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