python_hw2-pre-trained.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "OneNet.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/samuelFain/course-python_deep_learning/blob/main/python_hw2-pre-trained.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "afXzzm_jWM39",
        "outputId": "8aec7b4e-5690-45fe-a22b-b3efa37cf9e2"
      },
      "source": [
        "!git clone https://github.com/PeizeSun/OneNet.git"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'OneNet'...\n",
            "remote: Enumerating objects: 602, done.\u001b[K\n",
            "remote: Counting objects: 100% (602/602), done.\u001b[K\n",
            "remote: Compressing objects: 100% (499/499), done.\u001b[K\n",
            "remote: Total 602 (delta 135), reused 523 (delta 93), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (602/602), 1.50 MiB | 22.93 MiB/s, done.\n",
            "Resolving deltas: 100% (135/135), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ElvldoghMVV2"
      },
      "source": [
        "# Mount google drive "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9qYDtMqPV13b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3d5d8ad6-2338-4579-f7ac-3007ef1c6cc1"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6ArB46hUXgNC",
        "outputId": "d4648b00-5a9e-40f3-8f6a-280ed8770ce9"
      },
      "source": [
        "cd OneNet"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/OneNet\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CxGYhfl3rCy4"
      },
      "source": [
        "#  installing torchvison according to your cuda version"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ora4M9KThIwk",
        "outputId": "380eb0ce-15eb-4c69-cb7c-8e393f90bf42"
      },
      "source": [
        "!nvcc --version"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2020 NVIDIA Corporation\n",
            "Built on Wed_Jul_22_19:09:09_PDT_2020\n",
            "Cuda compilation tools, release 11.0, V11.0.221\n",
            "Build cuda_11.0_bu.TC445_37.28845127_0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aLOtDDDihcy0",
        "outputId": "d87d8559-e3cd-430e-e1a9-a34db800d190"
      },
      "source": [
        "pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio===0.7.2 -f https://download.pytorch.org/whl/torch_stable.html"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Collecting torch==1.7.1+cu101\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu101/torch-1.7.1%2Bcu101-cp37-cp37m-linux_x86_64.whl (735.4MB)\n",
            "\u001b[K     |████████████████████████████████| 735.4MB 25kB/s \n",
            "\u001b[?25hCollecting torchvision==0.8.2+cu101\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu101/torchvision-0.8.2%2Bcu101-cp37-cp37m-linux_x86_64.whl (12.8MB)\n",
            "\u001b[K     |████████████████████████████████| 12.8MB 65kB/s \n",
            "\u001b[?25hCollecting torchaudio===0.7.2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/37/16/ecdb9eb09ec6b8133d6c9536ea9e49cd13c9b5873c8488b8b765a39028da/torchaudio-0.7.2-cp37-cp37m-manylinux1_x86_64.whl (7.6MB)\n",
            "\u001b[K     |████████████████████████████████| 7.6MB 13.8MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch==1.7.1+cu101) (1.19.5)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.7.1+cu101) (3.7.4.3)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision==0.8.2+cu101) (7.1.2)\n",
            "\u001b[31mERROR: torchtext 0.9.1 has requirement torch==1.8.1, but you'll have torch 1.7.1+cu101 which is incompatible.\u001b[0m\n",
            "Installing collected packages: torch, torchvision, torchaudio\n",
            "  Found existing installation: torch 1.8.1+cu101\n",
            "    Uninstalling torch-1.8.1+cu101:\n",
            "      Successfully uninstalled torch-1.8.1+cu101\n",
            "  Found existing installation: torchvision 0.9.1+cu101\n",
            "    Uninstalling torchvision-0.9.1+cu101:\n",
            "      Successfully uninstalled torchvision-0.9.1+cu101\n",
            "Successfully installed torch-1.7.1+cu101 torchaudio-0.7.2 torchvision-0.8.2+cu101\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PwA0CZNlaxXg"
      },
      "source": [
        "# restart runtime after installing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SATmJGGiad0Q"
      },
      "source": [
        "!pip install pyyaml==5.1 pycocotools>=2.0.1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f5-hLPy_Zg9p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "83f79780-2c7f-4415-8792-a51010690be3"
      },
      "source": [
        "import torch, torchvision\n",
        "print(torch.__version__, torch.cuda.is_available())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.7.1+cu101 True\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IRMp5PH0ZaTQ"
      },
      "source": [
        "# install onenet"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VEOfkYVsW6ck",
        "outputId": "60fb1ba3-4a73-428b-ab70-fceca55e705a"
      },
      "source": [
        "!python setup.py build develop"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "running build\n",
            "running build_py\n",
            "creating build\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "creating build/lib.linux-x86_64-3.7/detectron2\n",
            "copying detectron2/__init__.py -> build/lib.linux-x86_64-3.7/detectron2\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/mask_ops.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/roi_align.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/shape_spec.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/nms.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/blocks.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/wrappers.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/roi_align_rotated.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/deform_conv.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/batch_norm.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/aspp.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "copying detectron2/layers/rotated_boxes.py -> build/lib.linux-x86_64-3.7/detectron2/layers\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/checkpoint\n",
            "copying detectron2/checkpoint/c2_model_loading.py -> build/lib.linux-x86_64-3.7/detectron2/checkpoint\n",
            "copying detectron2/checkpoint/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/checkpoint\n",
            "copying detectron2/checkpoint/detection_checkpoint.py -> build/lib.linux-x86_64-3.7/detectron2/checkpoint\n",
            "copying detectron2/checkpoint/catalog.py -> build/lib.linux-x86_64-3.7/detectron2/checkpoint\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/solver\n",
            "copying detectron2/solver/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/solver\n",
            "copying detectron2/solver/lr_scheduler.py -> build/lib.linux-x86_64-3.7/detectron2/solver\n",
            "copying detectron2/solver/build.py -> build/lib.linux-x86_64-3.7/detectron2/solver\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/env.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/testing.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/file_io.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/serialize.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/analysis.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/events.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/video_visualizer.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/visualizer.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/colormap.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/memory.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/comm.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/logger.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/registry.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "copying detectron2/utils/collect_env.py -> build/lib.linux-x86_64-3.7/detectron2/utils\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo\n",
            "copying detectron2/model_zoo/model_zoo.py -> build/lib.linux-x86_64-3.7/detectron2/model_zoo\n",
            "copying detectron2/model_zoo/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/model_zoo\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/config\n",
            "copying detectron2/config/config.py -> build/lib.linux-x86_64-3.7/detectron2/config\n",
            "copying detectron2/config/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/config\n",
            "copying detectron2/config/defaults.py -> build/lib.linux-x86_64-3.7/detectron2/config\n",
