeneratorFaceSkinSegDataset.py
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@ -8,6 +8,7 @@ import cv2
import numpy as np import numpy as np
from core import imagelib, mplib, pathex from core import imagelib, mplib, pathex
from core.imagelib import sd
from core.cv2ex import * from core.cv2ex import *
from core.interact import interact as io from core.interact import interact as io
from core.joblib import SubprocessGenerator, ThisThreadGenerator from core.joblib import SubprocessGenerator, ThisThreadGenerator
@ -121,8 +122,9 @@ class SampleGeneratorFaceSkinSegDataset(SampleGeneratorBase):
samples = pickle.loads(pickled_samples) samples = pickle.loads(pickled_samples)
obstructions_images_paths_len = len(obstructions_images_paths)
shuffle_o_idxs = [] shuffle_o_idxs = []
o_idxs = [*range(len(obstructions_images_paths))] o_idxs = [*range(obstructions_images_paths_len)]
shuffle_idxs = [] shuffle_idxs = []
idxs = [*range(len(samples))] idxs = [*range(len(samples))]
@ -178,6 +180,7 @@ class SampleGeneratorFaceSkinSegDataset(SampleGeneratorBase):
if len(mask.shape) == 2: if len(mask.shape) == 2:
mask = mask[...,None] mask = mask[...,None]
if obstructions_images_paths_len != 0:
# apply obstruction # apply obstruction
if len(shuffle_o_idxs) == 0: if len(shuffle_o_idxs) == 0:
shuffle_o_idxs = o_idxs.copy() shuffle_o_idxs = o_idxs.copy()
@ -241,13 +244,11 @@ class SampleGeneratorFaceSkinSegDataset(SampleGeneratorBase):
mask[mask >= 0.5] = 1.0 mask[mask >= 0.5] = 1.0
mask = np.clip(mask, 0, 1) mask = np.clip(mask, 0, 1)
img = imagelib.apply_random_hsv_shift(img)
#todo random mask for blur img = imagelib.apply_random_hsv_shift(img, mask=sd.random_circle_faded ([resolution,resolution]))
img = imagelib.apply_random_motion_blur( img, motion_blur_chance, motion_blur_mb_max_size, mask=sd.random_circle_faded ([resolution,resolution]))
img = imagelib.apply_random_motion_blur( img, motion_blur_chance, motion_blur_mb_max_size ) img = imagelib.apply_random_gaussian_blur( img, gaussian_blur_chance, gaussian_blur_kernel_max_size, mask=sd.random_circle_faded ([resolution,resolution]))
img = imagelib.apply_random_gaussian_blur( img, gaussian_blur_chance, gaussian_blur_kernel_max_size ) img = imagelib.apply_random_bilinear_resize( img, random_bilinear_resize_chance, random_bilinear_resize_max_size_per, mask=sd.random_circle_faded ([resolution,resolution]))
img = imagelib.apply_random_bilinear_resize( img, random_bilinear_resize_chance, random_bilinear_resize_max_size_per )
if data_format == "NCHW": if data_format == "NCHW":
img = np.transpose(img, (2,0,1) ) img = np.transpose(img, (2,0,1) )