From cf14a6a7aaf8ccb40552990785d5c9e400d93610 Mon Sep 17 00:00:00 2001
From: Aarni Koskela <akx@iki.fi>
Date: Sun, 31 Dec 2023 16:11:18 +0200
Subject: Refactor upscale_2 helper out of ScuNET/SwinIR; make sure devices are
 right

---
 extensions-builtin/SwinIR/scripts/swinir_model.py | 62 +++--------------------
 1 file changed, 8 insertions(+), 54 deletions(-)

(limited to 'extensions-builtin/SwinIR')

diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index 8a555c79..bc427fea 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -1,14 +1,10 @@
 import logging
 import sys
 
-import numpy as np
-import torch
 from PIL import Image
 
-from modules import modelloader, devices, script_callbacks, shared
-from modules.shared import opts
+from modules import devices, modelloader, script_callbacks, shared, upscaler_utils
 from modules.upscaler import Upscaler, UpscalerData
-from modules.upscaler_utils import tiled_upscale_2
 
 SWINIR_MODEL_URL = "https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth"
 
@@ -36,9 +32,7 @@ class UpscalerSwinIR(Upscaler):
         self.scalers = scalers
 
     def do_upscale(self, img: Image.Image, model_file: str) -> Image.Image:
-        current_config = (model_file, opts.SWIN_tile)
-
-        device = self._get_device()
+        current_config = (model_file, shared.opts.SWIN_tile)
 
         if self._cached_model_config == current_config:
             model = self._cached_model
@@ -51,12 +45,13 @@ class UpscalerSwinIR(Upscaler):
             self._cached_model = model
             self._cached_model_config = current_config
 
-        img = upscale(
+        img = upscaler_utils.upscale_2(
             img,
             model,
-            tile=opts.SWIN_tile,
-            tile_overlap=opts.SWIN_tile_overlap,
-            device=device,
+            tile_size=shared.opts.SWIN_tile,
+            tile_overlap=shared.opts.SWIN_tile_overlap,
+            scale=4,  # TODO: This was hard-coded before too...
+            desc="SwinIR",
         )
         devices.torch_gc()
         return img
@@ -77,7 +72,7 @@ class UpscalerSwinIR(Upscaler):
             dtype=devices.dtype,
             expected_architecture="SwinIR",
         )
-        if getattr(opts, 'SWIN_torch_compile', False):
+        if getattr(shared.opts, 'SWIN_torch_compile', False):
             try:
                 model_descriptor.model.compile()
             except Exception:
@@ -88,47 +83,6 @@ class UpscalerSwinIR(Upscaler):
         return devices.get_device_for('swinir')
 
 
-def upscale(
-    img,
-    model,
-    *,
-    tile: int,
-    tile_overlap: int,
-    window_size=8,
-    scale=4,
-    device,
-):
-
-    img = np.array(img)
-    img = img[:, :, ::-1]
-    img = np.moveaxis(img, 2, 0) / 255
-    img = torch.from_numpy(img).float()
-    img = img.unsqueeze(0).to(device, dtype=devices.dtype)
-    with torch.no_grad(), devices.autocast():
-        _, _, h_old, w_old = img.size()
-        h_pad = (h_old // window_size + 1) * window_size - h_old
-        w_pad = (w_old // window_size + 1) * window_size - w_old
-        img = torch.cat([img, torch.flip(img, [2])], 2)[:, :, : h_old + h_pad, :]
-        img = torch.cat([img, torch.flip(img, [3])], 3)[:, :, :, : w_old + w_pad]
-        output = tiled_upscale_2(
-            img,
-            model,
-            tile_size=tile,
-            tile_overlap=tile_overlap,
-            scale=scale,
-            device=device,
-            desc="SwinIR tiles",
-        )
-        output = output[..., : h_old * scale, : w_old * scale]
-        output = output.data.squeeze().float().cpu().clamp_(0, 1).numpy()
-        if output.ndim == 3:
-            output = np.transpose(
-                output[[2, 1, 0], :, :], (1, 2, 0)
-            )  # CHW-RGB to HCW-BGR
-        output = (output * 255.0).round().astype(np.uint8)  # float32 to uint8
-        return Image.fromarray(output, "RGB")
-
-
 def on_ui_settings():
     import gradio as gr
 
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