            "copying detectron2/config/compat.py -> build/lib.linux-x86_64-3.7/detectron2/config\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/torchscript_patch.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/c10.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/caffe2_export.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/shared.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/caffe2_patch.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/caffe2_inference.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/caffe2_modeling.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/torchscript.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "copying detectron2/export/api.py -> build/lib.linux-x86_64-3.7/detectron2/export\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/projects\n",
            "copying detectron2/projects/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/projects\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/panoptic_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/lvis_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/rotated_coco_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/testing.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/pascal_voc_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/sem_seg_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/evaluator.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/coco_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/fast_eval_api.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "copying detectron2/evaluation/cityscapes_evaluation.py -> build/lib.linux-x86_64-3.7/detectron2/evaluation\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/postprocessing.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/box_regression.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/test_time_augmentation.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/poolers.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/matcher.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/sampling.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "copying detectron2/modeling/anchor_generator.py -> build/lib.linux-x86_64-3.7/detectron2/modeling\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "copying detectron2/engine/hooks.py -> build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "copying detectron2/engine/train_loop.py -> build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "copying detectron2/engine/launch.py -> build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "copying detectron2/engine/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "copying detectron2/engine/defaults.py -> build/lib.linux-x86_64-3.7/detectron2/engine\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/keypoints.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/boxes.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/image_list.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/instances.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/masks.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "copying detectron2/structures/rotated_boxes.py -> build/lib.linux-x86_64-3.7/detectron2/structures\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/detection_utils.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/common.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/dataset_mapper.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/catalog.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "copying detectron2/data/build.py -> build/lib.linux-x86_64-3.7/detectron2/data\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/box_head.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/cascade_rcnn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/roi_heads.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/fast_rcnn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/rotated_fast_rcnn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/keypoint_head.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "copying detectron2/modeling/roi_heads/mask_head.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/roi_heads\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "copying detectron2/modeling/backbone/fpn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "copying detectron2/modeling/backbone/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "copying detectron2/modeling/backbone/resnet.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "copying detectron2/modeling/backbone/backbone.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "copying detectron2/modeling/backbone/build.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/backbone\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/panoptic_fpn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/semantic_seg.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/retinanet.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/rcnn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "copying detectron2/modeling/meta_arch/build.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/meta_arch\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "copying detectron2/modeling/proposal_generator/proposal_utils.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "copying detectron2/modeling/proposal_generator/rpn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "copying detectron2/modeling/proposal_generator/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "copying detectron2/modeling/proposal_generator/rrpn.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "copying detectron2/modeling/proposal_generator/build.py -> build/lib.linux-x86_64-3.7/detectron2/modeling/proposal_generator\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/data/samplers\n",
            "copying detectron2/data/samplers/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/data/samplers\n",
            "copying detectron2/data/samplers/distributed_sampler.py -> build/lib.linux-x86_64-3.7/detectron2/data/samplers\n",
            "copying detectron2/data/samplers/grouped_batch_sampler.py -> build/lib.linux-x86_64-3.7/detectron2/data/samplers\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/data/transforms\n",
            "copying detectron2/data/transforms/augmentation.py -> build/lib.linux-x86_64-3.7/detectron2/data/transforms\n",
            "copying detectron2/data/transforms/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/data/transforms\n",
            "copying detectron2/data/transforms/augmentation_impl.py -> build/lib.linux-x86_64-3.7/detectron2/data/transforms\n",
            "copying detectron2/data/transforms/transform.py -> build/lib.linux-x86_64-3.7/detectron2/data/transforms\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/coco.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/lvis_v0_5_categories.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/coco_panoptic.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/lvis.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/builtin.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/pascal_voc.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/lvis_v1_categories.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/__init__.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/cityscapes_panoptic.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/builtin_meta.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/cityscapes.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "copying detectron2/data/datasets/register_coco.py -> build/lib.linux-x86_64-3.7/detectron2/data/datasets\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs\n",
            "copying detectron2/model_zoo/configs/Base-RCNN-FPN.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs\n",
            "copying detectron2/model_zoo/configs/Base-RCNN-DilatedC5.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs\n",
            "copying detectron2/model_zoo/configs/Base-RetinaNet.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs\n",
            "copying detectron2/model_zoo/configs/Base-RCNN-C4.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/PascalVOC-Detection\n",
            "copying detectron2/model_zoo/configs/PascalVOC-Detection/faster_rcnn_R_50_FPN.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/PascalVOC-Detection\n",
            "copying detectron2/model_zoo/configs/PascalVOC-Detection/faster_rcnn_R_50_C4.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/PascalVOC-Detection\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_R_101_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_R_101_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/Base-Panoptic-FPN.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_101_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Cityscapes\n",
