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Zero
| import gradio as gr | |
| import numpy as np | |
| import random | |
| import spaces | |
| import torch | |
| from diffusers import DiffusionPipeline, AutoencoderTiny | |
| from huggingface_hub import hf_hub_download | |
| def feifeimodload(): | |
| dtype = torch.bfloat16 | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pipe = DiffusionPipeline.from_pretrained( | |
| "aifeifei798/DarkIdol-flux-v1.1", torch_dtype=dtype | |
| ).to(device) | |
| pipe.load_lora_weights( | |
| hf_hub_download("aifeifei798/flux-nsfw-lora", "Ultra-Realistic Nipple Generator_v2.safetensors"), | |
| adapter_name="Ultra-Realistic", | |
| ) | |
| pipe.set_adapters( | |
| ["Ultra-Realistic"], | |
| adapter_weights=[0.75], | |
| ) | |
| pipe.fuse_lora( | |
| adapter_name=["Ultra-Realistic"], | |
| lora_scale=1.0, | |
| ) | |
| pipe.vae.enable_slicing() | |
| pipe.vae.enable_tiling() | |
| pipe.unload_lora_weights() | |
| torch.cuda.empty_cache() | |
| return pipe | |
| pipe = feifeimodload() | |
| MAX_SEED = np.iinfo(np.int32).max | |
| MAX_IMAGE_SIZE = 2048 | |
| def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)): | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| generator = torch.Generator().manual_seed(seed) | |
| prompt = f"{prompt}, slight smile, Master of Light and Shadow." | |
| image = pipe( | |
| prompt = prompt, | |
| width = width, | |
| height = height, | |
| num_inference_steps = num_inference_steps, | |
| generator = generator, | |
| guidance_scale=3.5 | |
| ).images[0] | |
| return image, seed | |
| examples = [ | |
| "A stunning Japanese female model poses in a serene, misty forest, surrounded by lush greenery, with soft, warm light casting a golden glow on her face, as she gently lifts a delicate, crystal perfume bottle to her nose, her eyes closed in rapture, exuding an aura of elegance and refinement, with a subtle, enigmatic smile playing on her lips, in a masterful blend of natural and studio lighting, with a muted color palette of emerald greens, soft pinks, and creamy whites, and intricate details of her traditional Japanese attire, including a flowing, silk kimono with subtle, cherry blossom patterns, and a delicate, beaded obi, all perfectly captured in a high-resolution, large-format photograph, with impeccable composition, and a sense of timeless, ethereal beauty.", | |
| "Capture a serene Japanese model in a snow-covered street, clad in a sensual Balenciaga winter outfit, evoking a sense of intimacy and luxury, with a harmonious blend of warm and cool tones, subtle shadows, and meticulous details, conveying a narrative of elegance and poise.", | |
| "A high-resolution photograph of a female model posing for a Louis Vuitton brand advertisement, featuring natural lighting effects, a consistent style, balanced composition, rich details, harmonious colors, no visible flaws, emotional expression, creativity, and uniqueness, with optimized technical parameters, master-level lighting, master-level color, and master-level styling.", | |
| "A high-resolution photograph of a female model in a serene, natural setting, with soft, warm lighting, and a minimalist aesthetic, showcasing a elegant fragrance bottle and the model's effortless, emotive expression, with impeccable styling, and a muted color palette, evoking a sense of understated luxury and refinement.", | |
| "A high-resolution photograph of a female model posing beside a sleek, red Ferrari, bathed in warm, golden light, with subtle shadows accentuating her curves and the car's contours, set against a blurred, gradient blue background, with the model's elegant, flowing gown and the Ferrari's metallic sheen perfectly complementing each other in a masterful display of color, texture, and composition.", | |
| ] | |
| css=""" | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 520px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown(f"""# DarkIdol-flux | |
| DarkIdol-flux is a text-to-image AI model designed to create aesthetic, detailed and diverse images from textual prompts in just 6-8 steps. It offers enhanced performance in image quality, typography, understanding complex prompts, and resource efficiency. | |
| """) | |
| with gr.Row(): | |
| prompt = gr.Text( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=12, | |
| placeholder="Enter your prompt", | |
| container=False, | |
| ) | |
| run_button = gr.Button("Run") | |
| result = gr.Image(label="Result", show_label=False,height=520) | |
| with gr.Accordion("Advanced Settings", open=False): | |
| 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=64, | |
| value=832, | |
| ) | |
| height = gr.Slider( | |
| label="Height", | |
| minimum=256, | |
| maximum=MAX_IMAGE_SIZE, | |
| step=64, | |
| value=1280, | |
| ) | |
| with gr.Row(): | |
| num_inference_steps = gr.Slider( | |
| label="Number of inference steps", | |
| minimum=1, | |
| maximum=50, | |
| step=1, | |
| value=6, | |
| ) | |
| gr.Examples( | |
| examples = examples, | |
| fn = infer, | |
| inputs = [prompt], | |
| outputs = [result, seed], | |
| cache_examples=False | |
| ) | |
| gr.on( | |
| triggers=[run_button.click, prompt.submit], | |
| fn = infer, | |
| inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps], | |
| outputs = [result, seed] | |
| ) | |
| demo.launch() |