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

1 files changed, 5 insertions, 1 deletions

diff --git a/modules/processing.py b/modules/processing.py
index 3d2c4dc9..ab5a34d0 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -795,7 +795,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         for img in self.init_images:

             image = img.convert("RGB")

 

-            if crop_region is None:

+            if crop_region is None and self.resize_mode != 3:

                 image = images.resize_image(self.resize_mode, image, self.width, self.height)

 

             if image_mask is not None:

@@ -804,6 +804,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
 

                 self.overlay_images.append(image_masked.convert('RGBA'))

 

+            # crop_region is not none iif we are doing inpaint full res

             if crop_region is not None:

                 image = image.crop(crop_region)

                 image = images.resize_image(2, image, self.width, self.height)

@@ -840,6 +841,9 @@ 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:

+            self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")

+

         if image_mask is not None:

             init_mask = latent_mask

             latmask = init_mask.convert('RGB').resize((self.init_latent.shape[3], self.init_latent.shape[2]))