            "copying detectron2/model_zoo/configs/Cityscapes/mask_rcnn_R_50_FPN.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Cityscapes\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/retinanet_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_GCV_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_pred_boxes_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_DC5_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/retinanet_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/rpn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_normalized_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/rpn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/quick_schedules\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_DC5_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_DC5_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/fast_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/rpn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_C4_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_DC5_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_C4_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/rpn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection/zhang\n",
            "copying detectron2/model_zoo/configs/COCO-Detection/zhang/faster_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Detection/zhang\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "copying detectron2/model_zoo/configs/COCO-Keypoints/Base-Keypoint-RCNN-FPN.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-Keypoints\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
            "copying detectron2/model_zoo/configs/Detectron1-Comparisons/faster_rcnn_R_50_FPN_noaug_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
            "copying detectron2/model_zoo/configs/Detectron1-Comparisons/mask_rcnn_R_50_FPN_noaug_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
            "copying detectron2/model_zoo/configs/Detectron1-Comparisons/keypoint_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_C4_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x_giou.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_C4_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_DC5_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
            "creating build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_9x_gn.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_1x_cls_agnostic.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_1x_dconv_c3-c5.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_dconv_c3-c5.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_gn.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_X_152_32x8d_FPN_IN5k_gn_dconv.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/panoptic_fpn_R_101_dconv_cascade_gn_3x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/semantic_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_9x_syncbn.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_syncbn.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_3x_gn.yaml -> build/lib.linux-x86_64-3.7/detectron2/model_zoo/configs/Misc\n",
            "running build_ext\n",
            "/usr/local/lib/python3.7/dist-packages/torch/utils/cpp_extension.py:352: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
            "  warnings.warn(msg.format('we could not find ninja.'))\n",
            "building 'detectron2._C' extension\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/content\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/nms_rotated\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlign\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlignRotated\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/box_iou_rotated\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/cocoeval\n",
            "creating build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/deformable\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/vision.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/vision.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Parallel.h:149:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/utils.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/nn.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:12\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/content/OneNet/detectron2/layers/csrc/vision.cpp:3\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ParallelOpenMP.h:84:0:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kignoring #pragma omp parallel [\u001b[01;35m\u001b[K-Wunknown-pragmas\u001b[m\u001b[K]\n",
            " #pragma omp parallel for if ((end - begin) >= grain_size)\n",
            " \n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.cpp -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cuda.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cuda.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cuda.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda_kernel.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/boxing/impl/boxing.h(100): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/core/op_registration/op_whitelist.h(39): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cuda.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c /content/OneNet/detectron2/layers/csrc/cuda_version.cu -o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/cuda_version.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++14\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-OGiuun/python3.7-3.7.10=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/vision.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cuda.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cuda.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cuda.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda_kernel.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/deformable/deform_conv_cuda.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cuda.o build/temp.linux-x86_64-3.7/content/OneNet/detectron2/layers/csrc/cuda_version.o -L/usr/local/lib/python3.7/dist-packages/torch/lib -L/usr/local/cuda/lib64 -lc10 -ltorch -ltorch_cpu -ltorch_python -lcudart -lc10_cuda -ltorch_cuda -o build/lib.linux-x86_64-3.7/detectron2/_C.cpython-37m-x86_64-linux-gnu.so\n",
            "running develop\n",
            "running egg_info\n",
            "creating detectron2.egg-info\n",
            "writing detectron2.egg-info/PKG-INFO\n",
            "writing dependency_links to detectron2.egg-info/dependency_links.txt\n",
            "writing requirements to detectron2.egg-info/requires.txt\n",
            "writing top-level names to detectron2.egg-info/top_level.txt\n",
            "writing manifest file 'detectron2.egg-info/SOURCES.txt'\n",
            "adding license file 'LICENSE' (matched pattern 'LICEN[CS]E*')\n",
            "writing manifest file 'detectron2.egg-info/SOURCES.txt'\n",
            "running build_ext\n",
            "copying build/lib.linux-x86_64-3.7/detectron2/_C.cpython-37m-x86_64-linux-gnu.so -> detectron2\n",
            "Creating /usr/local/lib/python3.7/dist-packages/detectron2.egg-link (link to .)\n",
            "Adding detectron2 0.3 to easy-install.pth file\n",
            "\n",
            "Installed /content/OneNet\n",
            "Processing dependencies for detectron2==0.3\n",
            "Searching for fvcore>=0.1.1\n",
            "Reading https://pypi.org/simple/fvcore/\n",
            "Downloading https://files.pythonhosted.org/packages/77/82/833257ef5192421c667f47b575bd90a9458949d1dee87fc3e84405d0300a/fvcore-0.1.5.post20210518.tar.gz#sha256=bfface25eb017011324e0c4649440591178c6ba72d0d0719255f8f7828ba8941\n",
            "Best match: fvcore 0.1.5.post20210518\n",
            "Processing fvcore-0.1.5.post20210518.tar.gz\n",
            "Writing /tmp/easy_install-dw7m3qkp/fvcore-0.1.5.post20210518/setup.cfg\n",
            "Running fvcore-0.1.5.post20210518/setup.py -q bdist_egg --dist-dir /tmp/easy_install-dw7m3qkp/fvcore-0.1.5.post20210518/egg-dist-tmp-rlxmncvd\n",
            "zip_safe flag not set; analyzing archive contents...\n",
            "Moving fvcore-0.1.5.post20210518-py3.7.egg to /usr/local/lib/python3.7/dist-packages\n",
            "Adding fvcore 0.1.5.post20210518 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/fvcore-0.1.5.post20210518-py3.7.egg\n",
            "Searching for mock\n",
            "Reading https://pypi.org/simple/mock/\n",
            "Downloading https://files.pythonhosted.org/packages/5c/03/b7e605db4a57c0f6fba744b11ef3ddf4ddebcada35022927a2b5fc623fdf/mock-4.0.3-py3-none-any.whl#sha256=122fcb64ee37cfad5b3f48d7a7d51875d7031aaf3d8be7c42e2bee25044eee62\n",
            "Best match: mock 4.0.3\n",
            "Processing mock-4.0.3-py3-none-any.whl\n",
            "Installing mock-4.0.3-py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding mock 4.0.3 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/mock-4.0.3-py3.7.egg\n",
            "Searching for yacs>=0.1.6\n",
            "Reading https://pypi.org/simple/yacs/\n",
            "Downloading https://files.pythonhosted.org/packages/38/4f/fe9a4d472aa867878ce3bb7efb16654c5d63672b86dc0e6e953a67018433/yacs-0.1.8-py3-none-any.whl#sha256=99f893e30497a4b66842821bac316386f7bd5c4f47ad35c9073ef089aa33af32\n",
            "Best match: yacs 0.1.8\n",
