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()