| import gradio as gr | |
| import random | |
| import os | |
| models = { | |
| "Face Projection": gr.load("models/Purz/face-projection"), | |
| "Flux LoRA Uncensored": gr.load("models/prashanth970/flux-lora-uncensored"), | |
| "NSFW TrioHMH Flux": gr.load("models/DiegoJR1973/NSFW-TrioHMH-Flux"), | |
| "NSFW Master": gr.load("models/pimpilikipilapi1/NSFW_master") | |
| } | |
| def generate_image(text, num_inference_steps): | |
| result_images = {} | |
| for model_name, model in models.items(): | |
| result_images[model_name] = model(text) | |
| print(f"Inference Steps: {num_inference_steps}") | |
| return [result_images[model_name] for model_name in models] | |
| interface = gr.Interface( | |
| fn=generate_image, | |
| inputs=[ | |
| gr.Textbox(label="Type here your imagination:", placeholder="Type or click an example..."), | |
| gr.Slider(label="Number of inference steps", minimum=1, maximum=40, step=1, value=28), | |
| ], | |
| outputs=[gr.Image(label=model_name) for model_name in models], | |
| theme="NoCrypt/miku", | |
| description="Sorry for the inconvenience. The model is currently running on the CPU, which might affect performance. We appreciate your understanding.", | |
| ) | |
| interface.launch() | |