            "Processing yacs-0.1.8-py3-none-any.whl\n",
            "Installing yacs-0.1.8-py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding yacs 0.1.8 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/yacs-0.1.8-py3.7.egg\n",
            "Searching for iopath>=0.1.7\n",
            "Reading https://pypi.org/simple/iopath/\n",
            "Downloading https://files.pythonhosted.org/packages/21/d0/22104caed16fa41382702fed959f4a9b088b2f905e7a82e4483180a2ec2a/iopath-0.1.8-py3-none-any.whl#sha256=e11029c30ee77616b3efd82888aa80941d12afcc5940c2ef57e04a8e93a10f9f\n",
            "Best match: iopath 0.1.8\n",
            "Processing iopath-0.1.8-py3-none-any.whl\n",
            "Installing iopath-0.1.8-py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding iopath 0.1.8 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/iopath-0.1.8-py3.7.egg\n",
            "Searching for portalocker\n",
            "Reading https://pypi.org/simple/portalocker/\n",
            "Downloading https://files.pythonhosted.org/packages/68/33/cb524f4de298509927b90aa5ee34767b9a2b93e663cf354b2a3efa2b4acd/portalocker-2.3.0-py2.py3-none-any.whl#sha256=1d43fd8223e1743f5725e8910f69e7a45858ffd298e19252633ac903eafd83bc\n",
            "Best match: portalocker 2.3.0\n",
            "Processing portalocker-2.3.0-py2.py3-none-any.whl\n",
            "Installing portalocker-2.3.0-py2.py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding portalocker 2.3.0 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/portalocker-2.3.0-py3.7.egg\n",
            "Searching for pydot==1.3.0\n",
            "Best match: pydot 1.3.0\n",
            "Adding pydot 1.3.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for future==0.16.0\n",
            "Best match: future 0.16.0\n",
            "Adding future 0.16.0 to easy-install.pth file\n",
            "Installing futurize script to /usr/local/bin\n",
            "Installing pasteurize script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for pycocotools==2.0.2\n",
            "Best match: pycocotools 2.0.2\n",
            "Adding pycocotools 2.0.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tensorboard==2.5.0\n",
            "Best match: tensorboard 2.5.0\n",
            "Adding tensorboard 2.5.0 to easy-install.pth file\n",
            "Installing tensorboard script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tqdm==4.41.1\n",
            "Best match: tqdm 4.41.1\n",
            "Adding tqdm 4.41.1 to easy-install.pth file\n",
            "Installing tqdm script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for matplotlib==3.2.2\n",
            "Best match: matplotlib 3.2.2\n",
            "Adding matplotlib 3.2.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for cloudpickle==1.3.0\n",
            "Best match: cloudpickle 1.3.0\n",
            "Adding cloudpickle 1.3.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tabulate==0.8.9\n",
            "Best match: tabulate 0.8.9\n",
            "Adding tabulate 0.8.9 to easy-install.pth file\n",
            "Installing tabulate script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Pillow==7.1.2\n",
            "Best match: Pillow 7.1.2\n",
            "Adding Pillow 7.1.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for termcolor==1.1.0\n",
            "Best match: termcolor 1.1.0\n",
            "Adding termcolor 1.1.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for pyparsing==2.4.7\n",
            "Best match: pyparsing 2.4.7\n",
            "Adding pyparsing 2.4.7 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for setuptools==56.1.0\n",
            "Best match: setuptools 56.1.0\n",
            "Adding setuptools 56.1.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Cython==0.29.23\n",
            "Best match: Cython 0.29.23\n",
            "Adding Cython 0.29.23 to easy-install.pth file\n",
            "Installing cygdb script to /usr/local/bin\n",
            "Installing cython script to /usr/local/bin\n",
            "Installing cythonize script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for PyYAML==5.1\n",
            "Best match: PyYAML 5.1\n",
            "Adding PyYAML 5.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for numpy==1.19.5\n",
            "Best match: numpy 1.19.5\n",
            "Adding numpy 1.19.5 to easy-install.pth file\n",
            "Installing f2py script to /usr/local/bin\n",
            "Installing f2py3 script to /usr/local/bin\n",
            "Installing f2py3.7 script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Markdown==3.3.4\n",
            "Best match: Markdown 3.3.4\n",
            "Adding Markdown 3.3.4 to easy-install.pth file\n",
            "Installing markdown_py script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tensorboard-data-server==0.6.1\n",
            "Best match: tensorboard-data-server 0.6.1\n",
            "Adding tensorboard-data-server 0.6.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Werkzeug==1.0.1\n",
            "Best match: Werkzeug 1.0.1\n",
            "Adding Werkzeug 1.0.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for wheel==0.36.2\n",
            "Best match: wheel 0.36.2\n",
            "Adding wheel 0.36.2 to easy-install.pth file\n",
            "Installing wheel script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for requests==2.23.0\n",
            "Best match: requests 2.23.0\n",
            "Adding requests 2.23.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for protobuf==3.12.4\n",
            "Best match: protobuf 3.12.4\n",
            "Adding protobuf 3.12.4 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for google-auth==1.30.0\n",
            "Best match: google-auth 1.30.0\n",
            "Adding google-auth 1.30.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tensorboard-plugin-wit==1.8.0\n",
            "Best match: tensorboard-plugin-wit 1.8.0\n",
            "Adding tensorboard-plugin-wit 1.8.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for absl-py==0.12.0\n",
            "Best match: absl-py 0.12.0\n",
            "Adding absl-py 0.12.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for grpcio==1.34.1\n",
            "Best match: grpcio 1.34.1\n",
            "Adding grpcio 1.34.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for google-auth-oauthlib==0.4.4\n",
            "Best match: google-auth-oauthlib 0.4.4\n",
            "Adding google-auth-oauthlib 0.4.4 to easy-install.pth file\n",
            "Installing google-oauthlib-tool script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for kiwisolver==1.3.1\n",
            "Best match: kiwisolver 1.3.1\n",
            "Adding kiwisolver 1.3.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for cycler==0.10.0\n",
            "Best match: cycler 0.10.0\n",
            "Adding cycler 0.10.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for python-dateutil==2.8.1\n",
            "Best match: python-dateutil 2.8.1\n",
            "Adding python-dateutil 2.8.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for importlib-metadata==4.0.1\n",
            "Best match: importlib-metadata 4.0.1\n",
            "Adding importlib-metadata 4.0.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for chardet==3.0.4\n",
            "Best match: chardet 3.0.4\n",
            "Adding chardet 3.0.4 to easy-install.pth file\n",
            "Installing chardetect script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for idna==2.10\n",
            "Best match: idna 2.10\n",
            "Adding idna 2.10 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for urllib3==1.24.3\n",
            "Best match: urllib3 1.24.3\n",
            "Adding urllib3 1.24.3 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for certifi==2020.12.5\n",
            "Best match: certifi 2020.12.5\n",
            "Adding certifi 2020.12.5 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for six==1.15.0\n",
            "Best match: six 1.15.0\n",
            "Adding six 1.15.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for cachetools==4.2.2\n",
            "Best match: cachetools 4.2.2\n",
            "Adding cachetools 4.2.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for rsa==4.7.2\n",
            "Best match: rsa 4.7.2\n",
            "Adding rsa 4.7.2 to easy-install.pth file\n",
            "Installing pyrsa-decrypt script to /usr/local/bin\n",
            "Installing pyrsa-encrypt script to /usr/local/bin\n",
            "Installing pyrsa-keygen script to /usr/local/bin\n",
            "Installing pyrsa-priv2pub script to /usr/local/bin\n",
            "Installing pyrsa-sign script to /usr/local/bin\n",
            "Installing pyrsa-verify script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for pyasn1-modules==0.2.8\n",
            "Best match: pyasn1-modules 0.2.8\n",
            "Adding pyasn1-modules 0.2.8 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for requests-oauthlib==1.3.0\n",
