Set latents in StableDiffusionInpaintPipeline to original image
Hello,I’m trying to set the initial latents of the StableDiffusionInpaintPipeline to the original image.This is what I tried:# load the pipeline
        pipe = StableDiffusionInpaintPipeline.from_pretrained(
            "runwayml/stable-diffusion-inpainting",
            torch_dtype=torch.float16
        )
        pipe = pipe.to("cuda")

        # convert the image to a tensor and add a batch dimension
        image_tensor = pil_to_tensor(init_image).to(torch.float16).unsqueeze(0)

        # encode the image into its latent space using the VAE
        with torch.no_grad():
            latents = pipe.vae.encode(image_tensor.cuda())
        tensor_image = latents.latent_dist.sample()

        image = pipe(prompt="",
                    image=init_image, 
                    mask_image=fg_mask,
                    latents=tensor_image).images[0]However the results look very wrong, the general image is recognizable but it is almost like latent noise and it is also changed where the mask is 0.What am I missing?
2024-05-17T13:44:40Z
Hey hew! You’ll probably not remember, but did you manage to solve this?Thanks!