train.YOLOv3.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Copy of Untitled2.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNBufpHuLD8sL1eXKhYBy5T",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ali-kmirzaei/YOLO-object-detection/blob/main/train.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "e0SraIxrFDS0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "85fcba2c-c516-4f44-f852-0045aa92363a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fri Mar  4 17:47:36 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla K80           Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   70C    P8    34W / 149W |      0MiB / 11441MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/AlexeyAB/darknet.git"
      ],
      "metadata": {
        "id": "VmBJcL3_FHL5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%cd darknet\n",
        "!sed -i 's/OPENCV=0/OPENCV=1/' Makefile\n",
        "!sed -i 's/GPU=0/GPU=1/' Makefile\n",
        "!sed -i 's/CUDNN=0/CUDNN=1/' Makefile\n",
        "!make"
      ],
      "metadata": {
        "id": "zs-AC-UQFmBg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!cp yolov3.cfg cfg/yolov3_training.cfg"
      ],
      "metadata": {
        "id": "TrKSjKGCJvZ4"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# import dataset from google drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "!ln -s /content/gdrive/My\\ Drive/ /mydrive\n",
        "!ls /mydrive"
      ],
      "metadata": {
        "id": "drNWJYMaKAAC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip /mydrive/obj.zip -d data/ "
      ],
      "metadata": {
        "id": "-kzIaKELllgu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!cp /mydrive/yolov3_training_4000.weights ../darknet/"
      ],
      "metadata": {
        "id": "NYu3KK3ll3sF"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Start Training\n",
        "!./darknet detector train data/obj.data cfg/yolov3_training.cfg yolov3_training_4000.weights -dont_show -map"
      ],
      "metadata": {
        "id": "yLVWkPRpnJ9F"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "KEvqW1R7Gccb"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}