setting-paramerts.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Publishing.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K5gIl9aSVdGq"
      },
      "source": [
        "#### Defining training parameters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YVps_k4JRGa7"
      },
      "source": [
        "num_classes = 1\r\n",
        "batch_size = 96\r\n",
        "num_steps = 7500\r\n",
        "num_eval_steps = 1000\r\n",
        "\r\n",
        "train_record_path = '/content/dataset/train.record'\r\n",
        "test_record_path = '/content/dataset/test.record'\r\n",
        "model_dir = '/content/training/'\r\n",
        "labelmap_path = '/content/labelmap.pbtxt'\r\n",
        "\r\n",
        "pipeline_config_path = 'mobilenet_v2.config'\r\n",
        "fine_tune_checkpoint = '/content/mobilenet_v2/mobilenet_v2.ckpt-1'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BOiWE_mCVgap"
      },
      "source": [
        "#### Editing config file"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hH9pVN4qfbAb"
      },
      "source": [
        "import re\r\n",
        "\r\n",
        "with open(pipeline_config_path) as f:\r\n",
        "    config = f.read()\r\n",
        "\r\n",
        "with open(pipeline_config_path, 'w') as f:\r\n",
        "\r\n",
        "  # Set labelmap path\r\n",
        "  config = re.sub('label_map_path: \".*?\"', \r\n",
        "             'label_map_path: \"{}\"'.format(labelmap_path), config)\r\n",
        "  \r\n",
        "  # Set fine_tune_checkpoint path\r\n",
        "  config = re.sub('fine_tune_checkpoint: \".*?\"',\r\n",
        "                  'fine_tune_checkpoint: \"{}\"'.format(fine_tune_checkpoint), config)\r\n",
        "  \r\n",
        "  # Set train tf-record file path\r\n",
        "  config = re.sub('(input_path: \".*?)(PATH_TO_BE_CONFIGURED/train)(.*?\")', \r\n",
        "                  'input_path: \"{}\"'.format(train_record_path), config)\r\n",
        "  \r\n",
        "  # Set test tf-record file path\r\n",
        "  config = re.sub('(input_path: \".*?)(PATH_TO_BE_CONFIGURED/val)(.*?\")', \r\n",
        "                  'input_path: \"{}\"'.format(test_record_path), config)\r\n",
        "  \r\n",
        "  # Set number of classes.\r\n",
        "  config = re.sub('num_classes: [0-9]+',\r\n",
        "                  'num_classes: {}'.format(num_classes), config)\r\n",
        "  \r\n",
        "  # Set batch size\r\n",
        "  config = re.sub('batch_size: [0-9]+',\r\n",
        "                  'batch_size: {}'.format(batch_size), config)\r\n",
        "  \r\n",
        "  # Set training steps\r\n",
        "  config = re.sub('num_steps: [0-9]+',\r\n",
        "                  'num_steps: {}'.format(num_steps), config)\r\n",
        "  \r\n",
        "  f.write(config)"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}