mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
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f6aa2c64eb
* Add mask_restore option to give users the option to restore images based on mask, fixing #665. Before commitc73fdd78(Implement masking during sampling to improve blending, #308) image mask was applied after sampling, resulting in masked parts that are not regenerated to actually stay the same. Sincec73fdd78the masked img2img will change the whole image, even in masked areas. It gives better looking results at first glance, but will result in image degredation when applied a few times. See issue #665. In the workflow of using repeated masked img2img, users may want to use this options to keep the parts of image they actually want to keep without image degradation. A final masked img2img or whole image img2img with mask_restore disabled will give the better blending of "Implement masking during sampling". * revert changes ofa7be43bain change_image_editor_mode * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns * revert inserted newlines and whitespaces to match format of previous code * improve caption of new option mask_restore "Only modify regenerated parts of image" * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns an old copy of the function exists in webui.py, this superflous function mistakenly was changed by the earlier commitb6a9e16b* remove unused functions that are near duplicates of functions in ui_functions.py
220 lines
8.9 KiB
Python
220 lines
8.9 KiB
Python
import re
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import gradio as gr
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from PIL import Image, ImageFont, ImageDraw, ImageFilter, ImageOps
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from io import BytesIO
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import base64
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import re
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def change_image_editor_mode(choice, cropped_image, masked_image, resize_mode, width, height):
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if choice == "Mask":
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update_image_result = update_image_mask(cropped_image, resize_mode, width, height)
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return [gr.update(visible=False), update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)]
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update_image_result = update_image_mask(masked_image["image"] if masked_image is not None else None, resize_mode, width, height)
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return [update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)]
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def update_image_mask(cropped_image, resize_mode, width, height):
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resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None
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return gr.update(value=resized_cropped_image, visible=True)
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def toggle_options_gfpgan(selection):
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if 0 in selection:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def toggle_options_upscalers(selection):
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if 1 in selection:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def toggle_options_realesrgan(selection):
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if selection == 0 or selection == 1 or selection == 3:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def toggle_options_gobig(selection):
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if selection == 1:
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#print(selection)
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return gr.update(visible=True)
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if selection == 3:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def toggle_options_ldsr(selection):
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if selection == 2 or selection == 3:
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return gr.update(visible=True)
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else:
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return gr.update(visible=False)
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def increment_down(value):
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return value - 1
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def increment_up(value):
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return value + 1
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def copy_img_to_lab(img):
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try:
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image_data = re.sub('^data:image/.+;base64,', '', img)
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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tab_update = gr.update(selected='imgproc_tab')
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img_update = gr.update(value=processed_image)
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return processed_image, tab_update,
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except IndexError:
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return [None, None]
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def copy_img_params_to_lab(params):
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try:
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prompt = params[0][0].replace('\n', ' ').replace('\r', '')
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seed = int(params[1][1])
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steps = int(params[7][1])
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cfg_scale = float(params[9][1])
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sampler = params[11][1]
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return prompt,seed,steps,cfg_scale,sampler
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except IndexError:
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return [None, None]
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def copy_img_to_input(img):
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try:
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image_data = re.sub('^data:image/.+;base64,', '', img)
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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tab_update = gr.update(selected='img2img_tab')
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img_update = gr.update(value=processed_image)
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return processed_image, processed_image , tab_update
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except IndexError:
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return [None, None]
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def copy_img_to_edit(img):
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try:
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image_data = re.sub('^data:image/.+;base64,', '', img)
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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tab_update = gr.update(selected='img2img_tab')
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img_update = gr.update(value=processed_image)
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mode_update = gr.update(value='Crop')
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return processed_image, tab_update, mode_update
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except IndexError:
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return [None, None]
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def copy_img_to_mask(img):
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try:
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image_data = re.sub('^data:image/.+;base64,', '', img)
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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tab_update = gr.update(selected='img2img_tab')
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img_update = gr.update(value=processed_image)
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mode_update = gr.update(value='Mask')
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return processed_image, tab_update, mode_update
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except IndexError:
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return [None, None]
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def copy_img_to_upscale_esrgan(img):
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tabs_update = gr.update(selected='realesrgan_tab')
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image_data = re.sub('^data:image/.+;base64,', '', img)
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processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
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return processed_image, tabs_update
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help_text = """
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## Mask/Crop
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* Masking is not inpainting. You will probably get better results manually masking your images in photoshop instead.
