app.py

import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
from PIL import Image
import numpy as np
import cv2

# Device setup
device = "cuda" if torch.cuda.is_available() else "cpu"

# Load Stable Diffusion model
model_name = "CompVis/stable-diffusion-v1-4"
def load_image_model():
    return StableDiffusionPipeline.from_pretrained(model_name, torch_dtype=torch.float16).to(device)

image_model = load_image_model()

def generate_image(prompt):
    with torch.no_grad():
        image = image_model(prompt).images[0]
    return image

# Face swap function placeholder (replace with actual implementation)
def swap_faces(image1, image2):
    # Placeholder implementation, you should replace this with your actual face swapping code
    return image1

def face_swap(image1, image2):
    image1 = cv2.cvtColor(np.array(image1), cv2.COLOR_RGB2BGR)
    image2 = cv2.cvtColor(np.array(image2), cv2.COLOR_RGB2BGR)
    swapped_image = swap_faces(image1, image2)
    return cv2.cvtColor(swapped_image, cv2.COLOR_BGR2RGB)

# Upscaling function
def upscale_image(image, scale_factor=2):
    image = Image.fromarray(np.array(image))
    width, height = image.size
    new_size = (int(width * scale_factor), int(height * scale_factor))
    upscaled_image = image.resize(new_size, Image.LANCZOS)
    return upscaled_image

# Gradio interface function
def process_image(prompt, image1=None, image2=None, scale_factor=2):
    # Generate image from prompt
    generated_image = generate_image(prompt)
    
    # Perform faceswap if two images are provided
    swapped_image = None
    if image1 and image2:
        swapped_image = face_swap(image1, image2)
    
    # Perform upscaling if scale factor is specified
    upscaled_image = upscale_image(generated_image, scale_factor)

    return {
        "Generated Image": generated_image,
        "Swapped Image": swapped_image,
        "Upscaled Image": upscaled_image
    }

# Gradio interface setup
iface = gr.Interface(
    fn=process_image,
    inputs=[
        gr.Textbox(label="Enter your prompt"),
        gr.Image(label="Image 1 (for faceswap)", type="pil", optional=True),
        gr.Image(label="Image 2 (for faceswap)", type="pil", optional=True),
        gr.Slider(label="Upscale Factor", minimum=1, maximum=4, step=1, default=2)
    ],
    outputs=[
        gr.Image(label="Generated Image"),
        gr.Image(label="Swapped Image"),
        gr.Image(label="Upscaled Image")
    ],
    title="Fooocus Image Processing",
    description="Generate images from prompts, swap faces, and upscale images."
)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)