cutpaste_mi_runinho.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPg7Aqe/3SxS7pL7GhQmGJs",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/danielsoy/ALOCC-CVPR2018/blob/master/cutpaste_mi_runinho.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# https://github.com/Runinho/pytorch-cutpaste\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "Acc3WutkaU9f"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YsP6nX4zZquw",
        "outputId": "8afe50dd-7037-4732-b398-6e40706f27c6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'pytorch-cutpaste'...\n",
            "remote: Enumerating objects: 213, done.\u001b[K\n",
            "remote: Counting objects: 100% (43/43), done.\u001b[K\n",
            "remote: Compressing objects: 100% (7/7), done.\u001b[K\n",
            "remote: Total 213 (delta 39), reused 36 (delta 36), pack-reused 170\u001b[K\n",
            "Receiving objects: 100% (213/213), 817.70 KiB | 17.78 MiB/s, done.\n",
            "Resolving deltas: 100% (103/103), done.\n"
          ]
        }
      ],
      "source": [
        "\n",
        "!git clone https://github.com/Runinho/pytorch-cutpaste.git # runinho usa google drive."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cd /content/pytorch-cutpaste/  # /content/pytorch-cutpaste/\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qUk16bhoZ8jb",
        "outputId": "7da4d261-aaad-4bc1-9c78-a33d552efd8a"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[Errno 2] No such file or directory: '/content/pytorch-cutpaste/ # /content/pytorch-cutpaste/'\n",
            "/content\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install -r requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SJAgsrS4aA9j",
        "outputId": "c33d38c1-d967-471d-e5ca-8a51e36c4bb2"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[31mERROR: Could not open requirements file: [Errno 2] No such file or directory: 'requirements.txt'\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ns9wf4V5nOMB",
        "outputId": "45702fcd-5454-4e9a-b175-ad556e3b459e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cd  /content/drive/MyDrive/Data/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R37bknairVqK",
        "outputId": "a8d25d27-334e-42e2-d094-e9c86c6d85ee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/Data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.status.busy": "2021-11-26T17:03:22.966098Z",
          "iopub.execute_input": "2021-11-26T17:03:22.966804Z",
          "iopub.status.idle": "2021-11-26T17:03:22.982768Z",
          "shell.execute_reply.started": "2021-11-26T17:03:22.966766Z",
          "shell.execute_reply": "2021-11-26T17:03:22.98199Z"
        },
        "trusted": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "gOqx9kUXSmXv",
        "outputId": "1c507cae-4d07-47ba-c146-8a73f430bd92"
      },
      "source": [
        "import cv2\n",
        "img = cv2.imread(\"bottle/train/good/aume0.PNG\")\n",
        "img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
        "import matplotlib.pyplot as plt\n",
        "plt.imshow(img)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f8614edb6d0>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cd /content/pytorch-cutpaste/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nyUn4klBt1VY",
        "outputId": "1a682385-3c3b-4b7d-e7af-d7f75405a1b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/pytorch-cutpaste\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python run_training.py --model_dir models --head_layer 2 "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YiQCxbx5axPP",
        "outputId": "d79e5a3c-fdbd-41f9-9745-41104355dfda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-04-09 16:50:38.269757: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2023-04-09 16:50:39.577601: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "Namespace(type='all', epochs=256, model_dir='models', pretrained=True, test_epochs=10, freeze_resnet=20, lr=0.03, optim='sgd', batch_size=64, head_layer=2, variant='3way', cuda=False, workers=8)\n",
            "using device: cpu\n",
            "training bottle\n",
            "loading images\n",
            "loaded 0 images\n",
            "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py:561: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
            "  warnings.warn(_create_warning_msg(\n",
            "/usr/local/lib/python3.9/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.9/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n",
            "  warnings.warn(msg)\n",
            "  0% 0/256 [00:00<?, ?it/s]\n",
            "Traceback (most recent call last):\n",
            "  File \"/content/pytorch-cutpaste/run_training.py\", line 251, in <module>\n",
            "    run_training(data_type,\n",
            "  File \"/content/pytorch-cutpaste/run_training.py\", line 106, in run_training\n",
            "    batch_idx, data = next(dataloader_inf)\n",
            "  File \"/content/pytorch-cutpaste/run_training.py\", line 95, in get_data_inf\n",
            "    for out in enumerate(dataloader):\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py\", line 634, in __next__\n",
            "    data = self._next_data()\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py\", line 1346, in _next_data\n",
            "    return self._process_data(data)\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py\", line 1372, in _process_data\n",
            "    data.reraise()\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/_utils.py\", line 644, in reraise\n",
            "    raise exception\n",
            "ZeroDivisionError: Caught ZeroDivisionError in DataLoader worker process 0.\n",
            "Original Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/worker.py\", line 308, in _worker_loop\n",
            "    data = fetcher.fetch(index)\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py\", line 51, in fetch\n",
            "    data = [self.dataset[idx] for idx in possibly_batched_index]\n",
            "  File \"/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py\", line 51, in <listcomp>\n",
            "    data = [self.dataset[idx] for idx in possibly_batched_index]\n",
            "  File \"/content/pytorch-cutpaste/dataset.py\", line 16, in __getitem__\n",
            "    return self.org_dataset[idx % self.org_length]\n",
            "ZeroDivisionError: integer division or modulo by zero\n",
            "\n"
          ]
        }
      ]
    }
  ]
}