cleanup upscaler settings

modules/postprocess/esrgan_model.py

@@ -188,10 +188,10 @@ def upscale_without_tiling(model, img):
 
 
 def esrgan_upscale(model, img):
-    if opts.ESRGAN_tile == 0:
+    if opts.upscaler_tile_size == 0:
         return upscale_without_tiling(model, img)
 
-    grid = images.split_grid(img, opts.ESRGAN_tile, opts.ESRGAN_tile, opts.ESRGAN_tile_overlap)
+    grid = images.split_grid(img, opts.upscaler_tile_size, opts.upscaler_tile_size, opts.upscaler_tile_overlap)
     newtiles = []
     scale_factor = 1
 

modules/postprocess/realesrgan_model.py

@@ -55,8 +55,8 @@ class UpscalerRealESRGAN(Upscaler):
                 model_path=info.local_data_path,
                 model=info.model(),
                 half=not opts.no_half and not opts.upcast_sampling,
-                tile=opts.ESRGAN_tile,
-                tile_pad=opts.ESRGAN_tile_overlap,
+                tile=opts.upscaler_tile_size,
+                tile_pad=opts.upscaler_tile_overlap,
                 device=device,
             )
             self.models[info.local_data_path] = upsampler

modules/postprocess/scunet_model.py

@@ -39,8 +39,8 @@ class UpscalerSCUNet(Upscaler):
     def tiled_inference(img, model):
         # test the image tile by tile
         h, w = img.shape[2:]
-        tile = opts.SCUNET_tile
-        tile_overlap = opts.SCUNET_tile_overlap
+        tile = opts.upscaler_tile_size
+        tile_overlap = opts.upscaler_tile_overlap
         if tile == 0:
             return model(img)
         assert tile % 8 == 0, "tile size should be a multiple of window_size"
@@ -72,7 +72,7 @@ class UpscalerSCUNet(Upscaler):
         model = self.load_model(selected_file)
         if model is None:
             return img
-        tile = opts.SCUNET_tile
+        tile = opts.upscaler_tile_size
         h, w = img.height, img.width
         np_img = np.array(img)
         np_img = np_img[:, :, ::-1]  # RGB to BGR
@@ -95,13 +95,3 @@ class UpscalerSCUNet(Upscaler):
             log.debug(f"Upscaler unloaded: type={self.name} model={selected_file}")
             devices.torch_gc(force=True)
         return img
-
-
-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=('postprocessing', "Postprocessing")).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=('postprocessing', "Postprocessing")).info("Low values = visible seam"))
-
-
-script_callbacks.on_ui_settings(on_ui_settings)

modules/postprocess/swinir_model.py

@@ -85,8 +85,8 @@ def upscale(
         window_size=8,
         scale=4,
 ):
-    tile = tile or shared.opts.SWIN_tile
-    tile_overlap = tile_overlap or shared.opts.SWIN_tile_overlap
+    tile = tile or shared.opts.upscaler_tile_size
+    tile_overlap = tile_overlap or shared.opts.upscaler_tile_overlap
     img = np.array(img)
     img = img[:, :, ::-1]
     img = np.moveaxis(img, 2, 0) / 255
@@ -140,12 +140,3 @@ def inference(img, model, tile, tile_overlap, window_size, scale):
                 progress.update(task, advance=1, description="Upscaling")
     output = E.div_(W)
     return output
-
-
-def on_ui_settings():
-    import gradio as gr
-    shared.opts.add_option("SWIN_tile", shared.OptionInfo(192, "Tile size for SwinIR upscaler", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}, section=('postprocessing', "Postprocessing")))
-    shared.opts.add_option("SWIN_tile_overlap", shared.OptionInfo(8, "Tile overlap for SwinIR upscaler", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}, section=('postprocessing', "Postprocessing")))
-
-
-script_callbacks.on_ui_settings(on_ui_settings)