import re import gradio as gr from PIL import Image, ImageFont, ImageDraw, ImageFilter, ImageOps from io import BytesIO import base64 import re def change_img_choices(sample_size): choices = [] for i in range(int(sample_size)): choices.append( '图片{}(img{})'.format(i+1,i+1) ) update_choices = gr.update(choices=choices) return update_choices def change_image_editor_mode(choice, cropped_image, masked_image, resize_mode, width, height): if choice == "Mask": update_image_result = update_image_mask(cropped_image, resize_mode, width, height) 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)] update_image_result = update_image_mask(masked_image["image"] if masked_image is not None else None, resize_mode, width, height) 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)] def update_image_mask(cropped_image, resize_mode, width, height): resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None return gr.update(value=resized_cropped_image, visible=True) def toggle_options_gfpgan(selection): if 0 in selection: return gr.update(visible=True) else: return gr.update(visible=False) def toggle_options_upscalers(selection): if 1 in selection: return gr.update(visible=True) else: return gr.update(visible=False) def toggle_options_realesrgan(selection): if selection == 0 or selection == 1 or selection == 3: return gr.update(visible=True) else: return gr.update(visible=False) def toggle_options_gobig(selection): if selection == 1: #print(selection) return gr.update(visible=True) if selection == 3: return gr.update(visible=True) else: return gr.update(visible=False) def toggle_options_ldsr(selection): if selection == 2 or selection == 3: return gr.update(visible=True) else: return gr.update(visible=False) def increment_down(value): return value - 1 def increment_up(value): return value + 1 def copy_img_to_lab(img): try: image_data = re.sub('^data:image/.+;base64,', '', img) processed_image = Image.open(BytesIO(base64.b64decode(image_data))) tab_update = gr.update(selected='imgproc_tab') img_update = gr.update(value=processed_image) return processed_image, tab_update, except IndexError: return [None, None] def copy_img_params_to_lab(params): try: prompt = params[0][0].replace('\n', ' ').replace('\r', '') seed = int(params[1][1]) steps = int(params[7][1]) cfg_scale = float(params[9][1]) sampler = params[11][1] return prompt,seed,steps,cfg_scale,sampler except IndexError: return [None, None] def copy_img_to_input(img, idx): try: # print(img) # print("=============") # print("The img type is:{}".format(type(img[0]))) idx_map = { "图片1(img1)":0, "图片2(img2)":1, "图片3(img3)":2, "图片4(img4)":3, } idx = idx_map[idx] assert img[idx]['is_file'] processed_image = Image.open(img[idx]['name']) tab_update = gr.update(selected='img2img_tab') move_prompt_zh_update = gr.update(visible=True) move_prompt_en_update = gr.update(visible=True) prompt_update = gr.update(visible=True) return tab_update, processed_image, move_prompt_zh_update, move_prompt_en_update, prompt_update except IndexError as e: raise gr.Error(e) return [None, None, None, None, None] def copy_img_to_edit(img): try: image_data = re.sub('^data:image/.+;base64,', '', img) processed_image = Image.open(BytesIO(base64.b64decode(image_data))) tab_update = gr.update(selected='img2img_tab') img_update = gr.update(value=processed_image) mode_update = gr.update(value='Crop') return processed_image, tab_update, mode_update except IndexError: return [None, None] def copy_img_to_mask(img): try: image_data = re.sub('^data:image/.+;base64,', '', img) processed_image = Image.open(BytesIO(base64.b64decode(image_data))) tab_update = gr.update(selected='img2img_tab') img_update = gr.update(value=processed_image) mode_update = gr.update(value='Mask') return processed_image, tab_update, mode_update except IndexError: return [None, None] def copy_img_to_upscale_esrgan(img): tabs_update = gr.update(selected='realesrgan_tab') image_data = re.sub('^data:image/.+;base64,', '', img) processed_image = Image.open(BytesIO(base64.b64decode(image_data))) return processed_image, tabs_update help_text = """ ## Mask/Crop * Masking is not inpainting. You will probably get better results manually masking your images in photoshop instead. * Built-in masking/cropping is very temperamental. * It may take some time for the image to show when switching from Crop to Mask. * If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask * If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask. ## Advanced Editor * Click 💾 Save to send your editor changes to the img2img workflow * Click ❌ Clear to discard your editor changes If anything breaks, try switching modes again, switch tabs, clear the image, or reload. """ def resize_image(resize_mode, im, width, height): LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) if resize_mode == 0: res = im.resize((width, height), resample=LANCZOS) elif resize_mode == 1: ratio = width / height src_ratio = im.width / im.height src_w = width if ratio > src_ratio else im.width * height // im.height src_h = height if ratio <= src_ratio else im.height * width // im.width resized = im.resize((src_w, src_h), resample=LANCZOS) res = Image.new("RGBA", (width, height)) res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2)) else: ratio = width / height src_ratio = im.width / im.height src_w = width if ratio < src_ratio else im.width * height // im.height src_h = height if ratio >= src_ratio else im.height * width // im.width resized = im.resize((src_w, src_h), resample=LANCZOS) res = Image.new("RGBA", (width, height)) res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2)) if ratio < src_ratio: fill_height = height // 2 - src_h // 2 res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0)) res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h)) elif ratio > src_ratio: fill_width = width // 2 - src_w // 2 res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0)) res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0)) return res def update_dimensions_info(width, height): pixel_count_formated = "{:,.0f}".format(width * height) return f"Aspect ratio: {round(width / height, 5)}\nTotal pixel count: {pixel_count_formated}" def get_png_nfo( image: Image ): info_text = "" visible = bool(image and any(image.info)) if visible: for key,value in image.info.items(): info_text += f"{key}: {value}\n" info_text = info_text.rstrip('\n') return gr.Textbox.update(value=info_text, visible=visible) def load_settings(*values): new_settings, key_names, checkboxgroup_info = values[-3:] values = list(values[:-3]) if new_settings: if type(new_settings) is str: if os.path.exists(new_settings): with open(new_settings, "r", encoding="utf8") as f: new_settings = yaml.safe_load(f) elif new_settings.startswith("file://") and os.path.exists(new_settings[7:]): with open(new_settings[7:], "r", encoding="utf8") as f: new_settings = yaml.safe_load(f) else: new_settings = yaml.safe_load(new_settings) if type(new_settings) is not dict: new_settings = {"prompt": new_settings} if "txt2img" in new_settings: new_settings = new_settings["txt2img"] target = new_settings.pop("target", "txt2img") if target != "txt2img": print(f"Warning: applying settings to txt2img even though {target} is specified as target.", file=sys.stderr) skipped_settings = {} for key in new_settings.keys(): if key in key_names: values[key_names.index(key)] = new_settings[key] else: skipped_settings[key] = new_settings[key] if skipped_settings: print(f"Settings could not be applied: {skipped_settings}", file=sys.stderr) # Convert lists of checkbox indices to lists of checkbox labels: for (cbg_index, cbg_choices) in checkboxgroup_info: values[cbg_index] = [cbg_choices[i] for i in values[cbg_index]] return values