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import gradio as gr
import random
import os
# Load all models
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, seed, width, height, guidance_scale, num_inference_steps):
if seed is not None:
random.seed(seed)
result_images = {}
for model_name, model in models.items():
result_images[model_name] = model(text)
print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
return [result_images[model_name] for model_name in models]
def randomize_parameters():
seed = random.randint(0, 999999)
width = random.randint(512, 2048)
height = random.randint(512, 2048)
guidance_scale = round(random.uniform(0.1, 20.0), 1)
num_inference_steps = random.randint(1, 40)
return seed, width, height, guidance_scale, num_inference_steps
interface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Type here your imagination:", placeholder="Type or click an example..."),
gr.Slider(label="Seed", minimum=0, maximum=999999, step=1),
gr.Slider(label="Width", minimum=512, maximum=2048, step=64, value=1024),
gr.Slider(label="Height", minimum=512, maximum=2048, step=64, value=1024),
gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20.0, step=0.1, value=3.0),
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()
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