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https://github.com/Coyote-A/ultimate-upscale-for-automatic1111.git
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86a9ec00f9
Resolve "Fix upscale factor" Closes #4 See merge request mirzam/ultimate-upscale-for-automatic1111!7
210 lines
8.2 KiB
Python
210 lines
8.2 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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def getFactor(num):
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if num == 1:
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return 2
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if num % 4 == 0:
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return 4
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if num % 3 == 0:
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return 3
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if num % 2 == 0:
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return 2
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return 0
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def upscale(p, init_img, upscaler_index, tileSize, padding):
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scale_factor = max(p.width, p.height) // max(init_img.width, init_img.height)
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print(f"Canva size: {p.width}x{p.height}")
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print(f"Image size: {init_img.width}x{init_img.height}")
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print(f"Scale factor: {scale_factor}")
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upscaler = shared.sd_upscalers[upscaler_index]
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p.extra_generation_params["SD upscale overlap"] = padding
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p.extra_generation_params["SD upscale upscaler"] = upscaler.name
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initial_info = None
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seed = p.seed
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upscaled_img = init_img
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if upscaler.name == "None":
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return upscaled_img.resize((p.width, p.height), resample=Image.LANCZOS)
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current_scale = 1
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iteration = 0
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current_scale_factor = getFactor(scale_factor)
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while current_scale_factor == 0:
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scale_factor += 1
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current_scale_factor = getFactor(scale_factor)
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while current_scale < scale_factor:
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iteration += 1
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current_scale_factor = getFactor(scale_factor // current_scale)
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current_scale = current_scale * current_scale_factor
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if current_scale_factor == 0:
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break
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print(f"Upscaling iteration {iteration} with scale factor {current_scale_factor}")
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upscaled_img = upscaler.scaler.upscale(upscaled_img, current_scale_factor, upscaler.data_path)
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return upscaled_img.resize((p.width, p.height), resample=Image.LANCZOS)
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def redraw_image(p, upscaled_img, rows, cols, tileSize, padding):
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initial_info = None
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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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return upscaled_img, initial_info
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def seam_draw(p, upscaled_img, seam_pass_width, seam_pass_padding, seam_pass_denoise, padding, tileSize, cols, rows):
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p.denoising_strength = seam_pass_denoise
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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 = seam_pass_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 = seam_pass_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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return upscaled_img
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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(
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"<p style=\"margin-bottom:0.75em\">Will upscale the image to selected with and height</p>")
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gr.HTML("<p style=\"margin-bottom:0.75em\">Redraw options:</p>")
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with gr.Row():
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redraw_enabled = gr.Checkbox(label="Enabled", value=True)
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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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upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers],
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value=shared.sd_upscalers[0].name, type="index")
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gr.HTML("<p style=\"margin-bottom:0.75em\">Tile grid fix:</p>")
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with gr.Row():
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seam_pass_enabled = gr.Checkbox(label="Enabled")
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seam_pass_width = gr.Slider(label='Width', minimum=0, maximum=128, step=1, value=16)
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seam_pass_denoise = gr.Slider(label='Denoise', minimum=0, maximum=1, step=0.01, value=0.25)
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seam_pass_padding = gr.Slider(label='Padding', minimum=0, maximum=128, step=1, value=32)
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gr.HTML("<p style=\"margin-bottom:0.75em\">Save options:</p>")
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with gr.Row():
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save_upscaled_image = gr.Checkbox(label="Upscaled", value=True)
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save_seam_path_image = gr.Checkbox(label="Seam path", value=True)
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return [info, tileSize, mask_blur, padding, seam_pass_enabled, seam_pass_width, seam_pass_denoise,
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seam_pass_padding, upscaler_index, save_upscaled_image, save_seam_path_image, redraw_enabled]
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def run(self, p, _, tileSize, mask_blur, padding, seam_pass_enabled, seam_pass_width, seam_pass_denoise,
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seam_pass_padding, upscaler_index, save_upscaled_image, save_seam_path_image, redraw_enabled):
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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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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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# Upscaling
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upscaled_img = upscale(p, init_img, upscaler_index, tileSize, padding)
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# Drawing
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devices.torch_gc()
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p.do_not_save_grid = True
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p.do_not_save_samples = True
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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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print(f"Tiles amount: {rows * cols}")
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print(f"Grid: {rows}x{cols}")
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print(f"Seam path: {seam_pass_enabled}")
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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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state.job_count = ((rows*cols) if redraw_enabled else 0) + (seams if seam_pass_enabled else 0)
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result_images = []
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result_image = upscaled_img
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if redraw_enabled:
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result_image, initial_info = redraw_image(p, upscaled_img, rows, cols, tileSize, padding)
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result_images.append(result_image)
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if save_upscaled_image:
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images.save_image(result_image, p.outpath_samples, "", seed, p.prompt, opts.grid_format, info=initial_info, p=p)
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if seam_pass_enabled:
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print(f"Starting seam path drawing")
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result_image = seam_draw(p, result_image, seam_pass_width, seam_pass_padding, seam_pass_denoise, padding, tileSize, cols, rows)
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result_images.append(result_image)
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if save_seam_path_image:
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images.save_image(result_image, p.outpath_samples, "", seed, p.prompt, opts.grid_format, info=initial_info, p=p)
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processed = Processed(p, result_images, seed, initial_info)
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return processed
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