            "Best match: requests-oauthlib 1.3.0\n",
            "Adding requests-oauthlib 1.3.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for zipp==3.4.1\n",
            "Best match: zipp 3.4.1\n",
            "Adding zipp 3.4.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for typing-extensions==3.7.4.3\n",
            "Best match: typing-extensions 3.7.4.3\n",
            "Adding typing-extensions 3.7.4.3 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for pyasn1==0.4.8\n",
            "Best match: pyasn1 0.4.8\n",
            "Adding pyasn1 0.4.8 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for oauthlib==3.1.0\n",
            "Best match: oauthlib 3.1.0\n",
            "Adding oauthlib 3.1.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Finished processing dependencies for detectron2==0.3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EZ4aOsnUqdeL"
      },
      "source": [
        "# link coco datset to OneNet dateset folder\n",
        "## download COCO dataset and then link the folder with OneNet ---Irrelevant---"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6TNWAF7bW_bN"
      },
      "source": [
        "#!mkdir -p datasets/coco\n",
        "#!ln -s /content/drive/MyDrive/deepLearning/COCO/2017/annotations datasets/coco/annotations\n",
        "#!ln -s /content/drive/MyDrive/deepLearning/COCO/2017/train2017 datasets/coco/train2017\n",
        "#!ln -s /content/drive/MyDrive/deepLearning/COCO/2017/val2017 datasets/coco/val2017"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "01kNsDsFb0ry",
        "outputId": "c142c010-640b-46f6-b4c0-fe6e1adc8276"
      },
      "source": [
        "pip install -U iopath"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already up-to-date: iopath in /usr/local/lib/python3.7/dist-packages/iopath-0.1.8-py3.7.egg (0.1.8)\n",
            "Requirement already satisfied, skipping upgrade: portalocker in /usr/local/lib/python3.7/dist-packages/portalocker-2.3.0-py3.7.egg (from iopath) (2.3.0)\n",
            "Requirement already satisfied, skipping upgrade: tqdm in /usr/local/lib/python3.7/dist-packages (from iopath) (4.41.1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qQOQZKS5rI3J"
      },
      "source": [
        "# train ONeNet ---Irrelevant---"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T9_MTAAQXrIl"
      },
      "source": [
        "#!python projects/OneNet/train_net.py --num-gpus 1 \\\n",
        "#   --config-file /content/OneNet/projects/OneNet/configs/onenet.res18.dcn.yaml"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FEQFguZWrMRm"
      },
      "source": [
        "# Evaluate - give path to pre-trained onenet_r18dcn in google drive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-cm7zqKrYJlj",
        "outputId": "b12ead37-a403-45aa-f896-1722aa236545"
      },
      "source": [
        "!python projects/OneNet/train_net.py --num-gpus 1 \\\n",
        "    --config-file projects/OneNet/configs/onenet.res18.dcn.yaml \\\n",
        "    --eval-only MODEL.WEIGHTS /content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Command Line Args: Namespace(config_file='projects/OneNet/configs/onenet.res18.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=True, machine_rank=0, num_gpus=1, num_machines=1, opts=['MODEL.WEIGHTS', '/content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth'], resume=False)\n",
            "\u001b[32m[06/01 13:22:33 detectron2]: \u001b[0mRank of current process: 0. World size: 1\n",
            "\u001b[32m[06/01 13:22:34 detectron2]: \u001b[0mEnvironment info:\n",
            "----------------------  ---------------------------------------------------------------\n",
            "sys.platform            linux\n",
            "Python                  3.7.10 (default, May  3 2021, 02:48:31) [GCC 7.5.0]\n",
            "numpy                   1.19.5\n",
            "detectron2              0.3 @/content/OneNet/detectron2\n",
            "Compiler                GCC 7.5\n",
            "CUDA compiler           CUDA 11.0\n",
            "detectron2 arch flags   6.0\n",
            "DETECTRON2_ENV_MODULE   <not set>\n",
            "PyTorch                 1.7.1+cu101 @/usr/local/lib/python3.7/dist-packages/torch\n",
            "PyTorch debug build     False\n",
            "GPU available           True\n",
            "GPU 0                   Tesla P100-PCIE-16GB (arch=6.0)\n",
            "CUDA_HOME               /usr/local/cuda\n",
            "Pillow                  7.1.2\n",
            "torchvision             0.8.2+cu101 @/usr/local/lib/python3.7/dist-packages/torchvision\n",
            "torchvision arch flags  3.5, 5.0, 6.0, 7.0, 7.5\n",
            "fvcore                  0.1.5.post20210518\n",
            "cv2                     4.1.2\n",
            "----------------------  ---------------------------------------------------------------\n",
            "PyTorch built with:\n",
            "  - GCC 7.3\n",
            "  - C++ Version: 201402\n",
            "  - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications\n",
            "  - Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)\n",
            "  - OpenMP 201511 (a.k.a. OpenMP 4.5)\n",
            "  - NNPACK is enabled\n",
            "  - CPU capability usage: AVX2\n",
            "  - CUDA Runtime 10.1\n",
            "  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75\n",
            "  - CuDNN 7.6.3\n",
            "  - Magma 2.5.2\n",
            "  - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, \n",
            "\n",
            "\u001b[32m[06/01 13:22:34 detectron2]: \u001b[0mCommand line arguments: Namespace(config_file='projects/OneNet/configs/onenet.res18.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=True, machine_rank=0, num_gpus=1, num_machines=1, opts=['MODEL.WEIGHTS', '/content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth'], resume=False)\n",
            "\u001b[32m[06/01 13:22:34 detectron2]: \u001b[0mContents of args.config_file=projects/OneNet/configs/onenet.res18.dcn.yaml:\n",
            "_BASE_: \"Base-OneNet.yaml\"\n",
            "MODEL:\n",
            "  WEIGHTS: \"torchvision-R-18.pkl\"\n",
            "  BACKBONE:\n",
            "      FREEZE_AT: 0\n",
            "  RESNETS:\n",
            "    NORM: \"BN\"\n",
            "    DEPTH: 18\n",
            "    STRIDE_IN_1X1: False\n",
            "    RES2_OUT_CHANNELS: 64\n",
            "  OneNet:\n",
            "    DCN: True\n",
            "    NUM_CLASSES: 80\n",
            "    DECONV_CHANNEL: (512, 256, 128, 64)\n",
            "DATASETS:\n",
            "  TRAIN: (\"coco_2017_train\",)\n",
            "  TEST:  (\"coco_2017_val\",)\n",
            "SOLVER:\n",
            "  IMS_PER_BATCH: 64\n",
            "  STEPS: (210000, 250000)\n",
            "  MAX_ITER: 270000\n",
            "INPUT:\n",
            "  CROP:\n",
            "    ENABLED: True\n",
            "  FORMAT: \"RGB\"\n",
            "OUTPUT_DIR: 'output_onenet_r18dcn'\n",
            "\n",
            "\u001b[32m[06/01 13:22:34 detectron2]: \u001b[0mRunning with full config:\n",
            "CUDNN_BENCHMARK: False\n",
            "DATALOADER:\n",
            "  ASPECT_RATIO_GROUPING: True\n",
            "  FILTER_EMPTY_ANNOTATIONS: False\n",
            "  NUM_WORKERS: 4\n",
            "  REPEAT_THRESHOLD: 0.0\n",
            "  SAMPLER_TRAIN: TrainingSampler\n",
            "DATASETS:\n",
            "  PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000\n",
            "  PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000\n",
            "  PROPOSAL_FILES_TEST: ()\n",
            "  PROPOSAL_FILES_TRAIN: ()\n",
            "  TEST: ('coco_2017_val',)\n",
            "  TRAIN: ('coco_2017_train',)\n",
            "GLOBAL:\n",
            "  HACK: 1.0\n",
            "INPUT:\n",
            "  CROP:\n",
            "    ENABLED: True\n",
            "    SIZE: [384, 600]\n",
            "    TYPE: absolute_range\n",
            "  FORMAT: RGB\n",
            "  MASK_FORMAT: polygon\n",
            "  MAX_SIZE_TEST: 853\n",
            "  MAX_SIZE_TRAIN: 853\n",
            "  MIN_SIZE_TEST: 512\n",
            "  MIN_SIZE_TRAIN: (416, 448, 480, 512)\n",
            "  MIN_SIZE_TRAIN_SAMPLING: choice\n",
            "  RANDOM_FLIP: horizontal\n",
            "MODEL:\n",
            "  ANCHOR_GENERATOR:\n",
            "    ANGLES: [[-90, 0, 90]]\n",
            "    ASPECT_RATIOS: [[0.5, 1.0, 2.0]]\n",
            "    NAME: DefaultAnchorGenerator\n",
            "    OFFSET: 0.0\n",
            "    SIZES: [[32, 64, 128, 256, 512]]\n",
            "  BACKBONE:\n",
            "    FREEZE_AT: 0\n",
            "    NAME: build_resnet_backbone\n",
            "  DEVICE: cuda\n",
            "  FPN:\n",
            "    FUSE_TYPE: sum\n",
            "    IN_FEATURES: []\n",
            "    NORM: \n",
