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| import tempfile | |
| import numpy as np | |
| import PIL.Image | |
| import torch | |
| import trimesh | |
| from diffusers import ShapEImg2ImgPipeline, ShapEPipeline | |
| from diffusers.utils import export_to_ply | |
| class Model: | |
| def __init__(self): | |
| self.device = torch.device( | |
| 'cuda' if torch.cuda.is_available() else 'cpu') | |
| self.pipe = ShapEPipeline.from_pretrained('openai/shap-e', | |
| torch_dtype=torch.float16) | |
| self.pipe.to(self.device) | |
| self.pipe_img = ShapEImg2ImgPipeline.from_pretrained( | |
| 'openai/shap-e-img2img', torch_dtype=torch.float16) | |
| self.pipe_img.to(self.device) | |
| def to_glb(self, ply_path: str) -> str: | |
| mesh = trimesh.load(ply_path) | |
| rot = trimesh.transformations.rotation_matrix(-np.pi / 2, [1, 0, 0]) | |
| mesh = mesh.apply_transform(rot) | |
| rot = trimesh.transformations.rotation_matrix(np.pi, [0, 1, 0]) | |
| mesh = mesh.apply_transform(rot) | |
| mesh_path = tempfile.NamedTemporaryFile(suffix='.glb', delete=False) | |
| mesh.export(mesh_path.name, file_type='glb') | |
| return mesh_path.name | |
| def run_text(self, | |
| prompt: str, | |
| seed: int = 0, | |
| guidance_scale: float = 15.0, | |
| num_steps: int = 64) -> str: | |
| generator = torch.Generator(device=self.device).manual_seed(seed) | |
| images = self.pipe(prompt, | |
| generator=generator, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_steps, | |
| output_type='mesh').images | |
| ply_path = tempfile.NamedTemporaryFile(suffix='.ply', | |
| delete=False, | |
| mode='w+b') | |
| export_to_ply(images[0], ply_path.name) | |
| return self.to_glb(ply_path.name) | |
| def run_image(self, | |
| image: PIL.Image.Image, | |
| seed: int = 0, | |
| guidance_scale: float = 3.0, | |
| num_steps: int = 64) -> str: | |
| generator = torch.Generator(device=self.device).manual_seed(seed) | |
| images = self.pipe_img(image, | |
| generator=generator, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_steps, | |
| output_type='mesh').images | |
| ply_path = tempfile.NamedTemporaryFile(suffix='.ply', | |
| delete=False, | |
| mode='w+b') | |
| export_to_ply(images[0], ply_path.name) | |
| return self.to_glb(ply_path.name) | |