Spaces:
Runtime error
Runtime error
File size: 5,125 Bytes
c4aa815 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 |
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.local_data_path):
print("Unable to load RealESRGAN model: %s" % info.name)
return img
upsampler = RealESRGANer(
scale=info.scale,
model_path=info.local_data_path,
model=info.model(),
half=not cmd_opts.no_half and not cmd_opts.upcast_sampling,
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 = next(iter([scaler for scaler in self.scalers if scaler.data_path == path]), None)
if info is None:
print(f"Unable to find model info: {path}")
return None
info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True)
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)
|