text: # Author: Bichen Wu (bichen@berkeley.edu) 02/27/2017
  #-*- coding: utf-8 -*-
  
  """Image data base class for kitti"""
  # BSD 3-Clause License
  #
  # Copyright (c) 2019, FPAI
  # Copyright (c) 2019, SeriouslyHAO
  # Copyright (c) 2019, xcj2019
  # Copyright (c) 2019, Leonfirst
  #
  # All rights reserved.
  #
  # Redistribution and use in source and binary forms, with or without
  # modification, are permitted provided that the following conditions are met:
  #
  # * Redistributions of source code must retain the above copyright notice, this
  #   list of conditions and the following disclaimer.
  #
  # * Redistributions in binary form must reproduce the above copyright notice,
  #   this list of conditions and the following disclaimer in the documentation
  #   and/or other materials provided with the distribution.
  #
  # * Neither the name of the copyright holder nor the names of its
  #   contributors may be used to endorse or promote products derived from
  #   this software without specific prior written permission.
  #
  # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
  # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
  # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
  # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
  # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
  # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
  # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
  # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  import os 
  import numpy as np
  import subprocess
  
  from .imdb import imdb
  
  
  class kitti(imdb):
    def __init__(self, image_set, data_path, mc):
      imdb.__init__(self, 'kitti_'+image_set, mc)
  
      self._image_set = image_set
      self._data_root_path = data_path
      self._lidar_2d_path = os.path.join(self._data_root_path, 'lidar_2d')
      self._gta_2d_path = os.path.join(self._data_root_path, 'gta')
  
      # a list of string indices of images in the directory
      self._image_idx = self._load_image_set_idx() 
      # a dict of image_idx -> [[cx, cy, w, h, cls_idx]]. x,y,w,h are not divided by
      # the image width and height
  
      ## batch reader ##
      self._perm_idx = None
      self._cur_idx = 0
      # TODO(bichen): add a random seed as parameter
      self._shuffle_image_idx()
  
  
    def _load_image_set_idx(self):
      image_set_file = os.path.join(
          self._data_root_path, 'ImageSet', self._image_set+'.txt')
      assert os.path.exists(image_set_file), \
          'File does not exist: {}'.format(image_set_file)
  
      with open(image_set_file) as f:
        image_idx = [x.strip() for x in f.readlines()]
      return image_idx
  
  
    def _lidar_2d_path_at(self, idx):
      if idx[:4] == 'gta_':
        lidar_2d_path = os.path.join(self._gta_2d_path, idx+'.npy')
      else:
        lidar_2d_path = os.path.join(self._lidar_2d_path, idx+'.npy')
  
      assert os.path.exists(lidar_2d_path), \
          'File does not exist: {}'.format(lidar_2d_path)
      return lidar_2d_path
  