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Add latent upscale option to img2img
Recently, the option to do latent upscale was added to txt2img highres fix. This feature runs by scaling the latent sample of the image, and then running a second pass of img2img. But, in this edition of highres fix, the image and parameters cannot be changed between the first pass and second pass. We might want to do a fixup in img2img before doing the second pass, or might want to run the second pass at a different resolution. This change adds the option for img2img to perform its upscale in latent space, rather than image space, giving very similar results to highres fix with latent upscale. The result is not exactly the same because there is an additional latent -> decoder -> image -> encoder -> latent that won't happen in highres fix, but this conversion has relatively small losses
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@ -795,7 +795,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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for img in self.init_images:
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image = img.convert("RGB")
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if crop_region is None:
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if crop_region is None and self.resize_mode != 3:
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image = images.resize_image(self.resize_mode, image, self.width, self.height)
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if image_mask is not None:
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@ -804,6 +804,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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self.overlay_images.append(image_masked.convert('RGBA'))
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# crop_region is not none iif we are doing inpaint full res
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if crop_region is not None:
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image = image.crop(crop_region)
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image = images.resize_image(2, image, self.width, self.height)
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@ -840,6 +841,9 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image))
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if self.resize_mode == 3:
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self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
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if image_mask is not None:
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init_mask = latent_mask
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latmask = init_mask.convert('RGB').resize((self.init_latent.shape[3], self.init_latent.shape[2]))
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@ -829,7 +829,7 @@ def create_ui():
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img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)
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with gr.Row():
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resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
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resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill", "Upscale Latent Space"], type="index", value="Just resize")
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steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
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sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
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