Add support for DAT upscaler models
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import os
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import sys
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from modules import modelloader, devices
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from modules.shared import cmd_opts, opts
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from modules.upscaler import Upscaler, UpscalerData
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from modules.upscaler_utils import upscale_with_model
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from icecream import ic
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class UpscalerDAT(Upscaler):
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def __init__(self, user_path):
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self.name = "DAT"
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self.user_path = user_path
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self.scalers = []
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super().__init__()
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for file in self.find_models(ext_filter=[".pt", ".pth"]):
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name = modelloader.friendly_name(file)
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scaler_data = UpscalerData(name, file, upscaler=self, scale=None)
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self.scalers.append(scaler_data)
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for model in get_dat_models(self):
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if model.name in opts.dat_enabled_models:
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self.scalers.append(model)
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def do_upscale(self, img, selected_model):
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try:
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info = self.load_model(selected_model)
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except Exception as e:
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errors.report(f"Unable to load DAT model {path}", exc_info=True)
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return img
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model_descriptor = modelloader.load_spandrel_model(
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info.local_data_path,
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device=self.device,
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prefer_half=(not cmd_opts.no_half and not cmd_opts.upcast_sampling),
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expected_architecture="DAT",
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)
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return upscale_with_model(
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model_descriptor,
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img,
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tile_size=opts.DAT_tile,
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tile_overlap=opts.DAT_tile_overlap,
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)
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def load_model(self, path):
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for scaler in self.scalers:
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if scaler.data_path == path:
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if scaler.local_data_path.startswith("http"):
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scaler.local_data_path = modelloader.load_file_from_url(
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scaler.data_path,
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model_dir=self.model_download_path,
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)
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if not os.path.exists(scaler.local_data_path):
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raise FileNotFoundError(f"DAT data missing: {scaler.local_data_path}")
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return scaler
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raise ValueError(f"Unable to find model info: {path}")
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def get_dat_models(scaler):
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return [
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UpscalerData(
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name="DAT x2",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x2.pth",
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scale=2,
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upscaler=scaler,
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),
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UpscalerData(
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name="DAT x3",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x3.pth",
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scale=3,
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upscaler=scaler,
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),
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UpscalerData(
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name="DAT x4",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x4.pth",
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scale=4,
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upscaler=scaler,
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),
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]
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@ -8,6 +8,11 @@ def realesrgan_models_names():
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return [x.name for x in modules.realesrgan_model.get_realesrgan_models(None)]
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def dat_models_names():
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import modules.dat_model
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return [x.name for x in modules.dat_model.get_dat_models(None)]
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def postprocessing_scripts():
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import modules.scripts
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@ -97,6 +97,9 @@ options_templates.update(options_section(('upscaling', "Upscaling", "postprocess
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"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
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"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
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"realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
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"dat_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which DAT models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.dat_models_names()}),
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"DAT_tile": OptionInfo(192, "Tile size for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
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"DAT_tile_overlap": OptionInfo(8, "Tile overlap for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
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"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}),
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}))
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