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import os
import sys
import traceback
from collections import namedtuple
import numpy as np
from PIL import Image
from basicsr.utils.download_util import load_file_from_url
from realesrgan import RealESRGANer
import modules.images
from modules.paths import models_path
from modules.shared import cmd_opts, opts
model_dir = "RealESRGAN"
model_path = os.path.join(models_path, model_dir)
cmd_dir = None
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.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 making Real-ESRGAN models 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_model(dirname):
global model_path
if not os.path.exists(model_path):
os.makedirs(model_path)
global realesrgan_models
global have_realesrgan
if model_path != dirname:
model_path = dirname
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()
model_file = load_file_from_url(url=info.location, model_dir=model_path, progress=True)
if not os.path.exists(model_file):
print("Unable to load RealESRGAN model: %s" % info.name)
return image
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
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