            "    OUT_CHANNELS: 256\n",
            "  KEYPOINT_ON: False\n",
            "  LOAD_PROPOSALS: False\n",
            "  MASK_ON: False\n",
            "  META_ARCHITECTURE: OneNet\n",
            "  OneNet:\n",
            "    ACTIVATION: relu\n",
            "    ALPHA: 0.25\n",
            "    CLASS_WEIGHT: 2.0\n",
            "    DCN: True\n",
            "    DECONV_CHANNEL: [512, 256, 128, 64]\n",
            "    DECONV_KERNEL: [4, 4, 4]\n",
            "    GAMMA: 2.0\n",
            "    GIOU_WEIGHT: 2.0\n",
            "    IN_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
            "    L1_WEIGHT: 5.0\n",
            "    MODULATE_DEFORM: True\n",
            "    NMS: False\n",
            "    NUM_CLASSES: 80\n",
            "    PRIOR_PROB: 0.01\n",
            "  PANOPTIC_FPN:\n",
            "    COMBINE:\n",
            "      ENABLED: True\n",
            "      INSTANCES_CONFIDENCE_THRESH: 0.5\n",
            "      OVERLAP_THRESH: 0.5\n",
            "      STUFF_AREA_LIMIT: 4096\n",
            "    INSTANCE_LOSS_WEIGHT: 1.0\n",
            "  PIXEL_MEAN: [123.675, 116.28, 103.53]\n",
            "  PIXEL_STD: [58.395, 57.12, 57.375]\n",
            "  PROPOSAL_GENERATOR:\n",
            "    MIN_SIZE: 0\n",
            "    NAME: RPN\n",
            "  RESNETS:\n",
            "    DEFORM_MODULATED: False\n",
            "    DEFORM_NUM_GROUPS: 1\n",
            "    DEFORM_ON_PER_STAGE: [False, False, False, False]\n",
            "    DEPTH: 18\n",
            "    NORM: BN\n",
            "    NUM_GROUPS: 1\n",
            "    OUT_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
            "    RES2_OUT_CHANNELS: 64\n",
            "    RES5_DILATION: 1\n",
            "    STEM_OUT_CHANNELS: 64\n",
            "    STRIDE_IN_1X1: False\n",
            "    WIDTH_PER_GROUP: 64\n",
            "  RETINANET:\n",
            "    BBOX_REG_LOSS_TYPE: smooth_l1\n",
            "    BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
            "    FOCAL_LOSS_ALPHA: 0.25\n",
            "    FOCAL_LOSS_GAMMA: 2.0\n",
            "    IN_FEATURES: ['p3', 'p4', 'p5', 'p6', 'p7']\n",
            "    IOU_LABELS: [0, -1, 1]\n",
            "    IOU_THRESHOLDS: [0.4, 0.5]\n",
            "    NMS_THRESH_TEST: 0.5\n",
            "    NORM: \n",
            "    NUM_CLASSES: 80\n",
            "    NUM_CONVS: 4\n",
            "    PRIOR_PROB: 0.01\n",
            "    SCORE_THRESH_TEST: 0.05\n",
            "    SMOOTH_L1_LOSS_BETA: 0.1\n",
            "    TOPK_CANDIDATES_TEST: 1000\n",
            "  ROI_BOX_CASCADE_HEAD:\n",
            "    BBOX_REG_WEIGHTS: ((10.0, 10.0, 5.0, 5.0), (20.0, 20.0, 10.0, 10.0), (30.0, 30.0, 15.0, 15.0))\n",
            "    IOUS: (0.5, 0.6, 0.7)\n",
            "  ROI_BOX_HEAD:\n",
            "    BBOX_REG_LOSS_TYPE: smooth_l1\n",
            "    BBOX_REG_LOSS_WEIGHT: 1.0\n",
            "    BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0)\n",
            "    CLS_AGNOSTIC_BBOX_REG: False\n",
            "    CONV_DIM: 256\n",
            "    FC_DIM: 1024\n",
            "    NAME: \n",
            "    NORM: \n",
            "    NUM_CONV: 0\n",
            "    NUM_FC: 0\n",
            "    POOLER_RESOLUTION: 14\n",
            "    POOLER_SAMPLING_RATIO: 0\n",
            "    POOLER_TYPE: ROIAlignV2\n",
            "    SMOOTH_L1_BETA: 0.0\n",
            "    TRAIN_ON_PRED_BOXES: False\n",
            "  ROI_HEADS:\n",
            "    BATCH_SIZE_PER_IMAGE: 512\n",
            "    IN_FEATURES: ['res4']\n",
            "    IOU_LABELS: [0, 1]\n",
            "    IOU_THRESHOLDS: [0.5]\n",
            "    NAME: Res5ROIHeads\n",
            "    NMS_THRESH_TEST: 0.5\n",
            "    NUM_CLASSES: 80\n",
            "    POSITIVE_FRACTION: 0.25\n",
            "    PROPOSAL_APPEND_GT: True\n",
            "    SCORE_THRESH_TEST: 0.05\n",
            "  ROI_KEYPOINT_HEAD:\n",
            "    CONV_DIMS: (512, 512, 512, 512, 512, 512, 512, 512)\n",
            "    LOSS_WEIGHT: 1.0\n",
            "    MIN_KEYPOINTS_PER_IMAGE: 1\n",
            "    NAME: KRCNNConvDeconvUpsampleHead\n",
            "    NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: True\n",
            "    NUM_KEYPOINTS: 17\n",
            "    POOLER_RESOLUTION: 14\n",
            "    POOLER_SAMPLING_RATIO: 0\n",
            "    POOLER_TYPE: ROIAlignV2\n",
            "  ROI_MASK_HEAD:\n",
            "    CLS_AGNOSTIC_MASK: False\n",
            "    CONV_DIM: 256\n",
            "    NAME: MaskRCNNConvUpsampleHead\n",
            "    NORM: \n",
            "    NUM_CONV: 0\n",
            "    POOLER_RESOLUTION: 14\n",
            "    POOLER_SAMPLING_RATIO: 0\n",
            "    POOLER_TYPE: ROIAlignV2\n",
            "  RPN:\n",
            "    BATCH_SIZE_PER_IMAGE: 256\n",
            "    BBOX_REG_LOSS_TYPE: smooth_l1\n",
            "    BBOX_REG_LOSS_WEIGHT: 1.0\n",
            "    BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
            "    BOUNDARY_THRESH: -1\n",
            "    HEAD_NAME: StandardRPNHead\n",
            "    IN_FEATURES: ['res4']\n",
            "    IOU_LABELS: [0, -1, 1]\n",
            "    IOU_THRESHOLDS: [0.3, 0.7]\n",
            "    LOSS_WEIGHT: 1.0\n",
            "    NMS_THRESH: 0.7\n",
            "    POSITIVE_FRACTION: 0.5\n",
            "    POST_NMS_TOPK_TEST: 1000\n",
            "    POST_NMS_TOPK_TRAIN: 2000\n",
            "    PRE_NMS_TOPK_TEST: 6000\n",
            "    PRE_NMS_TOPK_TRAIN: 12000\n",
            "    SMOOTH_L1_BETA: 0.0\n",
            "  SEM_SEG_HEAD:\n",
            "    COMMON_STRIDE: 4\n",
            "    CONVS_DIM: 128\n",
            "    IGNORE_VALUE: 255\n",
            "    IN_FEATURES: ['p2', 'p3', 'p4', 'p5']\n",
            "    LOSS_WEIGHT: 1.0\n",
            "    NAME: SemSegFPNHead\n",
            "    NORM: GN\n",
            "    NUM_CLASSES: 54\n",
            "  WEIGHTS: /content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth\n",
            "OUTPUT_DIR: output_onenet_r18dcn\n",
            "SEED: 40244023\n",
            "SOLVER:\n",
            "  AMP:\n",
            "    ENABLED: False\n",
            "  BACKBONE_MULTIPLIER: 1.0\n",
            "  BASE_LR: 5e-05\n",
            "  BIAS_LR_FACTOR: 1.0\n",
            "  CHECKPOINT_PERIOD: 5000\n",
            "  CLIP_GRADIENTS:\n",
            "    CLIP_TYPE: full_model\n",
            "    CLIP_VALUE: 1.0\n",
            "    ENABLED: False\n",
            "    NORM_TYPE: 2.0\n",
            "  GAMMA: 0.1\n",
            "  IMS_PER_BATCH: 64\n",
            "  LR_SCHEDULER_NAME: WarmupMultiStepLR\n",
            "  MAX_ITER: 270000\n",
            "  MOMENTUM: 0.9\n",
            "  NESTEROV: False\n",
            "  OPTIMIZER: ADAMW\n",
            "  REFERENCE_WORLD_SIZE: 0\n",
            "  STEPS: (210000, 250000)\n",
            "  WARMUP_FACTOR: 0.01\n",
            "  WARMUP_ITERS: 1000\n",
            "  WARMUP_METHOD: linear\n",
            "  WEIGHT_DECAY: 0.0001\n",
            "  WEIGHT_DECAY_BIAS: 0.0001\n",
            "  WEIGHT_DECAY_NORM: 0.0\n",
            "TEST:\n",
            "  AUG:\n",
            "    ENABLED: False\n",
            "    FLIP: True\n",
            "    MAX_SIZE: 4000\n",
            "    MIN_SIZES: (400, 500, 600, 700, 800, 900, 1000, 1100, 1200)\n",
            "  DETECTIONS_PER_IMAGE: 100\n",
            "  EVAL_PERIOD: 7330\n",
            "  EXPECTED_RESULTS: []\n",
            "  KEYPOINT_OKS_SIGMAS: []\n",
            "  PRECISE_BN:\n",
            "    ENABLED: False\n",
            "    NUM_ITER: 200\n",
            "VERSION: 2\n",
            "VIS_PERIOD: 0\n",
            "\u001b[32m[06/01 13:22:34 detectron2]: \u001b[0mFull config saved to output_onenet_r18dcn/config.yaml\n",
            "\u001b[32m[06/01 13:22:36 d2.engine.defaults]: \u001b[0mModel:\n",
            "OneNet(\n",
            "  (backbone): ResNet(\n",
            "    (stem): BasicStem(\n",
            "      (conv1): Conv2d(\n",
            "        3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False\n",
            "        (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "      )\n",
            "    )\n",
            "    (res2): Sequential(\n",
            "      (0): BasicBlock(\n",
            "        (conv1): Conv2d(\n",
            "          64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "      (1): BasicBlock(\n",
            "        (conv1): Conv2d(\n",
            "          64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (res3): Sequential(\n",
            "      (0): BasicBlock(\n",
            "        (shortcut): Conv2d(\n",
            "          64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
            "          (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv1): Conv2d(\n",
            "          64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "      (1): BasicBlock(\n",
