fix: remove cursed open3d code

datasets/shapenet_data_pc.py

@@ -4,7 +4,6 @@ import numpy as np
 from torch.utils.data import Dataset
 from torch.utils import data
 import random
-import open3d as o3d
 import numpy as np
 import torch.nn.functional as F
 
@@ -234,34 +233,6 @@ class ShapeNet15kPointClouds(Uniform15KPC):
 
 
 
-class PointCloudMasks(object):
-    '''
-    render a view then save mask
-    '''
-    def __init__(self, radius : float=10, elev: float =45, azim:float=315, ):
-
-        self.radius = radius
-        self.elev = elev
-        self.azim = azim
-
-
-    def __call__(self, points):
-
-        pcd = o3d.geometry.PointCloud()
-        pcd.points = o3d.utility.Vector3dVector(points)
-
-        camera = [self.radius * np.sin(90-self.elev) * np.cos(self.azim),
-                  self.radius * np.cos(90 - self.elev),
-                  self.radius * np.sin(90 - self.elev) * np.sin(self.azim),
-                  ]
-        # camera = [0,self.radius,0]
-        _, pt_map = pcd.hidden_point_removal(camera, self.radius)
-
-        mask = torch.zeros_like(points)
-        mask[pt_map] = 1
-
-        return mask #points[pt_map]
-
 
 ####################################################################################
 

datasets/shapenet_data_sv.py

@@ -2,7 +2,6 @@ import warnings
 from torch.utils.data import Dataset
 from tqdm import tqdm
 from pathlib import Path
-import open3d as o3d
 import os
 import numpy as np
 
@@ -219,39 +218,3 @@ class ShapeNet_Multiview_Points(Dataset):
 
         return data
 
-
-
-
-class DepthToSingleViewPoints(object):
-    '''
-    render a view then save mask
-    '''
-    def __init__(self, cam_ext, cam_int):
-
-        self.cam_ext = cam_ext.reshape(4,4)
-        self.cam_int = cam_int.reshape(3,3)
-
-
-    def __call__(self, depth_pth, depth_minmax_pth):
-
-        depth_minmax = np.load(depth_minmax_pth)
-        depth_img = plt.imread(depth_pth)[...,0]
-        mask = np.where(depth_img == 0, -1.0, 1.0)
-        depth_img = 1 - depth_img
-        depth_img = (depth_img * (np.max(depth_minmax) - np.min(depth_minmax)) + np.min(depth_minmax)) * mask
-
-        intr = o3d.camera.PinholeCameraIntrinsic(depth_img.shape[0], depth_img.shape[1],
-                                                 self.cam_int[0, 0], self.cam_int[1, 1], self.cam_int[0,2],
-                                                 self.cam_int[1,2])
-
-        depth_im = o3d.geometry.Image(depth_img.astype(np.float32, copy=False))
-
-        # rgbd_im = o3d.geometry.RGBDImage.create_from_color_and_depth(color_im, depth_im)
-        pcd = o3d.geometry.PointCloud.create_from_depth_image(depth_im, intr, self.cam_ext, depth_scale=1.)
-        pc =  np.asarray(pcd.points)
-
-        return pc, depth_img
-
-    def __repr__(self):
-        return 'MeshToMaskedVoxel_'+str(self.radius)+str(self.resolution)+str(self.elev )+str(self.azim)+str(self.img_size )
-

environment.yml

@@ -7,7 +7,6 @@ channels:
   - nvidia
   - conda-forge
   - pyg
-  - open3d-admin
 
 dependencies:
   - python
@@ -15,7 +14,6 @@ dependencies:
   - torchvision
   - cudatoolkit
   - matplotlib
-  - open3d
   - tqdm
   - trimesh
   - scipy