import base64 import html import io import json import mimetypes import os import sys import time import traceback from PIL import Image import gradio as gr import gradio.utils from modules.paths import script_path from modules.shared import opts, cmd_opts import modules.shared as shared from modules.sd_samplers import samplers, samplers_for_img2img import modules.gfpgan_model as gfpgan import modules.realesrgan_model as realesrgan # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI mimetypes.init() mimetypes.add_type('application/javascript', '.js') if not cmd_opts.share: # fix gradio phoning home gradio.utils.version_check = lambda: None gradio.utils.get_local_ip_address = lambda: '127.0.0.1' def gr_show(visible=True): return {"visible": visible, "__type__": "update"} sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg" sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None css_hide_progressbar = """ .wrap .m-12 svg { display:none!important; } .wrap .m-12::before { content:"Loading..." } .progress-bar { display:none!important; } .meta-text { display:none!important; } """ def plaintext_to_html(text): text = "".join([f"
{html.escape(x)}
\n" for x in text.split('\n')]) return text def image_from_url_text(filedata): if type(filedata) == list: if len(filedata) == 0: return None filedata = filedata[0] if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] filedata = base64.decodebytes(filedata.encode('utf-8')) image = Image.open(io.BytesIO(filedata)) return image def send_gradio_gallery_to_image(x): if len(x) == 0: return None return image_from_url_text(x[0]) def save_files(js_data, images): import csv os.makedirs(opts.outdir_save, exist_ok=True) filenames = [] data = json.loads(js_data) with open("log/log.csv", "a", encoding="utf8", newline='') as file: at_start = file.tell() == 0 writer = csv.writer(file) if at_start: writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename"]) filename_base = str(int(time.time() * 1000)) for i, filedata in enumerate(images): filename = filename_base + ("" if len(images) == 1 else "-" + str(i + 1)) + ".png" filepath = os.path.join(opts.outdir_save, filename) if filedata.startswith("data:image/png;base64,"): filedata = filedata[len("data:image/png;base64,"):] with open(filepath, "wb") as imgfile: imgfile.write(base64.decodebytes(filedata.encode('utf-8'))) filenames.append(filename) writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0]]) return '', '', plaintext_to_html(f"Saved: {filenames[0]}") def wrap_gradio_call(func): def f(*args, **kwargs): t = time.perf_counter() try: res = list(func(*args, **kwargs)) except Exception as e: print("Error completing request", file=sys.stderr) print("Arguments:", args, kwargs, file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) res = [None, '', f"Time taken: {elapsed:.2f}s
" shared.state.interrupted = False return tuple(res) return f def create_ui(opts, cmd_opts, txt2img, img2img, run_extras, run_pnginfo): with gr.Blocks(analytics_enabled=False) as txt2img_interface: with gr.Row(): prompt = gr.Textbox(label="Prompt", elem_id="txt2img_prompt", show_label=False, placeholder="Prompt", lines=1) negative_prompt = gr.Textbox(label="Negative prompt", elem_id="txt2img_negative_prompt", show_label=False, placeholder="Negative prompt", lines=1, visible=False) submit = gr.Button('Generate', elem_id="txt2img_generate", variant='primary') with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20) sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index") with gr.Row(): use_GFPGAN = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan) prompt_matrix = gr.Checkbox(label='Prompt matrix', value=False) with gr.Row(): batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1) batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1) cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0) with gr.Group(): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) seed = gr.Number(label='Seed', value=-1) code = gr.Textbox(label="Python script", visible=cmd_opts.allow_code, lines=1) with gr.Column(variant='panel'): with gr.Group(): txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery') with gr.Group(): with gr.Row(): save = gr.Button('Save') send_to_img2img = gr.Button('Send to img2img') send_to_inpaint = gr.Button('Send to inpaint') send_to_extras = gr.Button('Send to extras') interrupt = gr.Button('Interrupt') with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) txt2img_args = dict( fn=txt2img, inputs=[ prompt, negative_prompt, steps, sampler_index, use_GFPGAN, prompt_matrix, batch_count, batch_size, cfg_scale, seed, height, width, code ], outputs=[ txt2img_gallery, generation_info, html_info ] ) prompt.submit(**txt2img_args) submit.click(**txt2img_args) interrupt.click( fn=lambda: shared.state.interrupt(), inputs=[], outputs=[], ) save.click( fn=wrap_gradio_call(save_files), inputs=[ generation_info, txt2img_gallery, ], outputs=[ html_info, html_info, html_info, ] ) with gr.Blocks(analytics_enabled=False) as img2img_interface: with gr.Row(): prompt = gr.Textbox(label="Prompt", elem_id="img2img_prompt", show_label=False, placeholder="Prompt", lines=1) submit = gr.Button('Generate', elem_id="img2img_generate", variant='primary') with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): with gr.Group(): switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'Loopback', 'SD upscale'], value='Redraw whole image', type="index", show_label=False) init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil") init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False) resize_mode = gr.Radio(label="Resize mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize") steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20) sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index") mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False) inpainting_fill = gr.Radio(label='Msked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False) with gr.Row(): use_GFPGAN = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan) prompt_matrix = gr.Checkbox(label='Prompt matrix', value=False) inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=True, visible=False) with