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import torch | |
import kiui | |
import numpy as np | |
import argparse | |
from pipeline_mvdream import MVDreamPipeline | |
import ipdb | |
pipe = MVDreamPipeline.from_pretrained( | |
# "./weights_imagedream", # local weights | |
"/mnt/cfs/home/liweiyu/codes/3DNativeGeneration/ckpts/pretrained_weights/huggingface/hub/models--ashawkey--imagedream-ipmv-diffusers/snapshots/73a034178e748421506492e91790cc62d6aefef5", # 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) | |
ipdb.set_trace() | |
# print(image) | |
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) | |