code: def get_ssd_config(img_reshape, inference=False):
      ssd_config = OrderedDict()
      ssd_config["batch_size"] = 32
      if inference:
          ssd_config["batch_size"] = 1
      ssd_config["block_size"] = 50
      ssd_config["cache_directory"] = get_data_cache_or_nothing(
          subdir="kitti_cache"
      )
      ssd_config["etl"] = [
          {
              "type": "localization_ssd",
              "height": img_reshape[0],
              "width": img_reshape[1],
              "max_gt_boxes": 500,
              "class_names": [
                  "__background__",
                  "Car",
                  "Van",
                  "Truck",
                  "Pedestrian",
                  "Person_sitting",
                  "Cyclist",
                  "Tram",
                  "Misc",
                  "DontCare",
              ],
          },
          {
              "type": "image",
              "height": img_reshape[0],
              "width": img_reshape[1],
              "channels": 3,
          },
      ]
      if not inference:
          ssd_config["augmentation"] = [
              {
                  "type": "image",
                  "batch_samplers": [
                      {"max_sample": 1, "max_trials": 1},
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "min_jaccard_overlap": 0.1
                          },
                      },
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "min_jaccard_overlap": 0.3
                          },
                      },
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "min_jaccard_overlap": 0.5
                          },
                      },
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "min_jaccard_overlap": 0.7
                          },
                      },
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "min_jaccard_overlap": 0.9
                          },
                      },
                      {
                          "max_sample": 1,
                          "max_trials": 50,
                          "sampler": {
                              "scale": [0.3, 1.0],
                              "aspect_ratio": [0.5, 2.0],
                          },
                          "sample_constraint": {
                              "max_jaccard_overlap": 1.0,
                              "min_jaccard_overlap": 0.1,
                          },
                      },
                  ],
              }
          ]
  
      ssd_config["ssd_config"] = OrderedDict(
          [
              (
                  "conv4_3",
                  {
                      "min_sizes": 30.0,
                      "max_sizes": 60.0,
                      "aspect_ratios": 2.0,
                      "step": 8,
                      "normalize": True,
                  },
              ),
              (
                  "fc7",
                  {
                      "min_sizes": 60.0,
                      "max_sizes": 111.0,
                      "aspect_ratios": (2.0, 3.0),
                      "step": 16,
                  },
              ),
              (
                  "conv6_2",
                  {
                      "min_sizes": 111.0,
                      "max_sizes": 162.0,
                      "aspect_ratios": (2.0, 3.0),
                      "step": 32,
                  },
              ),
              (
                  "conv7_2",
                  {
                      "min_sizes": 162.0,
                      "max_sizes": 213.0,
                      "aspect_ratios": (2.0, 3.0),
                      "step": 64,
                  },
              ),
              (
                  "conv8_2",
                  {
                      "min_sizes": 213.0,
                      "max_sizes": 264.0,
                      "aspect_ratios": 2.0,
                      "step": 100,
                  },
              ),
              (
                  "conv9_2",
                  {
                      "min_sizes": 264.0,
                      "max_sizes": 315.0,
                      "aspect_ratios": 2.0,
                      "step": {"step_h": 300, "step_w": 100},
                  },
              ),
          ]
      )
  
      return ssd_config
  
file_path: neon/examples/ssd/datasets/ingest_kitti.py
imports: from __future__ import print_function
  import os
  import glob
  import json
  import numpy
  from PIL import Image
  import math
  from tqdm import tqdm
  from collections import OrderedDict
  import ingest_utils
  from neon.util.persist import get_data_cache_or_nothing
label_desc: Use image node_id 1 for calling a global function with example usage: get_ssd_config(img_reshape, inference) and returns: ssd_config