| import torch | |
| import requests | |
| import numpy as np | |
| from io import BytesIO | |
| from diffusers import DiffusionPipeline | |
| from PIL import Image | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| "dylanebert/LGM-full", | |
| custom_pipeline="dylanebert/LGM-full", | |
| torch_dtype=torch.float16, | |
| trust_remote_code=True, | |
| ).to("cuda") | |
| input_url = "https://huggingface.co/datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg" | |
| input_image = Image.open(BytesIO(requests.get(input_url).content)) | |
| input_image = np.array(input_image, dtype=np.float32) / 255.0 | |
| result = pipeline("", input_image) | |
| result_path = "/tmp/output.ply" | |
| pipeline.save_ply(result, result_path) | |