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on
Zero
Running
on
Zero
| import gradio as gr | |
| import numpy as np | |
| import random | |
| import spaces | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| import importlib # to import tag modules dynamically | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| model_repo_id = "John6666/wai-ani-nsfw-ponyxl-v8-sdxl" # Replace with your desired model | |
| if torch.cuda.is_available(): | |
| torch_dtype = torch.float16 | |
| else: | |
| torch_dtype = torch.float32 | |
| pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype) | |
| pipe.to(device) | |
| MAX_SEED = np.iinfo(np.int32).max | |
| MAX_IMAGE_SIZE = 1024 | |
| # Function to load tags dynamically based on the selected tab | |
| def load_tags(active_tab): | |
| if active_tab == "Gay": | |
| tags_module = importlib.import_module('tags_gay') # dynamically import the tags_gay module | |
| elif active_tab == "Straight": | |
| tags_module = importlib.import_module('tags_straight') # dynamically import the tags_straight module | |
| elif active_tab == "Lesbian": | |
| tags_module = importlib.import_module('tags_lesbian') # dynamically import the tags_lesbian module | |
| else: | |
| raise ValueError(f"Unknown tab: {active_tab}") | |
| return tags_module | |
| def infer( | |
| prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, | |
| selected_participant_tags, selected_tribe_tags, selected_role_tags, selected_skin_tone_tags, selected_body_type_tags, | |
| selected_tattoo_tags, selected_piercing_tags, selected_expression_tags, selected_eye_tags, selected_hair_style_tags, | |
| selected_position_tags, selected_fetish_tags, selected_location_tags, selected_camera_tags, selected_atmosphere_tags, | |
| active_tab, progress=gr.Progress(track_tqdm=True) | |
| ): | |
| # Dynamically load the correct tags module based on active tab | |
| tags_module = load_tags(active_tab) | |
| # Now use the tags from the loaded module | |
| participant_tags = tags_module.participant_tags | |
| tribe_tags = tags_module.tribe_tags | |
| role_tags = tags_module.role_tags | |
| skin_tone_tags = tags_module.skin_tone_tags | |
| body_type_tags = tags_module.body_type_tags | |
| tattoo_tags = tags_module.tattoo_tags | |
| piercing_tags = tags_module.piercing_tags | |
| expression_tags = tags_module.expression_tags | |
| eye_tags = tags_module.eye_tags | |
| hair_style_tags = tags_module.hair_style_tags | |
| position_tags = tags_module.position_tags | |
| fetish_tags = tags_module.fetish_tags | |
| location_tags = tags_module.location_tags | |
| camera_tags = tags_module.camera_tags | |
| atmosphere_tags = tags_module.atmosphere_tags | |
| # Handle the active tab and generate the prompt accordingly | |
| tag_list = ( | |
| [participant_tags[tag] for tag in selected_participant_tags] + | |
| [tribe_tags[tag] for tag in selected_tribe_tags] + | |
| [role_tags[tag] for tag in selected_role_tags] + | |
| [skin_tone_tags[tag] for tag in selected_skin_tone_tags] + | |
| [body_type_tags[tag] for tag in selected_body_type_tags] + | |
| [tattoo_tags[tag] for tag in selected_tattoo_tags] + | |
| [piercing_tags[tag] for tag in selected_piercing_tags] + | |
| [expression_tags[tag] for tag in selected_expression_tags] + | |
| [eye_tags[tag] for tag in selected_eye_tags] + | |
| [hair_style_tags[tag] for tag in selected_hair_style_tags] + | |
| [position_tags[tag] for tag in selected_position_tags] + | |
| [fetish_tags[tag] for tag in selected_fetish_tags] + | |
| [location_tags[tag] for tag in selected_location_tags] + | |
| [camera_tags[tag] for tag in selected_camera_tags] + | |
| [atmosphere_tags[tag] for tag in selected_atmosphere_tags] | |
| ) | |
| final_prompt = f"score_9, score_8_up, score_7_up, source_anime, {', '.join(tag_list)}" | |
| # Concatenate additional negative prompts | |
| additional_negatives = "worst quality, bad quality, jpeg artifacts, source_cartoon, 3d, (censor), monochrome, blurry, lowres, watermark" | |
| full_negative_prompt = f"{additional_negatives}, {negative_prompt}" | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| generator = torch.Generator(device=device).manual_seed(seed) | |
| image = pipe( | |
| prompt=final_prompt, | |
| negative_prompt=full_negative_prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_inference_steps, | |
| width=width, | |
| height=height, | |
| generator=generator | |
| ).images[0] | |
| return image, seed, f"Prompt: {final_prompt}\nNegative Prompt: {full_negative_prompt}" | |
| # CSS for the layout | |
| css = """ | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 640px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown("# Image Generator with Tags and Prompts") | |
| result = gr.Image(label="Result", show_label=False) | |
| prompt_info = gr.Textbox(label="Prompts Used", lines=3, interactive=False) | |
| active_tab = gr.State("Prompt Input") | |
| with gr.Tabs() as tabs: | |
| # Prompt Input Tab | |
| with gr.TabItem("Prompt Input"): | |
| prompt = gr.Textbox(label="Prompt", placeholder="Enter your custom prompt") | |
| tabs.select(lambda: "Prompt Input", inputs=None, outputs=active_tab) | |
| # Straight Tab | |
| with gr.TabItem("Straight"): | |
| selected_participant_tags = gr.CheckboxGroup(choices=[], label="Participant Tags") | |
