app.py

import gradio as gr
from diffusers import StableDiffusionImg2ImgPipeline
import torch
from PIL import Image

# Load the pretrained model
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float16,   # Or float32 if on CPU
    use_auth_token=True
)

# Set to GPU or CPU
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipe.to(device)

# Thumbnail generation function
def generate_thumbnail(prompt, input_image):
    image = input_image.resize((512, 512)).convert("RGB")
    result = pipe(prompt=prompt, image=image, strength=0.75, guidance_scale=7.5)
    return result.images[0]

# Gradio UI
interface = gr.Interface(
    fn=generate_thumbnail,
    inputs=[
        gr.Textbox(label="Thumbnail Prompt (e.g., 'NOOB vs PRO in Minecraft')"),
        gr.Image(type="pil", label="Upload Background Image")
    ],
    outputs=gr.Image(label="Generated Thumbnail"),
    title="🖼️ AI Thumbnail Generator",
    description="Upload a background image and enter a thumbnail prompt to generate your own YouTube-style thumbnail using Stable Diffusion!"
)

interface.launch()