            "        (conv1): Conv2d(\n",
            "          128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (res4): Sequential(\n",
            "      (0): BasicBlock(\n",
            "        (shortcut): Conv2d(\n",
            "          128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
            "          (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv1): Conv2d(\n",
            "          128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "      (1): BasicBlock(\n",
            "        (conv1): Conv2d(\n",
            "          256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (res5): Sequential(\n",
            "      (0): BasicBlock(\n",
            "        (shortcut): Conv2d(\n",
            "          256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
            "          (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv1): Conv2d(\n",
            "          256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "      (1): BasicBlock(\n",
            "        (conv1): Conv2d(\n",
            "          512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "        (conv2): Conv2d(\n",
            "          512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
            "          (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "  )\n",
            "  (head): Head(\n",
            "    (deconv): CenternetDeconv(\n",
            "      (deconv1): DCNDeconvLayer(\n",
            "        (dcn_offset): Conv2d(512, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "        (dcn): ModulatedDeformConv(in_channels=512, out_channels=256, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
            "        (dcn_bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (up_sample): ConvTranspose2d(256, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "        (up_bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (relu): ReLU()\n",
            "      )\n",
            "      (lateral_conv1): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
            "      (deconv2): DCNDeconvLayer(\n",
            "        (dcn_offset): Conv2d(256, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "        (dcn): ModulatedDeformConv(in_channels=256, out_channels=128, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
            "        (dcn_bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (up_sample): ConvTranspose2d(128, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "        (up_bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (relu): ReLU()\n",
            "      )\n",
            "      (lateral_conv2): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
            "      (deconv3): DCNDeconvLayer(\n",
            "        (dcn_offset): Conv2d(128, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "        (dcn): ModulatedDeformConv(in_channels=128, out_channels=64, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
            "        (dcn_bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (up_sample): ConvTranspose2d(64, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
            "        (up_bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "        (relu): ReLU()\n",
            "      )\n",
            "      (lateral_conv3): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
            "      (output_conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "    )\n",
            "    (feat1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "    (cls_score): Conv2d(64, 80, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "    (ltrb_pred): Conv2d(64, 4, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  )\n",
            "  (criterion): SetCriterion(\n",
            "    (matcher): MinCostMatcher()\n",
            "  )\n",
            ")\n",
            "\u001b[32m[06/01 13:22:36 fvcore.common.checkpoint]: \u001b[0m[Checkpointer] Loading from /content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth ...\n",
            "\u001b[32m[06/01 13:22:37 d2.data.datasets.coco]: \u001b[0mLoaded 5000 images in COCO format from datasets/coco/annotations/instances_val2017.json\n",
            "\u001b[32m[06/01 13:22:38 d2.data.build]: \u001b[0mDistribution of instances among all 80 categories:\n",
            "\u001b[36m|   category    | #instances   |   category   | #instances   |   category    | #instances   |\n",
            "|:-------------:|:-------------|:------------:|:-------------|:-------------:|:-------------|\n",
            "|    person     | 10777        |   bicycle    | 314          |      car      | 1918         |\n",
            "|  motorcycle   | 367          |   airplane   | 143          |      bus      | 283          |\n",
            "|     train     | 190          |    truck     | 414          |     boat      | 424          |\n",
            "| traffic light | 634          | fire hydrant | 101          |   stop sign   | 75           |\n",
            "| parking meter | 60           |    bench     | 411          |     bird      | 427          |\n",
            "|      cat      | 202          |     dog      | 218          |     horse     | 272          |\n",
            "|     sheep     | 354          |     cow      | 372          |   elephant    | 252          |\n",
            "|     bear      | 71           |    zebra     | 266          |    giraffe    | 232          |\n",
            "|   backpack    | 371          |   umbrella   | 407          |    handbag    | 540          |\n",
            "|      tie      | 252          |   suitcase   | 299          |    frisbee    | 115          |\n",
            "|     skis      | 241          |  snowboard   | 69           |  sports ball  | 260          |\n",
            "|     kite      | 327          | baseball bat | 145          | baseball gl.. | 148          |\n",
            "|  skateboard   | 179          |  surfboard   | 267          | tennis racket | 225          |\n",
            "|    bottle     | 1013         |  wine glass  | 341          |      cup      | 895          |\n",
            "|     fork      | 215          |    knife     | 325          |     spoon     | 253          |\n",
            "|     bowl      | 623          |    banana    | 370          |     apple     | 236          |\n",
            "|   sandwich    | 177          |    orange    | 285          |   broccoli    | 312          |\n",
            "|    carrot     | 365          |   hot dog    | 125          |     pizza     | 284          |\n",
            "|     donut     | 328          |     cake     | 310          |     chair     | 1771         |\n",
            "|     couch     | 261          | potted plant | 342          |      bed      | 163          |\n",
            "| dining table  | 695          |    toilet    | 179          |      tv       | 288          |\n",
            "|    laptop     | 231          |    mouse     | 106          |    remote     | 283          |\n",
            "|   keyboard    | 153          |  cell phone  | 262          |   microwave   | 55           |\n",
            "|     oven      | 143          |   toaster    | 9            |     sink      | 225          |\n",
            "| refrigerator  | 126          |     book     | 1129         |     clock     | 267          |\n",
            "|     vase      | 274          |   scissors   | 36           |  teddy bear   | 190          |\n",
            "|  hair drier   | 11           |  toothbrush  | 57           |               |              |\n",
            "|     total     | 36335        |              |              |               |              |\u001b[0m\n",
            "\u001b[32m[06/01 13:22:38 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(512, 512), max_size=853, sample_style='choice')]\n",
            "\u001b[32m[06/01 13:22:38 d2.data.common]: \u001b[0mSerializing 5000 elements to byte tensors and concatenating them all ...\n",
            "\u001b[32m[06/01 13:22:38 d2.data.common]: \u001b[0mSerialized dataset takes 19.10 MiB\n",
            "\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[06/01 13:22:38 d2.evaluation.coco_evaluation]: \u001b[0mCOCO Evaluator instantiated using config, this is deprecated behavior. Please pass in explicit arguments instead.\n",
            "\u001b[32m[06/01 13:22:39 d2.evaluation.evaluator]: \u001b[0mStart inference on 5000 images\n",
            "\u001b[32m[06/01 13:22:39 d2.evaluation.evaluator]: \u001b[0mInference done 11/5000. 0.0148 s / img. ETA=0:01:18\n",
            "\u001b[32m[06/01 13:22:44 d2.evaluation.evaluator]: \u001b[0mInference done 281/5000. 0.0158 s / img. ETA=0:01:27\n",
            "\u001b[32m[06/01 13:22:49 d2.evaluation.evaluator]: \u001b[0mInference done 558/5000. 0.0159 s / img. ETA=0:01:21\n",
            "\u001b[32m[06/01 13:22:54 d2.evaluation.evaluator]: \u001b[0mInference done 834/5000. 0.0158 s / img. ETA=0:01:15\n",
