asa

 avatar
unknown
python
a year ago
4.3 kB
6
Indexable
import torch
import trimesh
from scipy.spatial.transform import Rotation as R
import numpy as np

from lib.common.BNI_utils import (
    depth_inverse_transform,
    double_side_bilateral_normal_integration,
    verts_inverse_transform,
)

class BNI:
    def __init__(self, dir_path, name, BNI_dict, cfg, device):

        self.scale = 256.0
        self.cfg = cfg
        self.name = name

        self.normal_front = BNI_dict["normal_F"]
        self.normal_back = BNI_dict["normal_B"]
        self.mask = BNI_dict["mask"]

        self.depth_front = BNI_dict["depth_F"]
        self.depth_back = BNI_dict["depth_B"]
        self.depth_mask = BNI_dict["depth_mask"]

        self.k = self.cfg['k']
        self.lambda1 = self.cfg['lambda1']
        self.boundary_consist = self.cfg['boundary_consist']
        self.cut_intersection = self.cfg['cut_intersection']

        self.F_B_surface = None
        self.F_B_trimesh = None
        self.F_depth = None
        self.B_depth = None

        self.device = device
        self.export_dir = dir_path

    def extract_surface(self, verbose=True):
        bni_result = double_side_bilateral_normal_integration(
            normal_front=self.normal_front,
            normal_back=self.normal_back,
            normal_mask=self.mask,
            depth_front=self.depth_front * self.scale,
            depth_back=self.depth_back * self.scale,
            depth_mask=self.depth_mask,
            k=self.k,
            lambda_normal_back=1.0,
            lambda_depth_front=self.lambda1,
            lambda_depth_back=self.lambda1,
            lambda_boundary_consistency=self.boundary_consist,
            cut_intersection=self.cut_intersection,
        )

        F_verts = verts_inverse_transform(bni_result["F_verts"], self.scale)
        B_verts = verts_inverse_transform(bni_result["B_verts"], self.scale)

        self.F_depth = depth_inverse_transform(bni_result["F_depth"], self.scale)
        self.B_depth = depth_inverse_transform(bni_result["B_depth"], self.scale/2)

        # Debug: Print shapes and some vertices for inspection
        print("F_verts shape:", F_verts.shape)
        print("B_verts shape:", B_verts.shape)
        print("Sample F_verts:", F_verts[:5])
        print("Sample B_verts:", B_verts[:5])

        # Rotate the back vertices 180 degrees around the y-axis
        rotation_matrix_y = R.from_euler('y', 180, degrees=True).as_matrix()
        B_verts_rotated = np.dot(B_verts, rotation_matrix_y.T)

        # Debug: Print rotated vertices
        print("Sample B_verts_rotated:", B_verts_rotated[:5])

        # Additional rotation if needed
        rotation_matrix_x = R.from_euler('x', -25, degrees=True).as_matrix()
        B_verts_rotated_x = np.dot(B_verts_rotated, rotation_matrix_x.T)

        # Debug: Print rotated vertices after second rotation
        print("Sample B_verts_rotated_x:", B_verts_rotated_x[:5])

        F_B_verts = torch.cat((F_verts, torch.tensor(B_verts_rotated_x)), dim=0)
        F_B_faces = torch.cat(
            (bni_result["F_faces"], bni_result["B_faces"] + bni_result["F_faces"].max() + 1), dim=0
        )

        self.F_B_trimesh = trimesh.Trimesh(
            F_B_verts.float(), F_B_faces.long(), process=False, maintain_order=True
        )

        self.F_trimesh = trimesh.Trimesh(
            F_verts.float(), bni_result["F_faces"].long(), process=False, maintain_order=True
        )

        self.B_trimesh = trimesh.Trimesh(
            torch.tensor(B_verts_rotated_x).float(), bni_result["B_faces"].long(), process=False, maintain_order=True
        )

if __name__ == "__main__":
    import os.path as osp
    import numpy as np
    from tqdm import tqdm

    root = "/home/yxiu/Code/ECON/results/examples/BNI"
    npy_file = f"{root}/304e9c4798a8c3967de7c74c24ef2e38.npy"
    bni_dict = np.load(npy_file, allow_pickle=True).item()

    default_cfg = {'k': 2, 'lambda1': 1e-4, 'boundary_consist': 1e-6}

    bni_object = BNI(
        osp.dirname(npy_file), osp.basename(npy_file), bni_dict, default_cfg,
        torch.device('cuda:0')
    )

    bni_object.extract_surface()
    bni_object.F_trimesh.export(osp.join(osp.dirname(npy_file), "F.obj"))
    bni_object.B_trimesh.export(osp.join(osp.dirname(npy_file), "B.obj"))
    bni_object.F_B_trimesh.export(osp.join(osp.dirname(npy_file), "BNI.obj"))
Editor is loading...
Leave a Comment