openvinotoolkit/stable-diffusion-webui
1
1
Fork 0
mirror of https://github.com/openvinotoolkit/stable-diffusion-webui.git synced 2024-12-14 22:53:25 +03:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #5521 from AndrewRyanChama/ryan/img2imglatentscale

Browse Source 
Add latent upscale option to img2img
This commit is contained in:
AUTOMATIC1111 2022-12-24 11:10:35 +03:00 committed by GitHub
commit b2dbd4d698
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 6 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
modules/processing.py
View File

@ -837,7 +837,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
for img in self.init_images:
image = images.flatten(img, opts.img2img_background_color)
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:
@ -846,6 +846,7 @@ 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)
@ -882,6 +883,9 @@ 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]))

2
modules/ui.py
View File

@ -857,7 +857,7 @@ def create_ui():
img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)
with gr.Row():
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")
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")
steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")