import torch import kiui import numpy as np import argparse from pipeline_mvdream import MVDreamPipeline pipe = MVDreamPipeline.from_pretrained( # "./weights_imagedream", # local weights "ashawkey/imagedream-ipmv-diffusers", # remote weights torch_dtype=torch.float16, trust_remote_code=True, ) pipe = pipe.to("cuda") parser = argparse.ArgumentParser(description="ImageDream") parser.add_argument("image", type=str, default='data/anya_rgba.png') parser.add_argument("--prompt", type=str, default="") args = parser.parse_args() for i in range(5): input_image = kiui.read_image(args.image, mode='float') image = pipe(args.prompt, input_image, guidance_scale=5, num_inference_steps=30, elevation=0) grid = np.concatenate( [ np.concatenate([image[0], image[2]], axis=0), np.concatenate([image[1], image[3]], axis=0), ], axis=1, ) # kiui.vis.plot_image(grid) kiui.write_image(f'test_imagedream_{i}.jpg', grid)