| import torch |
| import kiui |
| import numpy as np |
| import argparse |
| from pipeline_mvdream import MVDreamPipeline |
|
|
| pipe = MVDreamPipeline.from_pretrained( |
| |
| "ashawkey/imagedream-ipmv-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, 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.write_image(f'test_imagedream_{i}.jpg', grid) |
|
|