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Perlin noise

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hkinghuang
2023-05-15 11:16:08 +08:00
parent 5f1d07d62f
commit bca6a44974
3 changed files with 12 additions and 4 deletions
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6
library/custom_train_functions.py
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@@ -410,9 +410,9 @@ def rand_perlin_2d_octaves(device, shape, res, octaves=1, persistence=0.5):
amplitude *= persistence amplitude *= persistence
return noise return noise
def perlin_noise(noise, device): def perlin_noise(noise, device,octaves):
b, c, w, h = noise.shape() b, c, w, h = noise.shape()
perlin = lambda : rand_perlin_2d_octaves(device,(w,h),(4,4),1) perlin = lambda : rand_perlin_2d_octaves(device,(w,h),(4,4),octaves)
noise_perlin_r = torch.rand(noise.shape, device=device) + perlin() noise_perlin_r = torch.rand(noise.shape, device=device) + perlin()
noise_perlin_g = torch.rand(noise.shape, device=device) + perlin() noise_perlin_g = torch.rand(noise.shape, device=device) + perlin()
noise_perlin_b = torch.rand(noise.shape, device=device) + perlin() noise_perlin_b = torch.rand(noise.shape, device=device) + perlin()
@@ -420,7 +420,7 @@ def perlin_noise(noise, device):
(noise_perlin_r, (noise_perlin_r,
noise_perlin_g, noise_perlin_g,
noise_perlin_b), noise_perlin_b),
2) 1)
return noise_perlin return noise_perlin

6
library/train_util.py
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@@ -2127,6 +2127,12 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
default=None, default=None,
help="enable multires noise with this number of iterations (if enabled, around 6-10 is recommended) / Multires noiseを有効にしてこのイテレーション数を設定する（有効にする場合は6-10程度を推奨）", help="enable multires noise with this number of iterations (if enabled, around 6-10 is recommended) / Multires noiseを有効にしてこのイテレーション数を設定する（有効にする場合は6-10程度を推奨）",
) )
parser.add_argument(
"--perlin_noise",
type=int,
default=None,
help="enable perlin noise and set the octaves",
)
parser.add_argument( parser.add_argument(
"--multires_noise_discount", "--multires_noise_discount",
type=float, type=float,

4
train_db.py
View File

@@ -23,7 +23,7 @@ from library.config_util import (
BlueprintGenerator, BlueprintGenerator,
) )
import library.custom_train_functions as custom_train_functions import library.custom_train_functions as custom_train_functions
from library.custom_train_functions import apply_snr_weight, get_weighted_text_embeddings, pyramid_noise_like, apply_noise_offset from library.custom_train_functions import apply_snr_weight, get_weighted_text_embeddings, pyramid_noise_like, apply_noise_offset,perlin_noise
def train(args): def train(args):
@@ -274,6 +274,8 @@ def train(args):
noise = apply_noise_offset(latents, noise, args.noise_offset, args.adaptive_noise_scale) noise = apply_noise_offset(latents, noise, args.noise_offset, args.adaptive_noise_scale)
elif args.multires_noise_iterations: elif args.multires_noise_iterations:
noise = pyramid_noise_like(noise, latents.device, args.multires_noise_iterations, args.multires_noise_discount) noise = pyramid_noise_like(noise, latents.device, args.multires_noise_iterations, args.multires_noise_discount)
elif args.perlin_noise:
noise = perlin_noise(noise,latents.device,args.perlin_noise)
# Get the text embedding for conditioning # Get the text embedding for conditioning
with torch.set_grad_enabled(global_step < args.stop_text_encoder_training): with torch.set_grad_enabled(global_step < args.stop_text_encoder_training):