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Update SD Upscaler to include user selectable Scale Factor

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This commit is contained in:
kaneda2004 2022-11-28 12:28:22 -08:00
parent 0202547696
commit 91226829f8
1 changed files with 6 additions and 11 deletions
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15
scripts/sd_upscale.py
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@ -17,12 +17,10 @@ class Script(scripts.Script):
return is_img2img
def ui(self, is_img2img):
info = gr.HTML(
"<p style=\"margin-bottom:0.75em\">Will upscale the image by the selected scale factor; use width and height sliders to set tile size</p>")
info = gr.HTML("<p style=\"margin-bottom:0.75em\">Will upscale the image by the selected scale factor; use width and height sliders to set tile size</p>")
overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64)
scale_factor = gr.Slider(minimum=0, maximum=4, step=1, label='Scale Factor', value=2)
upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers],
value=shared.sd_upscalers[0].name, type="index")
upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
return [info, overlap, upscaler_index, scale_factor]
@ -62,8 +60,7 @@ class Script(scripts.Script):
batch_count = math.ceil(len(work) / batch_size)
state.job_count = batch_count * upscale_count
print(
f"SD upscaling will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)} per upscale in a total of {state.job_count} batches.")
print(f"SD upscaling will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)} per upscale in a total of {state.job_count} batches.")
result_images = []
for n in range(upscale_count):
@ -87,16 +84,14 @@ class Script(scripts.Script):
image_index = 0
for y, h, row in grid.tiles:
for tiledata in row:
tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (
p.width, p.height))
tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height))
image_index += 1
combined_image = images.combine_grid(grid)
result_images.append(combined_image)
if opts.samples_save:
images.save_image(combined_image, p.outpath_samples, "", start_seed, p.prompt, opts.samples_format,
info=initial_info, p=p)
images.save_image(combined_image, p.outpath_samples, "", start_seed, p.prompt, opts.samples_format, info=initial_info, p=p)
processed = Processed(p, result_images, seed, initial_info)