gr.Row(): sd_upscale_upscaler_name = gr.Radio(label='Upscaler', choices=list(shared.sd_upscalers.keys()), value=list(shared.sd_upscalers.keys())[0], visible=False) sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False) with gr.Row(): batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1) batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1) with gr.Group(): cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0) denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength', value=0.75) with gr.Group(): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) seed = gr.Number(label='Seed', value=-1) with gr.Column(variant='panel'): with gr.Group(): img2img_gallery = gr.Gallery(label='Output', elem_id='img2img_gallery') with gr.Group(): with gr.Row(): interrupt = gr.Button('Interrupt') save = gr.Button('Save') img2img_send_to_extras = gr.Button('Send to extras') with gr.Group(): html_info = gr.HTML() generation_info = gr.Textbox(visible=False) def apply_mode(mode): is_classic = mode == 0 is_inpaint = mode == 1 is_loopback = mode == 2 is_upscale = mode == 3 return { init_img: gr_show(not is_inpaint), init_img_with_mask: gr_show(is_inpaint), mask_blur: gr_show(is_inpaint), inpainting_fill: gr_show(is_inpaint), prompt_matrix: gr_show(is_classic), batch_count: gr_show(not is_upscale), batch_size: gr_show(not is_loopback), sd_upscale_upscaler_name: gr_show(is_upscale), sd_upscale_overlap:gr_show(is_upscale), inpaint_full_res: gr_show(is_inpaint), } switch_mode.change( apply_mode, inputs=[switch_mode], outputs=[ init_img, init_img_with_mask, mask_blur, inpainting_fill, prompt_matrix, batch_count, batch_size, sd_upscale_upscaler_name, sd_upscale_overlap, inpaint_full_res, ] ) img2img_args = dict( fn=img2img, inputs=[ prompt, init_img, init_img_with_mask, steps, sampler_index, mask_blur, inpainting_fill, use_GFPGAN, prompt_matrix, switch_mode, batch_count, batch_size, cfg_scale, denoising_strength, seed, height, width, resize_mode, sd_upscale_upscaler_name, sd_upscale_overlap, inpaint_full_res, ], outputs=[ img2img_gallery, generation_info, html_info ] ) prompt.submit(**img2img_args) submit.click(**img2img_args) interrupt.click( fn=lambda: shared.state.interrupt(), inputs=[], outputs=[], ) save.click( fn=wrap_gradio_call(save_files), inputs=[ generation_info, img2img_gallery, ], outputs=[ html_info, html_info, html_info, ] ) send_to_img2img.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery", inputs=[txt2img_gallery], outputs=[init_img], ) send_to_inpaint.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery", inputs=[txt2img_gallery], outputs=[init_img_with_mask], ) with gr.Blocks(analytics_enabled=False) as extras_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): with gr.Group(): image = gr.Image(label="Source", source="upload", interactive=True, type="pil") gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN strength", value=1, interactive=gfpgan.have_gfpgan) realesrgan_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Real-ESRGAN upscaling", value=2, interactive=realesrgan.have_realesrgan) realesrgan_model = gr.Radio(label='Real-ESRGAN model', choices=[x.name for x in realesrgan.realesrgan_models], value=realesrgan.realesrgan_models[0].name, type="index", interactive=realesrgan.have_realesrgan) submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') with gr.Column(variant='panel'): result_image = gr.Image(label="Result") html_info_x = gr.HTML() html_info = gr.HTML() extras_args = dict( fn=run_extras, inputs=[ image, gfpgan_strength, realesrgan_resize, realesrgan_model, ], outputs=[ result_image, html_info_x, html_info, ] ) submit.click(**extras_args) send_to_extras.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery", inputs=[txt2img_gallery], outputs=[image], ) img2img_send_to_extras.click( fn=lambda x: image_from_url_text(x), _js="extract_image_from_gallery", inputs=[img2img_gallery], outputs=[image], ) pnginfo_interface = gr.Interface( wrap_gradio_call(run_pnginfo), inputs=[ gr.Image(label="Source", source="upload", interactive=True, type="pil"), ], outputs=[ gr.HTML(), gr.HTML(), gr.HTML(), ], allow_flagging="never", analytics_enabled=False, ) def create_setting_component(key): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default info = opts.data_labels[key] t = type(info.default) if info.component is not None: item = info.component(label=info.label, value=fun, **(info.component_args or {})) elif t == str: item = gr.Textbox(label=info.label, value=fun, lines=1) elif t == int: item = gr.Number(label=info.label, value=fun) elif t == bool: item = gr.Checkbox(label=info.label, value=fun) else: raise Exception(f'bad options item type: {str(t)} for key {key}') return item def run_settings(*args): up = [] for key, value, comp in zip(opts.data_labels.keys(), args, settings_interface.input_components): opts.data[key] = value up.append(comp.update(value=value)) opts.save(shared.config_filename) return 'Settings saved.', '', '' settings_interface = gr.Interface( run_settings, inputs=[create_setting_component(key) for key in opts.data_labels.keys()], outputs=[ gr.Textbox(label='Result'), gr.HTML(), gr.HTML(), ], title=None, description=None, allow_flagging="never", analytics_enabled=False, ) interfaces = [ (txt2img_interface, "txt2img"), (img2img_interface, "img2img"), (extras_interface, "Extras"), (pnginfo_interface, "PNG Info"), (settings_interface, "Settings"), ] with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: css = file.read() if not cmd_opts.no_progressbar_hiding: css += css_hide_progressbar demo = gr.TabbedInterface( interface_list=[x[0] for x in interfaces], tab_names=[x[1] for x in interfaces], analytics_enabled=False, css=css, ) return demo with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as file: javascript = file.read() def inject_gradio_html(javascript): import gradio.routes def template_response(*args, **kwargs): res = gradio_routes_templates_response(*args, **kwargs) res.body = res.body.replace(b'', f''.encode("utf8")) res.init_headers() return res gradio_routes_templates_response = gradio.routes.templates.TemplateResponse gradio.routes.templates.TemplateResponse = template_response inject_gradio_html(javascript)