github/DeepFaceLab
1
0
Fork 0
mirror of https://github.com/iperov/DeepFaceLab.git synced 2025-08-19 21:13:20 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

Motion blur

Browse source
This commit is contained in:
Jeremy Hummel 2021-05-23 18:18:35 -07:00
commit b2cf0dec59
2 changed files with 18 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

6
models/Model_SAEHD/Model.py
View file

@ -58,6 +58,8 @@ class SAEHDModel(ModelBase):
default_random_warp = self.options['random_warp'] = self.load_or_def_option('random_warp', True) default_random_warp = self.options['random_warp'] = self.load_or_def_option('random_warp', True)
default_random_downsample = self.options['random_downsample'] = self.load_or_def_option('random_downsample', False) default_random_downsample = self.options['random_downsample'] = self.load_or_def_option('random_downsample', False)
default_random_noise = self.options['random_noise'] = self.load_or_def_option('random_noise', False) default_random_noise = self.options['random_noise'] = self.load_or_def_option('random_noise', False)
default_random_blur = self.options['random_blur'] = self.load_or_def_option('random_blur', False)
default_background_power = self.options['background_power'] = self.load_or_def_option('background_power', 0.0) default_background_power = self.options['background_power'] = self.load_or_def_option('background_power', 0.0)
default_true_face_power = self.options['true_face_power'] = self.load_or_def_option('true_face_power', 0.0) default_true_face_power = self.options['true_face_power'] = self.load_or_def_option('true_face_power', 0.0)
default_face_style_power = self.options['face_style_power'] = self.load_or_def_option('face_style_power', 0.0) default_face_style_power = self.options['face_style_power'] = self.load_or_def_option('face_style_power', 0.0)
@ -163,7 +165,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
self.options['random_downsample'] = io.input_bool("Enable random downsample of samples", default_random_downsample, help_message="") self.options['random_downsample'] = io.input_bool("Enable random downsample of samples", default_random_downsample, help_message="")
self.options['random_noise'] = io.input_bool("Enable random noise added to samples", default_random_noise, help_message="") self.options['random_noise'] = io.input_bool("Enable random noise added to samples", default_random_noise, help_message="")
# self.options['random_blur'] = io.input_bool("Enable random blur of samples", False, help_message="") self.options['random_blur'] = io.input_bool("Enable random blur of samples", False, help_message="")
# self.options['random_jpeg'] = io.input_bool("Enable random jpeg compression of samples", False, help_message="") # self.options['random_jpeg'] = io.input_bool("Enable random jpeg compression of samples", False, help_message="")
self.options['gan_version'] = np.clip (io.input_int("GAN version", default_gan_version, add_info="2 or 3", help_message="Choose GAN version (v2: 7/16/2020, v3: 1/3/2021):"), 2, 3) self.options['gan_version'] = np.clip (io.input_int("GAN version", default_gan_version, add_info="2 or 3", help_message="Choose GAN version (v2: 7/16/2020, v3: 1/3/2021):"), 2, 3)
@ -755,6 +757,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':random_warp, output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':random_warp,
'random_downsample': self.options['random_downsample'], 'random_downsample': self.options['random_downsample'],
'random_noise': self.options['random_noise'], 'random_noise': self.options['random_noise'],
'random_blur': self.options['random_blur'],
'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode, 'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode,
'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False , 'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}, {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False , 'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
@ -769,6 +772,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':random_warp, output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':random_warp,
'random_downsample': self.options['random_downsample'], 'random_downsample': self.options['random_downsample'],
'random_noise': self.options['random_noise'], 'random_noise': self.options['random_noise'],
'random_blur': self.options['random_blur'],
'transform':True, 'channel_type' : channel_type, 'ct_mode': fs_aug, 'transform':True, 'channel_type' : channel_type, 'ct_mode': fs_aug,
'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False , 'transform':True, 'channel_type' : channel_type, 'ct_mode': fs_aug, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}, {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False , 'transform':True, 'channel_type' : channel_type, 'ct_mode': fs_aug, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},

14
samplelib/SampleProcessor.py
View file

@ -7,7 +7,7 @@ import numpy as np
from core import imagelib from core import imagelib
from core.cv2ex import * from core.cv2ex import *
from core.imagelib import sd from core.imagelib import sd, blursharpen
from core.imagelib.color_transfer import random_lab_rotation from core.imagelib.color_transfer import random_lab_rotation
from facelib import FaceType, LandmarksProcessor from facelib import FaceType, LandmarksProcessor
@ -114,6 +114,7 @@ class SampleProcessor(object):
transform = opts.get('transform', False) transform = opts.get('transform', False)
random_downsample = opts.get('random_downsample', False) random_downsample = opts.get('random_downsample', False)
random_noise = opts.get('random_noise', False) random_noise = opts.get('random_noise', False)
random_blur = opts.get('random_blur', False)
motion_blur = opts.get('motion_blur', None) motion_blur = opts.get('motion_blur', None)
gaussian_blur = opts.get('gaussian_blur', None) gaussian_blur = opts.get('gaussian_blur', None)
random_bilinear_resize = opts.get('random_bilinear_resize', None) random_bilinear_resize = opts.get('random_bilinear_resize', None)
@ -237,6 +238,17 @@ class SampleProcessor(object):
noise = np.random.poisson(lam=noise_lam, size=img.shape) noise = np.random.poisson(lam=noise_lam, size=img.shape)
img += noise / 255.0 img += noise / 255.0
# Apply random blur
if random_blur:
blur_type = np.random.choice(['motion', 'gaussian'])
if blur_type == 'motion':
blur_k = np.random.randint(10, 20)
blur_angle = 360 * np.random.random()
img = blursharpen.LinearMotionBlur(img, blur_k, blur_angle)
elif blur_type == 'gaussian':
pass
img = imagelib.warp_by_params (params_per_resolution[resolution], img, warp, transform, can_flip=True, border_replicate=border_replicate) img = imagelib.warp_by_params (params_per_resolution[resolution], img, warp, transform, can_flip=True, border_replicate=border_replicate)
img = np.clip(img.astype(np.float32), 0, 1) img = np.clip(img.astype(np.float32), 0, 1)