            "\u001b[32m[06/01 13:22:59 d2.evaluation.evaluator]: \u001b[0mInference done 1107/5000. 0.0158 s / img. ETA=0:01:11\n",
            "\u001b[32m[06/01 13:23:04 d2.evaluation.evaluator]: \u001b[0mInference done 1388/5000. 0.0158 s / img. ETA=0:01:05\n",
            "\u001b[32m[06/01 13:23:09 d2.evaluation.evaluator]: \u001b[0mInference done 1667/5000. 0.0158 s / img. ETA=0:01:00\n",
            "\u001b[32m[06/01 13:23:14 d2.evaluation.evaluator]: \u001b[0mInference done 1936/5000. 0.0158 s / img. ETA=0:00:55\n",
            "\u001b[32m[06/01 13:23:19 d2.evaluation.evaluator]: \u001b[0mInference done 2217/5000. 0.0158 s / img. ETA=0:00:50\n",
            "\u001b[32m[06/01 13:23:24 d2.evaluation.evaluator]: \u001b[0mInference done 2500/5000. 0.0158 s / img. ETA=0:00:45\n",
            "\u001b[32m[06/01 13:23:29 d2.evaluation.evaluator]: \u001b[0mInference done 2770/5000. 0.0157 s / img. ETA=0:00:40\n",
            "\u001b[32m[06/01 13:23:34 d2.evaluation.evaluator]: \u001b[0mInference done 3051/5000. 0.0157 s / img. ETA=0:00:35\n",
            "\u001b[32m[06/01 13:23:39 d2.evaluation.evaluator]: \u001b[0mInference done 3332/5000. 0.0157 s / img. ETA=0:00:30\n",
            "\u001b[32m[06/01 13:23:44 d2.evaluation.evaluator]: \u001b[0mInference done 3613/5000. 0.0157 s / img. ETA=0:00:25\n",
            "\u001b[32m[06/01 13:23:49 d2.evaluation.evaluator]: \u001b[0mInference done 3877/5000. 0.0157 s / img. ETA=0:00:20\n",
            "\u001b[32m[06/01 13:23:54 d2.evaluation.evaluator]: \u001b[0mInference done 4159/5000. 0.0157 s / img. ETA=0:00:15\n",
            "\u001b[32m[06/01 13:23:59 d2.evaluation.evaluator]: \u001b[0mInference done 4445/5000. 0.0157 s / img. ETA=0:00:10\n",
            "\u001b[32m[06/01 13:24:04 d2.evaluation.evaluator]: \u001b[0mInference done 4732/5000. 0.0157 s / img. ETA=0:00:04\n",
            "\u001b[32m[06/01 13:24:09 d2.evaluation.evaluator]: \u001b[0mTotal inference time: 0:01:29.976256 (0.018013 s / img per device, on 1 devices)\n",
            "\u001b[32m[06/01 13:24:09 d2.evaluation.evaluator]: \u001b[0mTotal inference pure compute time: 0:01:18 (0.015670 s / img per device, on 1 devices)\n",
            "\u001b[32m[06/01 13:24:11 d2.evaluation.coco_evaluation]: \u001b[0mPreparing results for COCO format ...\n",
            "\u001b[32m[06/01 13:24:12 d2.evaluation.coco_evaluation]: \u001b[0mSaving results to output_onenet_r18dcn/inference/coco_instances_results.json\n",
            "\u001b[32m[06/01 13:24:14 d2.evaluation.coco_evaluation]: \u001b[0mEvaluating predictions with unofficial COCO API...\n",
            "Loading and preparing results...\n",
            "DONE (t=1.68s)\n",
            "creating index...\n",
            "index created!\n",
            "Running per image evaluation...\n",
            "Evaluate annotation type *bbox*\n",
            "COCOeval_opt.evaluate() finished in 13.20 seconds.\n",
            "Accumulating evaluation results...\n",
            "COCOeval_opt.accumulate() finished in 1.86 seconds.\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.301\n",
            " Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.465\n",
            " Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.323\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.146\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.316\n",
            " Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.419\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.279\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.475\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.520\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.284\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.554\n",
            " Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.724\n",
            "\u001b[32m[06/01 13:24:31 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for bbox: \n",
            "|   AP   |  AP50  |  AP75  |  APs   |  APm   |  APl   |\n",
            "|:------:|:------:|:------:|:------:|:------:|:------:|\n",
            "| 30.058 | 46.492 | 32.292 | 14.646 | 31.608 | 41.929 |\n",
            "\u001b[32m[06/01 13:24:31 d2.evaluation.coco_evaluation]: \u001b[0mPer-category bbox AP: \n",
            "| category      | AP     | category     | AP     | category       | AP     |\n",
            "|:--------------|:-------|:-------------|:-------|:---------------|:-------|\n",
            "| person        | 45.856 | bicycle      | 21.340 | car            | 30.992 |\n",
            "| motorcycle    | 32.092 | airplane     | 54.226 | bus            | 50.835 |\n",
            "| train         | 53.409 | truck        | 24.276 | boat           | 16.007 |\n",
            "| traffic light | 18.839 | fire hydrant | 52.368 | stop sign      | 55.485 |\n",
            "| parking meter | 30.671 | bench        | 15.428 | bird           | 25.488 |\n",
            "| cat           | 57.039 | dog          | 47.857 | horse          | 41.102 |\n",
            "| sheep         | 41.681 | cow          | 44.780 | elephant       | 55.350 |\n",
            "| bear          | 65.773 | zebra        | 59.104 | giraffe        | 58.685 |\n",
            "| backpack      | 7.340  | umbrella     | 29.946 | handbag        | 5.627  |\n",
            "| tie           | 19.604 | suitcase     | 25.425 | frisbee        | 47.239 |\n",
            "| skis          | 14.152 | snowboard    | 22.089 | sports ball    | 33.059 |\n",
            "| kite          | 32.341 | baseball bat | 13.959 | baseball glove | 22.701 |\n",
            "| skateboard    | 35.855 | surfboard    | 23.405 | tennis racket  | 31.813 |\n",
            "| bottle        | 25.702 | wine glass   | 23.546 | cup            | 27.468 |\n",
            "| fork          | 15.382 | knife        | 6.414  | spoon          | 6.364  |\n",
            "| bowl          | 26.837 | banana       | 15.819 | apple          | 7.775  |\n",
            "| sandwich      | 24.849 | orange       | 20.465 | broccoli       | 17.480 |\n",
            "| carrot        | 15.027 | hot dog      | 24.130 | pizza          | 41.184 |\n",
            "| donut         | 36.576 | cake         | 23.859 | chair          | 17.315 |\n",
            "| couch         | 39.133 | potted plant | 16.649 | bed            | 34.869 |\n",
            "| dining table  | 17.115 | toilet       | 51.162 | tv             | 45.212 |\n",
            "| laptop        | 41.752 | mouse        | 44.844 | remote         | 12.731 |\n",
            "| keyboard      | 37.485 | cell phone   | 19.029 | microwave      | 45.039 |\n",
            "| oven          | 23.542 | toaster      | 41.254 | sink           | 24.477 |\n",
            "| refrigerator  | 41.021 | book         | 8.443  | clock          | 41.171 |\n",
            "| vase          | 25.541 | scissors     | 13.243 | teddy bear     | 31.896 |\n",
            "| hair drier    | 0.390  | toothbrush   | 9.190  |                |        |\n",
            "\u001b[32m[06/01 13:24:33 d2.engine.defaults]: \u001b[0mEvaluation results for coco_2017_val in csv format:\n",
            "\u001b[32m[06/01 13:24:33 d2.evaluation.testing]: \u001b[0mcopypaste: Task: bbox\n",
            "\u001b[32m[06/01 13:24:33 d2.evaluation.testing]: \u001b[0mcopypaste: AP,AP50,AP75,APs,APm,APl\n",
            "\u001b[32m[06/01 13:24:33 d2.evaluation.testing]: \u001b[0mcopypaste: 30.0577,46.4925,32.2917,14.6464,31.6079,41.9288\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bxiRGTX3rR2-"
      },
      "source": [
        "# Visualize - give path to image in google drive\n",
        "install opencv additinoally for visualize "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IfBOKwOBlWrf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "22928c13-699d-4c5d-8124-0cb117000e5e"
      },
      "source": [
        "!python demo/demo.py\\\n",
        "    --config-file projects/OneNet/configs/onenet.res18.dcn.yaml \\\n",
        "    --input /content/drive/MyDrive/deepLearning/COCO/2017/train2017/000000581904.jpg --output /content/output --confidence-threshold 0.4 \\\n",
        "    --opts MODEL.WEIGHTS /content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[32m[06/01 13:24:42 detectron2]: \u001b[0mArguments: Namespace(confidence_threshold=0.4, config_file='projects/OneNet/configs/onenet.res18.dcn.yaml', input=['/content/drive/MyDrive/deepLearning/COCO/2017/train2017/000000581904.jpg'], opts=['MODEL.WEIGHTS', '/content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth'], output='/content/output', video_input=None, webcam=False)\n",
            "\u001b[32m[06/01 13:24:44 fvcore.common.checkpoint]: \u001b[0m[Checkpointer] Loading from /content/drive/MyDrive/deepLearning/hw2/onenet_r18dcn.pth ...\n",
            "  0% 0/1 [00:00<?, ?it/s]\u001b[32m[06/01 13:24:45 detectron2]: \u001b[0m/content/drive/MyDrive/deepLearning/COCO/2017/train2017/000000581904.jpg: detected 16 instances in 0.10s\n",
            "100% 1/1 [00:00<00:00,  5.39it/s]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}