Python-PointSIFT一种类似SIFT的网络模块用于3D点云语义分割

a module for 3D semantic segmentation in point clouds

import pickle
import os
import numpy as np


class ScannetDataset（）:
    def __init__（self root npoints=8192 split=‘train‘）:
        self.npoints = npoints
        self.root = root
        self.split = split
        self.data_filename = os.path.join（self.root ‘scannet_%s.pickle‘ % split）
        with open（self.data_filename ‘rb‘） as fp:
            self.scene_points_list = pickle.load（fp encoding=‘bytes‘）
            self.semantic_labels_list = pickle.load（fp encoding=‘bytes‘）
        if split == ‘train‘:
            labelweights = np.zeros（21）
            for seg in self.semantic_labels_list:
                tmp _ = np.histogram（seg range（22））
                labelweights += tmp
            labelweights = labelweights.astype（np.float32）
            labelweights = labelweights/np.sum（labelweights）
            self.labelweights = 1/np.log（1.2+labelweights）
        elif split == ‘test‘:
            self.labelweights = np.ones（21）

    def __getitem__（self index）:
        point_set = self.scene_points_list[index]
        semantic_seg = self.semantic_labels_list[index].astype（np.int32）
        coordmax = np.max（point_setaxis=0）
        coordmin = np.min（point_setaxis=0）
        smpmin = np.maximum（coordmax-[1.5 1.5 3.0] coordmin）
        smpmin[2] = coordmin[2]
        smpsz = np.minimum（coordmax-smpmin [1.5 1.5 3.0]）
        smpsz[2] = coordmax[2]-coordmin[2]
        cur_semantic_seg = None
        cur_point_set = None
        mask = None
        for i in range（10）:
            curcenter = point_set[np.random.choice（len（semantic_seg）1）[0]:]
            curmin = curcenter-[0.75 0.75 1.5]
            curmax = curcenter+[0.75 0.75 1.5]
            curmin[2] = coordmin[2]
            curmax[2] = coordmax[2]
            curchoice = np.sum（（point_set >= （curmin-0.2））*（point_set <= （curmax+0.2））axis=1） == 3
            cur_point_set = point_set[curchoice :]
            cur_semantic_seg = semantic_seg[curchoice]
            if len（cur_semantic_seg） == 0:
                continue
            mask = np.sum（（cur_point_set >= （curmin-0.01））*（cur_point_set <= （curmax+0.01）） axis=1） == 3
            vidx = np.ceil（（cur_point_set[mask :]-curmin）/（curmax-curmin）*[31.0 31.0 62.0]）
            vidx = np.unique（vidx[: 0] * 31.0 * 62.0 + vidx[: 1] * 62.0 + vidx[: 2]）
            isvalid = np.sum（cur_semantic_seg > 0）/len（cur_semantic_seg） >= 0.7 and len（vidx）/31.0/31.0/62.0 >= 0.02
            if isvalid:
                break
        choice = np.random.choice（len（cur_semantic_seg） self.npoints replace=True）
        point_set = cur_point_set[choice:]

        semantic_seg = cur_semantic_seg[choice]
        mask = mask[choice]
        sample_weight = self.labelweights[semantic_seg]
        sample_weight *= mask
        return point_set semantic_seg sample_weight

    def __len__（self）:
        return len（self.scene_points_list）


class ScannetDatasetWholeScene（object）:
    def __init__（self root npoints=8192 split=‘train‘）:
     

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     目录           0  2018-11-24 03:49  pointSIFT-master\
     文件        3113  2018-11-24 03:49  pointSIFT-master\README.md
     目录           0  2018-11-24 03:49  pointSIFT-master\img\
     文件       47663  2018-11-24 03:49  pointSIFT-master\img\fig1.png
     目录           0  2018-11-24 03:49  pointSIFT-master\models\
     文件        4886  2018-11-24 03:49  pointSIFT-master\models\pointSIFT_pointnet.py
     文件        6104  2018-11-24 03:49  pointSIFT-master\scannet_dataset.py
     文件           1  2018-11-24 03:49  pointSIFT-master\test.py
     目录           0  2018-11-24 03:49  pointSIFT-master\tf_utils\
     文件       18149  2018-11-24 03:49  pointSIFT-master\tf_utils\pointSIFT_util.py
     文件       11756  2018-11-24 03:49  pointSIFT-master\tf_utils\provider.py
     目录           0  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\
     目录           0  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\
     文件         188  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\.gitignore
     目录           0  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\
     文件         300  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\compile.sh
     文件        3824  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\query_ball_point.cpp
     文件        4309  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\query_ball_point.cu
     文件        4230  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\query_ball_point_block.cu
     文件        4589  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\query_ball_point_grid.cu
     文件        2481  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\selection_sort.cpp
     文件        1920  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\selection_sort.cu
     文件        2454  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\test\selection_sort_const.cu
     文件       10471  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\tf_grouping.cpp
     文件        2777  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\tf_grouping.py
     文件         886  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\tf_grouping_compile.sh
     文件        5045  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\tf_grouping_g.cu
     文件         904  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\grouping\tf_grouping_op_test.py
     目录           0  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\interpolation\
     文件        5003  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\interpolation\interpolate.cpp
     文件       10969  2018-11-24 03:49  pointSIFT-master\tf_utils\tf_ops\interpolation\tf_interpolate.cpp
............此处省略18个文件信息