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Refactor upscale_2 helper out of ScuNET/SwinIR; make sure devices are right

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This commit is contained in:
Aarni Koskela
2023-12-31 16:11:18 +02:00
parent 980970d390
commit cf14a6a7aa
3 changed files with 86 additions and 111 deletions
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48
extensions-builtin/ScuNET/scripts/scunet_model.py
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@@ -1,13 +1,9 @@
import sys
import PIL.Image
import numpy as np
import torch
import modules.upscaler
from modules import devices, modelloader, script_callbacks, errors
from modules.shared import opts
from modules.upscaler_utils import tiled_upscale_2
from modules import devices, errors, modelloader, script_callbacks, shared, upscaler_utils
class UpscalerScuNET(modules.upscaler.Upscaler):
@@ -40,46 +36,23 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
self.scalers = scalers
def do_upscale(self, img: PIL.Image.Image, selected_file):
devices.torch_gc()
try:
model = self.load_model(selected_file)
except Exception as e:
print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr)
return img
device = devices.get_device_for('scunet')
tile = opts.SCUNET_tile
h, w = img.height, img.width
np_img = np.array(img)
np_img = np_img[:, :, ::-1] # RGB to BGR
np_img = np_img.transpose((2, 0, 1)) / 255 # HWC to CHW
torch_img = torch.from_numpy(np_img).float().unsqueeze(0).to(device) # type: ignore
if tile > h or tile > w:
_img = torch.zeros(1, 3, max(h, tile), max(w, tile), dtype=torch_img.dtype, device=torch_img.device)
_img[:, :, :h, :w] = torch_img # pad image
torch_img = _img
with torch.no_grad():
torch_output = tiled_upscale_2(
torch_img,
model,
tile_size=opts.SCUNET_tile,
tile_overlap=opts.SCUNET_tile_overlap,
scale=1,
device=devices.get_device_for('scunet'),
desc="ScuNET tiles",
).squeeze(0)
torch_output = torch_output[:, :h * 1, :w * 1] # remove padding, if any
np_output: np.ndarray = torch_output.float().cpu().clamp_(0, 1).numpy()
del torch_img, torch_output
img = upscaler_utils.upscale_2(
img,
model,
tile_size=shared.opts.SCUNET_tile,
tile_overlap=shared.opts.SCUNET_tile_overlap,
scale=1, # ScuNET is a denoising model, not an upscaler
desc='ScuNET',
)
devices.torch_gc()
output = np_output.transpose((1, 2, 0)) # CHW to HWC
output = output[:, :, ::-1] # BGR to RGB
return PIL.Image.fromarray((output * 255).astype(np.uint8))
return img
def load_model(self, path: str):
device = devices.get_device_for('scunet')
@@ -93,7 +66,6 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
def on_ui_settings():
import gradio as gr
from modules import shared
shared.opts.add_option("SCUNET_tile", shared.OptionInfo(256, "Tile size for SCUNET upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}, section=('upscaling', "Upscaling")).info("0 = no tiling"))
shared.opts.add_option("SCUNET_tile_overlap", shared.OptionInfo(8, "Tile overlap for SCUNET upscalers.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}, section=('upscaling', "Upscaling")).info("Low values = visible seam"))