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* Built-in masking/cropping is very temperamental.
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* It may take some time for the image to show when switching from Crop to Mask.
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* If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask
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* If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask.
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## Advanced Editor
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* Click 💾 Save to send your editor changes to the img2img workflow
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* Click ❌ Clear to discard your editor changes
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If anything breaks, try switching modes again, switch tabs, clear the image, or reload.
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"""
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def resize_image(resize_mode, im, width, height):
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LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
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if resize_mode == 0:
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res = im.resize((width, height), resample=LANCZOS)
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elif resize_mode == 1:
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ratio = width / height
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src_ratio = im.width / im.height
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src_w = width if ratio > src_ratio else im.width * height // im.height
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src_h = height if ratio <= src_ratio else im.height * width // im.width
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resized = im.resize((src_w, src_h), resample=LANCZOS)
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res = Image.new("RGBA", (width, height))
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res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
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else:
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ratio = width / height
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src_ratio = im.width / im.height
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src_w = width if ratio < src_ratio else im.width * height // im.height
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src_h = height if ratio >= src_ratio else im.height * width // im.width
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resized = im.resize((src_w, src_h), resample=LANCZOS)
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res = Image.new("RGBA", (width, height))
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res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
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if ratio < src_ratio:
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fill_height = height // 2 - src_h // 2
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res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0))
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res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h))
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elif ratio > src_ratio:
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fill_width = width // 2 - src_w // 2
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res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0))
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res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0))
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return res
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def update_dimensions_info(width, height):
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pixel_count_formated = "{:,.0f}".format(width * height)
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return f"Aspect ratio: {round(width / height, 5)}\nTotal pixel count: {pixel_count_formated}"
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def get_png_nfo( image: Image ):
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info_text = ""
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visible = bool(image and any(image.info))
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if visible:
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for key,value in image.info.items():
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info_text += f"{key}: {value}\n"
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info_text = info_text.rstrip('\n')
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return gr.Textbox.update(value=info_text, visible=visible)
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def load_settings(*values):
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new_settings, key_names, checkboxgroup_info = values[-3:]
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values = list(values[:-3])
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if new_settings:
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if type(new_settings) is str:
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if os.path.exists(new_settings):
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with open(new_settings, "r", encoding="utf8") as f:
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new_settings = yaml.safe_load(f)
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elif new_settings.startswith("file://") and os.path.exists(new_settings[7:]):
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with open(new_settings[7:], "r", encoding="utf8") as f:
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new_settings = yaml.safe_load(f)
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else:
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new_settings = yaml.safe_load(new_settings)
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if type(new_settings) is not dict:
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new_settings = {"prompt": new_settings}
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if "txt2img" in new_settings:
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new_settings = new_settings["txt2img"]
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target = new_settings.pop("target", "txt2img")
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if target != "txt2img":
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print(f"Warning: applying settings to txt2img even though {target} is specified as target.", file=sys.stderr)
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skipped_settings = {}
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for key in new_settings.keys():
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if key in key_names:
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values[key_names.index(key)] = new_settings[key]
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else:
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skipped_settings[key] = new_settings[key]
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if skipped_settings:
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print(f"Settings could not be applied: {skipped_settings}", file=sys.stderr)
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# Convert lists of checkbox indices to lists of checkbox labels:
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for (cbg_index, cbg_choices) in checkboxgroup_info:
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values[cbg_index] = [cbg_choices[i] for i in values[cbg_index]]
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return values
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