mirror of
https://github.com/Coyote-A/ultimate-upscale-for-automatic1111.git
synced 2026-03-04 21:09:57 +00:00
126 lines
4.9 KiB
Python
126 lines
4.9 KiB
Python
import math
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import modules.scripts as scripts
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import gradio as gr
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from PIL import Image, ImageDraw
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from modules import processing, shared, sd_samplers, images, devices
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from modules.processing import Processed
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from modules.shared import opts, cmd_opts, state
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class Script(scripts.Script):
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def title(self):
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return "Ultimate SD upscale"
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def show(self, is_img2img):
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return is_img2img
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def ui(self, is_img2img):
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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>")
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tileSize = gr.Slider(minimum=256, maximum=2048, step=64, label='Tile size', value=512)
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mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8)
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padding = gr.Slider(label='Padding', minimum=0, maximum=128, step=1, value=32)
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seam_pass_enabled = gr.Checkbox(label= "Seam pass enabled")
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seam_pass_width = gr.Slider(label='Seam pass width', minimum=0, maximum=128, step=1, value=16)
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seam_pass_denoise = gr.Slider(label='Seam pass denoise', minimum=0, maximum=1, step=0.01, value=0.25)
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seam_pass_padding = gr.Slider(label='Seam pass padding', minimum=0, maximum=128, step=1, value=32)
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return [info, tileSize, mask_blur, padding, seam_pass_enabled, seam_pass_width, seam_pass_denoise, seam_pass_padding]
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def run(self, p, _, tileSize, mask_blur, padding, seam_pass_enabled, seam_pass_width, seam_pass_denoise, seam_pass_padding):
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processing.fix_seed(p)
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p.extra_generation_params["SD upscale tileSize"] = tileSize
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p.mask_blur = mask_blur
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initial_info = None
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seed = p.seed
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init_img = p.init_images[0]
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init_img = images.flatten(init_img, opts.img2img_background_color)
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upscaled_img = init_img.resize((p.width, p.height), resample=Image.LANCZOS)
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devices.torch_gc()
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p.inpaint_full_res = False
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rows = math.ceil(p.height / tileSize)
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cols = math.ceil(p.width / tileSize)
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seams = 0
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if seam_pass_enabled:
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seams = rows-1 + cols - 1
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result_images = []
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state.job_count = rows*cols + seams
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for yi in range(rows):
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for xi in range(cols):
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p.width = tileSize
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p.height = tileSize
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p.inpaint_full_res = True
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p.inpaint_full_res_padding = padding
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mask = Image.new("L", (upscaled_img.width, upscaled_img.height), "black")
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draw = ImageDraw.Draw(mask)
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draw.rectangle((
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xi * tileSize,
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yi * tileSize,
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xi * tileSize + tileSize,
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yi * tileSize + tileSize
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), fill="white")
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p.init_images = [upscaled_img]
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p.image_mask = mask
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processed = processing.process_images(p)
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initial_info = processed.info
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if (len(processed.images)>0):
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upscaled_img = processed.images[0]
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result_images.append(upscaled_img)
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if seam_pass_enabled:
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for xi in range(1, cols):
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p.width = seam_pass_width + seam_pass_padding*2
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p.height = upscaled_img.height
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p.inpaint_full_res = True
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p.inpaint_full_res_padding = padding
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mask = Image.new("L", (upscaled_img.width, upscaled_img.height), "black")
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draw = ImageDraw.Draw(mask)
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draw.rectangle((
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xi * tileSize - seam_pass_width//2,
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0,
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xi * tileSize + seam_pass_width//2,
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mask.height
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), fill="white")
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p.init_images = [upscaled_img]
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p.image_mask = mask
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processed = processing.process_images(p)
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if (len(processed.images) > 0):
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upscaled_img = processed.images[0]
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for yi in range(1, rows):
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p.width = upscaled_img.width
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p.height = seam_pass_width + seam_pass_padding*2
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p.inpaint_full_res = True
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p.inpaint_full_res_padding = padding
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mask = Image.new("L", (upscaled_img.width, upscaled_img.height), "black")
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draw = ImageDraw.Draw(mask)
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draw.rectangle((
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0,
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yi * tileSize - seam_pass_width//2,
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mask.width,
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yi * tileSize + seam_pass_width//2
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), fill="white")
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p.init_images = [upscaled_img]
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p.image_mask = mask
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processed = processing.process_images(p)
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if (len(processed.images) > 0):
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upscaled_img = processed.images[0]
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result_images.append(upscaled_img)
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processed = Processed(p, result_images, seed, initial_info)
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return processed
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