import os import sys import traceback import numpy as np from PIL import Image from basicsr.utils.download_util import load_file_from_url from realesrgan import RealESRGANer from modules.upscaler import Upscaler, UpscalerData from modules.shared import cmd_opts, opts class UpscalerRealESRGAN(Upscaler): def __init__(self, path): self.name = "RealESRGAN" self.user_path = path super().__init__() try: from basicsr.archs.rrdbnet_arch import RRDBNet from realesrgan import RealESRGANer from realesrgan.archs.srvgg_arch import SRVGGNetCompact self.enable = True self.scalers = [] scalers = self.load_models(path) for scaler in scalers: if scaler.name in opts.realesrgan_enabled_models: self.scalers.append(scaler) except Exception: print("Error importing Real-ESRGAN:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) self.enable = False self.scalers = [] def do_upscale(self, img, path): if not self.enable: return img info = self.load_model(path) if not os.path.exists(info.data_path): print("Unable to load RealESRGAN model: %s" % info.name) return img upsampler = RealESRGANer( scale=info.scale, model_path=info.data_path, model=info.model(), half=not cmd_opts.no_half, tile=opts.ESRGAN_tile, tile_pad=opts.ESRGAN_tile_overlap, ) upsampled = upsampler.enhance(np.array(img), outscale=info.scale)[0] image = Image.fromarray(upsampled) return image def load_model(self, path): try: info = None for scaler in self.scalers: if scaler.data_path == path: info = scaler if info is None: print(f"Unable to find model info: {path}") return None model_file = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True) info.data_path = model_file return info except Exception as e: print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) return None def load_models(self, _): return get_realesrgan_models(self) def get_realesrgan_models(scaler): try: from basicsr.archs.rrdbnet_arch import RRDBNet from realesrgan.archs.srvgg_arch import SRVGGNetCompact models = [ UpscalerData( name="R-ESRGAN General 4xV3", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth", scale=4, upscaler=scaler, model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu') ), UpscalerData( name="R-ESRGAN General WDN 4xV3", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth", scale=4, upscaler=scaler, model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu') ), UpscalerData( name="R-ESRGAN AnimeVideo", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth", scale=4, upscaler=scaler, model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu') ), UpscalerData( name="R-ESRGAN 4x+", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth", scale=4, upscaler=scaler, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4) ), UpscalerData( name="R-ESRGAN 4x+ Anime6B", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth", scale=4, upscaler=scaler, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4) ), UpscalerData( name="R-ESRGAN 2x+", path="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth", scale=2, upscaler=scaler, 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 making Real-ESRGAN models list:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr)