stable-diffusion-webui/modules/realesrgan_model.py

120 lines
4.7 KiB
Python

import sys
import traceback
from collections import namedtuple
import numpy as np
from PIL import Image
from realesrgan import RealESRGANer
import modules.images
from modules.shared import cmd_opts, opts
RealesrganModelInfo = namedtuple("RealesrganModelInfo", ["name", "location", "model", "netscale"])
realesrgan_models = []
have_realesrgan = False
def get_realesrgan_models():
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
models = [
RealesrganModelInfo(
name="Real-ESRGAN General x4x3",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN General WDN x4x3",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN AnimeVideo",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
netscale=4,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus anime 6B",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
netscale=4,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 2x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
netscale=2,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
),
]
return models
except Exception as e:
print("Error makeing Real-ESRGAN midels list:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
class UpscalerRealESRGAN(modules.images.Upscaler):
def __init__(self, upscaling, model_index):
self.upscaling = upscaling
self.model_index = model_index
self.name = realesrgan_models[model_index].name
def do_upscale(self, img):
return upscale_with_realesrgan(img, self.upscaling, self.model_index)
def setup_realesrgan():
global realesrgan_models
global have_realesrgan
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
realesrgan_models = get_realesrgan_models()
have_realesrgan = True
for i, model in enumerate(realesrgan_models):
if model.name in opts.realesrgan_enabled_models:
modules.shared.sd_upscalers.append(UpscalerRealESRGAN(model.netscale, i))
except Exception:
print("Error importing Real-ESRGAN:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
realesrgan_models = [RealesrganModelInfo('None', '', 0, None)]
have_realesrgan = False
def upscale_with_realesrgan(image, RealESRGAN_upscaling, RealESRGAN_model_index):
if not have_realesrgan:
return image
info = realesrgan_models[RealESRGAN_model_index]
model = info.model()
upsampler = RealESRGANer(
scale=info.netscale,
model_path=info.location,
model=model,
half=not cmd_opts.no_half,
tile=opts.ESRGAN_tile,
tile_pad=opts.ESRGAN_tile_overlap,
)
upsampled = upsampler.enhance(np.array(image), outscale=RealESRGAN_upscaling)[0]
image = Image.fromarray(upsampled)
return image