| selected_tribe_tags = gr.CheckboxGroup(choices=[], label="Tribe Tags") | |
| selected_role_tags = gr.CheckboxGroup(choices=[], label="Role Tags") | |
| selected_skin_tone_tags = gr.CheckboxGroup(choices=[], label="Skin Tone Tags") | |
| selected_body_type_tags = gr.CheckboxGroup(choices=[], label="Body Type Tags") | |
| selected_tattoo_tags = gr.CheckboxGroup(choices=[], label="Tattoo Tags") | |
| selected_piercing_tags = gr.CheckboxGroup(choices=[], label="Piercing Tags") | |
| selected_expression_tags = gr.CheckboxGroup(choices=[], label="Expression Tags") | |
| selected_eye_tags = gr.CheckboxGroup(choices=[], label="Eye Tags") | |
| selected_hair_style_tags = gr.CheckboxGroup(choices=[], label="Hair Style Tags") | |
| selected_position_tags = gr.CheckboxGroup(choices=[], label="Position Tags") | |
| selected_fetish_tags = gr.CheckboxGroup(choices=[], label="Fetish Tags") | |
| selected_location_tags = gr.CheckboxGroup(choices=[], label="Location Tags") | |
| selected_camera_tags = gr.CheckboxGroup(choices=[], label="Camera Tags") | |
| selected_atmosphere_tags = gr.CheckboxGroup(choices=[], label="Atmosphere Tags") | |
| tabs.select(lambda: "Straight", inputs=None, outputs=active_tab) | |
| # Gay Tab | |
| with gr.TabItem("Gay"): | |
| selected_participant_tags = gr.CheckboxGroup(choices=[], label="Participant Tags") | |
| selected_tribe_tags = gr.CheckboxGroup(choices=[], label="Tribe Tags") | |
| selected_role_tags = gr.CheckboxGroup(choices=[], label="Role Tags") | |
| selected_skin_tone_tags = gr.CheckboxGroup(choices=[], label="Skin Tone Tags") | |
| selected_body_type_tags = gr.CheckboxGroup(choices=[], label="Body Type Tags") | |
| selected_tattoo_tags = gr.CheckboxGroup(choices=[], label="Tattoo Tags") | |
| selected_piercing_tags = gr.CheckboxGroup(choices=[], label="Piercing Tags") | |
| selected_expression_tags = gr.CheckboxGroup(choices=[], label="Expression Tags") | |
| selected_eye_tags = gr.CheckboxGroup(choices=[], label="Eye Tags") | |
| selected_hair_style_tags = gr.CheckboxGroup(choices=[], label="Hair Style Tags") | |
| selected_position_tags = gr.CheckboxGroup(choices=[], label="Position Tags") | |
| selected_fetish_tags = gr.CheckboxGroup(choices=[], label="Fetish Tags") | |
| selected_location_tags = gr.CheckboxGroup(choices=[], label="Location Tags") | |
| selected_camera_tags = gr.CheckboxGroup(choices=[], label="Camera Tags") | |
| selected_atmosphere_tags = gr.CheckboxGroup(choices=[], label="Atmosphere Tags") | |
| tabs.select(lambda: "Gay", inputs=None, outputs=active_tab) | |
| # Lesbian Tab | |
| with gr.TabItem("Lesbian"): | |
| selected_participant_tags = gr.CheckboxGroup(choices=[], label="Participant Tags") | |
| selected_tribe_tags = gr.CheckboxGroup(choices=[], label="Tribe Tags") | |
| selected_role_tags = gr.CheckboxGroup(choices=[], label="Role Tags") | |
| selected_skin_tone_tags = gr.CheckboxGroup(choices=[], label="Skin Tone Tags") | |
| selected_body_type_tags = gr.CheckboxGroup(choices=[], label="Body Type Tags") | |
| selected_tattoo_tags = gr.CheckboxGroup(choices=[], label="Tattoo Tags") | |
| selected_piercing_tags = gr.CheckboxGroup(choices=[], label="Piercing Tags") | |
| selected_expression_tags = gr.CheckboxGroup(choices=[], label="Expression Tags") | |
| selected_eye_tags = gr.CheckboxGroup(choices=[], label="Eye Tags") | |
| selected_hair_style_tags = gr.CheckboxGroup(choices=[], label="Hair Style Tags") | |
| selected_position_tags = gr.CheckboxGroup(choices=[], label="Position Tags") | |
| selected_fetish_tags = gr.CheckboxGroup(choices=[], label="Fetish Tags") | |
| selected_location_tags = gr.CheckboxGroup(choices=[], label="Location Tags") | |
| selected_camera_tags = gr.CheckboxGroup(choices=[], label="Camera Tags") | |
| selected_atmosphere_tags = gr.CheckboxGroup(choices=[], label="Atmosphere Tags") | |
| tabs.select(lambda: "Lesbian", inputs=None, outputs=active_tab) | |
| # Advanced Settings | |
| with gr.Accordion("Advanced Settings", open=False): | |
| negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter negative prompt") | |
| seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0) | |
| randomize_seed = gr.Checkbox(label="Randomize Seed", value=True) | |
| with gr.Row(): | |
| width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024) | |
| height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024) | |
| with gr.Row(): | |
| guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.0, maximum=10.0, step=0.1, value=7) | |
| num_inference_steps = gr.Slider(label="Number of Inference Steps", minimum=1, maximum=50, step=1, value=35) | |
| run_button = gr.Button("Run") | |
| run_button.click( | |
| infer, | |
| inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, | |
| selected_participant_tags, selected_tribe_tags, selected_role_tags, selected_skin_tone_tags, selected_body_type_tags, | |
| selected_tattoo_tags, selected_piercing_tags, selected_expression_tags, selected_eye_tags, | |
| selected_hair_style_tags, selected_position_tags, selected_fetish_tags, selected_location_tags, | |
| selected_camera_tags, selected_atmosphere_tags, active_tab], | |
| outputs=[result, seed, prompt_info] | |
| ) | |
| demo.queue().launch() | |