prep_dataset_1.ipynb

{
  "cells": [
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Traffix-C23-PC636/scripts/blob/main/prep_dataset_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O5aGPQ2tDllw",
        "outputId": "bcdf2eb1-112d-43ae-a1e5-600649ba6bb1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-05-22 11:42:29--  http://images.cocodataset.org/zips/val2017.zip\n",
            "Resolving images.cocodataset.org (images.cocodataset.org)... 52.217.203.33, 3.5.28.223, 54.231.199.225, ...\n",
            "Connecting to images.cocodataset.org (images.cocodataset.org)|52.217.203.33|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 815585330 (778M) [application/zip]\n",
            "Saving to: ‘val2017.zip.1’\n",
            "\n",
            "val2017.zip.1        32%[=====>              ] 250.24M  44.4MB/s    eta 14s    ^C\n"
          ]
        }
      ],
      "source": [
        "# !wget http://images.cocodataset.org/zips/train2017.zip\n",
        "!wget http://images.cocodataset.org/zips/val2017.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7VrD4toPJWQI",
        "outputId": "989a32a0-1899-44b3-aaa6-de70f84855a8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "mkdir: cannot create directory ‘datasets’: File exists\n",
            "Archive:  val2017.zip\n",
            "replace datasets/COCO/val2017/000000212226.jpg? [y]es, [n]o, [A]ll, [N]one, [r]ename: "
          ]
        }
      ],
      "source": [
        "!mkdir datasets\n",
        "# !unzip train2017.zip -d datasets/COCO\n",
        "# !rm train2017.zip\n",
        "!unzip val2017.zip -d datasets/COCO"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Uw4D-4h0TVMH",
        "outputId": "6af0dfe1-28e1-49a7-ebb5-16e59576b920"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-05-22 11:43:00--  http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
            "Resolving images.cocodataset.org (images.cocodataset.org)... 52.217.229.17, 3.5.1.139, 52.216.99.187, ...\n",
            "Connecting to images.cocodataset.org (images.cocodataset.org)|52.217.229.17|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 252907541 (241M) [application/zip]\n",
            "Saving to: ‘annotations_trainval2017.zip’\n",
            "\n",
            "annotations_trainva 100%[===================>] 241.19M  43.4MB/s    in 6.2s    \n",
            "\n",
            "2023-05-22 11:43:06 (38.9 MB/s) - ‘annotations_trainval2017.zip’ saved [252907541/252907541]\n",
            "\n",
            "Archive:  annotations_trainval2017.zip\n",
            "  inflating: datasets/COCO/annotations/instances_train2017.json  \n",
            "  inflating: datasets/COCO/annotations/instances_val2017.json  \n",
            "  inflating: datasets/COCO/annotations/captions_train2017.json  \n",
            "  inflating: datasets/COCO/annotations/captions_val2017.json  \n",
            "  inflating: datasets/COCO/annotations/person_keypoints_train2017.json  \n",
            "  inflating: datasets/COCO/annotations/person_keypoints_val2017.json  \n"
          ]
        }
      ],
      "source": [
        "!wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
        "!unzip annotations_trainval2017.zip -d datasets/COCO"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "qmSw-aoFvHH2"
      },
      "source": [
        "FILTER CLASESSES\n",
        "\n",
        "adjust filter.py with the data you looking for and change the `categories` variable with the selected COCO classes accordingly."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ALJjK3ICg0ov",
        "outputId": "8968a670-923a-441a-e1c4-db73b822deed"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "loading annotations into memory...\n",
            "Done (t=0.85s)\n",
            "creating index...\n",
            "index created!\n",
            "catIds:  [2, 3, 4, 6, 8]\n",
            "870 images of '' instances\n",
            "Saving the images with required categories ...\n",
            "100% 870/870 [06:00<00:00,  2.41it/s]\n",
            "Filtering the annotations ... \n",
            "new_categories:  [{'supercategory': 'vehicle', 'id': 2, 'name': 'bicycle'}, {'supercategory': 'vehicle', 'id': 3, 'name': 'car'}, {'supercategory': 'vehicle', 'id': 4, 'name': 'motorcycle'}, {'supercategory': 'vehicle', 'id': 6, 'name': 'bus'}, {'supercategory': 'vehicle', 'id': 8, 'name': 'truck'}]\n",
            "saving json: \n"
          ]
        }
      ],
      "source": [
        "!python /content/filter.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1pEyx1Yspycr",
        "outputId": "b5665e20-d877-4352-eebb-49c4a7419457"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "788M\t./datasets/COCO/val2017\n",
            "2.0M\t./datasets/COCO/my_custom_dataset_val/annotations\n",
            "150M\t./datasets/COCO/my_custom_dataset_val/images\n",
            "152M\t./datasets/COCO/my_custom_dataset_val\n",
            "796M\t./datasets/COCO/annotations\n",
            "1.7G\t./datasets/COCO\n",
            "1.7G\t./datasets/\n"
          ]
        }
      ],
      "source": [
        "!du -h ./datasets/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lA6GLDltra1t",
        "outputId": "e5d94921-e9cd-4d75-db08-7d0919409433"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "  adding: datasets/COCO/my_custom_dataset_val/ (stored 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/annotations/ (stored 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/annotations/coco_annotation.json (deflated 71%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/ (stored 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000008899.jpg (deflated 0%)\n",
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            "  adding: datasets/COCO/my_custom_dataset_val/images/000000463647.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000210273.jpg (deflated 6%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000037751.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000148719.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000426268.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000023272.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000344029.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000329614.jpg (deflated 1%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000143931.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000569030.jpg (deflated 0%)\n",
            "  adding: datasets/COCO/my_custom_dataset_val/images/000000314251.jpg (deflated 0%)\n"
          ]
        }
      ],
      "source": [
        "!zip -r data_val.zip ./datasets/COCO/my_custom_dataset_val"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eDivoSdUrkHE"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FlQFUILL6W4U",
        "outputId": "9075ca29-6a4b-4562-a840-26b7edd3e1f6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ok-uzI9t6Y19"
      },
      "outputs": [],
      "source": [
        "!cp data_val.zip ./drive/MyDrive"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ixD97bH16jTh"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "gpuType": "T4",
      "include_colab_link": true,
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}