Add upscaler to img2img

modules/generation_parameters_copypaste.py

@@ -282,8 +282,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
         res["Hires resize-1"] = 0
         res["Hires resize-2"] = 0
 
-    if "Img2Img Upscale" not in res:
+    if "Img2Img upscale" not in res:
-        res["Img2Img Upscale"] = 1
+        res["Img2Img upscale"] = 1
 
     restore_old_hires_fix_params(res)
 

modules/img2img.py

@@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, scale: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, scale: float, upscaler: str, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -150,6 +150,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         inpainting_mask_invert=inpainting_mask_invert,
         override_settings=override_settings,
         scale=scale,
+        upscaler=upscaler,
     )
 
     p.scripts = modules.scripts.scripts_txt2img

modules/processing.py

@@ -929,7 +929,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
     sampler = None
 
-    def __init__(self, init_images: Optional[list] = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: Optional[float] = None, mask: Any = None, mask_blur: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: Optional[float] = None, scale: float = 0, **kwargs):
+    def __init__(self, init_images: Optional[list] = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: Optional[float] = None, mask: Any = None, mask_blur: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: Optional[float] = None, scale: float = 0, upscaler: Optional[str] = None, **kwargs):
         super().__init__(**kwargs)
 
         self.init_images = init_images
@@ -950,6 +950,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         self.nmask = None
         self.image_conditioning = None
         self.scale = scale
+        self.upscaler = upscaler
 
     def get_final_size(self):
         if self.scale > 1:
@@ -966,7 +967,16 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         crop_region = None
 
         if self.scale > 1:
-            self.extra_generation_params["Img2Img Upscale"] = self.scale
+            self.extra_generation_params["Img2Img upscale"] = self.scale
+
+        # Non-latent upscalers are run before sampling
+        # Latent upscalers are run during sampling
+        init_upscaler = None
+        if self.upscaler is not None:
+            self.extra_generation_params["Img2Img upscaler"] = self.upscaler
+            if self.upscaler not in shared.latent_upscale_modes:
+                assert len([x for x in shared.sd_upscalers if x.name == self.upscaler]) > 0, f"could not find upscaler named {self.upscaler}"
+                init_upscaler = self.upscaler
 
         self.width, self.height = self.get_final_size()
 
@@ -992,7 +1002,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
                 image_mask = images.resize_image(2, mask, self.width, self.height)
                 self.paste_to = (x1, y1, x2-x1, y2-y1)
             else:
-                image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height)
+                image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height, init_upscaler)
                 np_mask = np.array(image_mask)
                 np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8)
                 self.mask_for_overlay = Image.fromarray(np_mask)
@@ -1009,7 +1019,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
             image = images.flatten(img, opts.img2img_background_color)
 
             if crop_region is None and self.resize_mode != 3:
-                image = images.resize_image(self.resize_mode, image, self.width, self.height)
+                image = images.resize_image(self.resize_mode, image, self.width, self.height, init_upscaler)
 
             if image_mask is not None:
                 image_masked = Image.new('RGBa', (image.width, image.height))
@@ -1054,8 +1064,9 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
 
         self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image))
 
-        if self.resize_mode == 3:
+        latent_scale_mode = shared.latent_upscale_modes.get(self.upscaler, None) if self.upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest")
-            self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
+        if latent_scale_mode is not None:
+            self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode=latent_scale_mode["mode"], antialias=latent_scale_mode["antialias"])
 
         if image_mask is not None:
             init_mask = latent_mask

modules/ui.py

@@ -767,7 +767,7 @@ def create_ui():
                     )
 
                 with FormRow():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
 
                 for category in ordered_ui_categories():
                     if category == "sampler":
@@ -797,7 +797,9 @@ def create_ui():
                             with FormRow():
                                 cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
                                 image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit")
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
+                            with FormRow():
+                                upscaler = gr.Dropdown(label="Upscaler", elem_id="img2img_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
 
                     elif category == "seed":
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
@@ -934,6 +936,7 @@ def create_ui():
                     height,
                     width,
                     scale,
+                    upscaler,
                     resize_mode,
                     inpaint_full_res,
                     inpaint_full_res_padding,
@@ -1019,7 +1022,8 @@ def create_ui():
                 (seed, "Seed"),
                 (width, "Size-1"),
                 (height, "Size-2"),
-                (scale, "Img2Img Upscale"),
+                (scale, "Img2Img upscale"),
+                (upscaler, "Img2Img upscaler"),
                 (batch_size, "Batch size"),
                 (subseed, "Variation seed"),
                 (subseed_strength, "Variation seed strength"),

scripts/xyz_grid.py

@@ -220,6 +220,7 @@ axis_options = [
     AxisOption("Clip skip", int, apply_clip_skip),
     AxisOption("Denoising", float, apply_field("denoising_strength")),
     AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
+    AxisOptionImg2Img("Upscaler", str, apply_field("upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
     AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")),
     AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)),
     AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)),

style.css

@@ -779,7 +779,7 @@ footer {
 #img2img_finalres{
     min-height: 0 !important;
     padding: .625rem .75rem;
-    margin-left: -0.75em
+    margin-left: 0.25em
 }
 
 #img2img_finalres .resolution{