def ver1to2(layer: Layer) -> Layer:
"""Convert a 1.8 skin to 1.8_bedrock.
Args:
layer (Layer): texture layer to upscale
Returns:
Layer: upscaled layer
"""
image = layer.image.convert("RGBA")
args = argparse.Namespace(
gpu=-1,
method="scale",
noise_level=1,
color="rgb",
model_dir=f"{Path(__file__).resolve().parent}/models/vgg7/",
arch="VGG7",
scale_ratio=2,
tta_level=8,
tta=False,
block_size=128,
batch_size=16,
)
model = load_models(args)
image = cleanImg(upscale_image(args, image, model["scale"]))
return Layer(
layer.name,
image,
image.size,
(layer.offsets[0] * 2, layer.offsets[1] * 2),
layer.opacity,
layer.visible,
layer.blendmode,
)
def test_foreground_png():
"""test_foreground_png"""
src = Image.open(f"{THISDIR}/data/foreground.png")
dst = src.copy()
dst = upscale_image(args, dst, models["scale"])
# dst.convert(src.mode).save(f"{THISDIR}/data/foreground_upresnet10_expected.png")
assert imgcompare.is_equal(
dst,
f"{THISDIR}/data/foreground_upresnet10_expected.png",
tolerance=0.2,
)
def png_to_waifu2x(data, method, arch, color):
import sys
import os
import types
if 'waifu2x_chainer' not in sys.path:
sys.path.append('waifu2x_chainer')
import waifu2x
if not hasattr(png_to_waifu2x, 'gpu'):
png_to_waifu2x.gpu = -1
cfg = types.SimpleNamespace()
cfg.scale_ratio = 2.0
cfg.tta = True
cfg.tta_level = 8
cfg.block_size = 128
cfg.batch_size = 16
cfg.method = method # scale, noise, scale_noise
cfg.arch = arch # VGG7, UpConv7, ResNet10, UpResNet10
cfg.color = color # rgb, y
cfg.gpu = png_to_waifu2x.gpu
cfg.model_dir = os.path.join('waifu2x_chainer','models',cfg.arch.lower())
models = waifu2x.load_models(cfg)
src = data_to_image(data)
# Can get out of memory errors if cuda is multiprocessed
# TODO: Maybe revisit this? Seems to get away with it for abit before crashing and burning
try:
with HiddenPrints():
dst = waifu2x.upscale_image(cfg, src, models['scale'])
except Exception as e:
print(e)
raise Exception('Could not waifu2x upscale, caught error.')
return image_to_data(dst)