import gradio as gr from model import models from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery, change_model, warm_model, get_model_info_md, loaded_models, warm_models, get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix, get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en) from tagger.tagger import (predict_tags_wd, remove_specific_prompt, convert_danbooru_to_e621_prompt, insert_recom_prompt, compose_prompt_to_copy) from tagger.fl2sd3longcap import predict_tags_fl2_sd3 from tagger.v2 import V2_ALL_MODELS, v2_random_prompt from tagger.utils import (V2_ASPECT_RATIO_OPTIONS, V2_RATING_OPTIONS, V2_LENGTH_OPTIONS, V2_IDENTITY_OPTIONS) max_images = 6 MAX_SEED = 2**32-1 load_models(models) warm_models(models[0:max_images]) css = """ .title { font-size: 3em; align-items: center; text-align: center; } .info { align-items: center; text-align: center; } .model_info { text-align: center; } .output { width=112px; height=112px; max_width=112px; max_height=112px; !important; } .gallery { min_width=512px; min_height=512px; max_height=1024px; !important; } :root .dark { --body-background-fill:none!important;} """ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo: with gr.Tab(""): with gr.Row(): with gr.Column(scale=10): with gr.Group(): model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True) model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info") prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True) with gr.Accordion("Advanced options", open=False): neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="") v2_rating = gr.Radio(label="Rating", choices=list(V2_RATING_OPTIONS), value="explicit") v2_aspect_ratio = gr.Radio(label="Aspect ratio", info="The aspect ratio of the image.", choices=list(V2_ASPECT_RATIO_OPTIONS), value="square", visible=False) with gr.Row(equal_height=True): width = gr.Slider(label="Width", maximum=1216, step=32, value=0) height = gr.Slider(label="Height", maximum=1216, step=32, value=0) steps = gr.Slider(label="Number of inference steps", maximum=100, step=1, value=0) with gr.Row(equal_height=True): cfg = gr.Slider(label="Guidance scale", maximum=30.0, step=0.1, value=0) seed = gr.Slider(label="Seed", minimum=-1, maximum=MAX_SEED, step=1, value=-1) seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary") recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common") with gr.Row(equal_height=True): positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[]) positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"]) negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[]) negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"]) with gr.Row(equal_height=True): image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2) run_button = gr.Button("Generate Image", variant="primary", scale=3) random_button = gr.Button("Random Model 🎲", variant="secondary", scale=2) stop_button = gr.Button('Stop', variant="stop", interactive=False, scale=1) #with gr.Row(equal_height=True): with gr.Column(scale=10): with gr.Group(): with gr.Row(): output = [gr.Image(label='', elem_classes="output", type="filepath", format="png", show_download_button=True, show_share_button=False, show_label=False, interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)] with gr.Group(): results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False, container=True, format="png", object_fit="cover", columns=2, rows=2) image_files = gr.Files(label="Download", interactive=False) clear_results = gr.Button("Clear Gallery / Download 🗑️", variant="secondary") #gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False) model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\ .success(warm_model, [model_name], None, queue=False, show_api=False) for i, o in enumerate(output): img_i = gr.Number(i, visible=False) image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False) gen_event = gr.on(triggers=[run_button.click, prompt.submit], fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None, inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed, positive_prefix, positive_suffix, negative_prefix, negative_suffix], outputs=[o], queue=False, show_api=False) # Be sure to delete ", queue=False" when activating the stop button gen_event2 = gr.on(triggers=[random_button.click], fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None, inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed, positive_prefix, positive_suffix, negative_prefix, negative_suffix], outputs=[o], queue=False, show_api=False) # Be sure to delete ", queue=False" when activating the stop button o.change(save_gallery, [o, results], [results, image_files], show_api=False) #stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False) recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset], [positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False) seed_rand.click(randomize_seed, None, [seed], queue=False, show_api=False) #demo.queue(default_concurrency_limit=200, max_size=200) demo.launch(max_threads=400, ssr_mode=False)