from diffusers import StableDiffusionInpaintPipeline
import torch
from PIL import Image

def test_local():
    # Load model
    model_id = "Uminosachi/realisticVisionV51_v51VAE-inpainting"
    device = "cuda" if torch.cuda.is_available() else "cpu"
    dtype = torch.float16 if device == "cuda" else torch.float32
    
    print(f"Using device: {device}")
    
    pipe = StableDiffusionInpaintPipeline.from_pretrained(
        model_id,
        torch_dtype=dtype,
        safety_checker=None
    ).to(device)
    
    # Load test images
    image_path = r"C:\Users\M. Y\Downloads\t2.png"
    mask_path = "generated_mask_1.png"
    
    image = Image.open(image_path)
    mask_image = Image.open(mask_path)
    
    # Resize to multiple of 8
    width, height = (dim - dim % 8 for dim in image.size)
    image = image.resize((width, height))
    mask_image = mask_image.resize((width, height))
    mask_image = mask_image.convert("L")
    
    # Test inference
    result = pipe(
        prompt="add some flowers and a fountain",
        image=image,
        mask_image=mask_image,
        num_inference_steps=20,
        guidance_scale=7.5,
    ).images[0]
    
    result.save("local_test_result.png")
    print("Test complete! Check local_test_result.png")

if __name__ == "__main__":
    test_local()