| import torch | |
| import kiui | |
| import numpy as np | |
| import argparse | |
| from pipeline_mvdream import MVDreamPipeline | |
| pipe = MVDreamPipeline.from_pretrained( | |
| "./weights_imagedream", # local weights | |
| # "ashawkey/mvdream-sd2.1-diffusers", | |
| 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) | |
| 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) | |