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| 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, | |
| get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix, | |
| get_recom_prompt_type, set_recom_prompt_preset, get_tag_type) | |
| 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) | |
| css = """ | |
| .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; } | |
| """ | |
| with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=10): | |
| with gr.Group(): | |
| with gr.Accordion("Prompt from Image File", open=False): | |
| tagger_image = gr.Image(label="Input image", type="pil", sources=["upload", "clipboard"], height=256) | |
| with gr.Accordion(label="Advanced options", open=False): | |
| with gr.Row(): | |
| tagger_general_threshold = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.01, interactive=True) | |
| tagger_character_threshold = gr.Slider(label="Character threshold", minimum=0.0, maximum=1.0, value=0.8, step=0.01, interactive=True) | |
| tagger_tag_type = gr.Radio(label="Convert tags to", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru") | |
| with gr.Row(): | |
| tagger_recom_prompt = gr.Radio(label="Insert reccomended prompt", choices=["None", "Animagine", "Pony"], value="None", interactive=True) | |
| tagger_keep_tags = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all") | |
| tagger_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner"], label="Algorithms", value=["Use WD Tagger"]) | |
| tagger_generate_from_image = gr.Button(value="Generate Tags from Image", variant="secondary") | |
| with gr.Accordion("Prompt Transformer", open=False): | |
| with gr.Row(): | |
| v2_rating = gr.Radio(label="Rating", choices=list(V2_RATING_OPTIONS), value="sfw") | |
| 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) | |
| v2_length = gr.Radio(label="Length", info="The total length of the tags.", choices=list(V2_LENGTH_OPTIONS), value="long") | |
| with gr.Row(): | |
| v2_identity = gr.Radio(label="Keep identity", info="How strictly to keep the identity of the character or subject. If you specify the detail of subject in the prompt, you should choose `strict`. Otherwise, choose `none` or `lax`. `none` is very creative but sometimes ignores the input prompt.", choices=list(V2_IDENTITY_OPTIONS), value="lax") | |
| v2_ban_tags = gr.Textbox(label="Ban tags", info="Tags to ban from the output.", placeholder="alternate costumen, ...", value="censored") | |
| v2_tag_type = gr.Radio(label="Tag Type", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru", visible=False) | |
| v2_model = gr.Dropdown(label="Model", choices=list(V2_ALL_MODELS.keys()), value=list(V2_ALL_MODELS.keys())[0]) | |
| v2_copy = gr.Button(value="Copy to clipboard", variant="secondary", size="sm", interactive=False) | |
| with gr.Row(): | |
| v2_character = gr.Textbox(label="Character", placeholder="hatsune miku", scale=2) | |
| v2_series = gr.Textbox(label="Series", placeholder="vocaloid", scale=2) | |
| random_prompt = gr.Button(value="Extend Prompt 🎲", variant="secondary", size="sm", scale=1) | |
| clear_prompt = gr.Button(value="Clear Prompt 🗑️", variant="secondary", size="sm", scale=1) | |
| 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="") | |
| with gr.Row(): | |
| width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0) | |
| height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0) | |
| with gr.Row(): | |
| steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0) | |
| cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0) | |
| seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1) | |
| recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common") | |
| with gr.Row(): | |
| 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"]) | |
| image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=1) | |
| with gr.Row(): | |
| run_button = gr.Button("Generate Image", variant="primary", scale=6) | |
| random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3) | |
| stop_button = gr.Button('Stop', variant="stop", interactive=False, scale=1) | |
| 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") | |
| 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) 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") | |
| with gr.Column(): | |
| examples = gr.Examples( | |
| examples = [ | |
| ["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"], | |
| ["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"], | |
| ["kafuu chino, 1girl, solo"], | |
| ["1girl"], | |
| ["beautiful sunset"], | |
| ], | |
| inputs=[prompt], | |
| ) | |
| gr.Markdown( | |
| f"""This demo was created in reference to the following demos.<br> | |
| [Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood), | |
| [Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL), | |
| [Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX). | |
| """ | |
| ) | |
| gr.DuplicateButton(value="Duplicate Space") | |
| gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.") | |
| 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=True, 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=True, show_api=False) | |
| 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=True, show_api=False) | |
| 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) | |
| clear_prompt.click(lambda: None, None, [prompt], queue=False, show_api=False) | |
| clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, 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) | |
| random_prompt.click( | |
| v2_random_prompt, [prompt, v2_series, v2_character, v2_rating, v2_aspect_ratio, v2_length, | |
| v2_identity, v2_ban_tags, v2_model], [prompt, v2_series, v2_character], show_api=False, | |
| ).success(get_tag_type, [positive_prefix, positive_suffix, negative_prefix, negative_suffix], [v2_tag_type], queue=False, show_api=False | |
| ).success(convert_danbooru_to_e621_prompt, [prompt, v2_tag_type], [prompt], queue=False, show_api=False) | |
| tagger_generate_from_image.click(lambda: ("", "", ""), None, [v2_series, v2_character, prompt], queue=False, show_api=False, | |
| ).success( | |
| predict_tags_wd, | |
| [tagger_image, prompt, tagger_algorithms, tagger_general_threshold, tagger_character_threshold], | |
| [v2_series, v2_character, prompt, v2_copy], | |
| show_api=False, | |
| ).success(predict_tags_fl2_sd3, [tagger_image, prompt, tagger_algorithms], [prompt], show_api=False, | |
| ).success(remove_specific_prompt, [prompt, tagger_keep_tags], [prompt], queue=False, show_api=False, | |
| ).success(convert_danbooru_to_e621_prompt, [prompt, tagger_tag_type], [prompt], queue=False, show_api=False, | |
| ).success(insert_recom_prompt, [prompt, neg_prompt, tagger_recom_prompt], [prompt, neg_prompt], queue=False, show_api=False, | |
| ).success(compose_prompt_to_copy, [v2_character, v2_series, prompt], [prompt], queue=False, show_api=False) | |
| demo.queue(default_concurrency_limit=200, max_size=200) | |
| demo.launch(max_threads=400) | |