| 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) | |