training-roboflow-dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: Invalid requirement: '#'\n"
     ]
    }
   ],
   "source": [
    "%pip install -qr requirements.txt # install dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setup complete. Using torch 1.13.0 (NVIDIA GeForce RTX 4080)\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import os\n",
    "from IPython.display import Image, clear_output  # to display images\n",
    "\n",
    "print(f\"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name if torch.cuda.is_available() else 'CPU'})\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ROBOFLOW_DATASET_API_KEY=\"vgQ4Yo4PFezVeMa73FXO\"\n",
    "ROBOFLOW_DATASET_WORKSPACE=\"lama-alosaimi-qm2dm\"\n",
    "ROBOFLOW_DATASET_PROJECT=\"dummy2-xnmib\"\n",
    "ROBOFLOW_DATASET_VERSION=\"1\"\n",
    "IMAGE_SIZE=\"640\"\n",
    "BATCH=\"16\"\n",
    "EPOCH=\"150\"\n",
    "CONFIDENCE=\"0.1\"\n",
    "IMAGE_EXTENSION=\"jpg\"\n",
    "YOLO_V5_TYPE=\"yolov5s.pt\" # allowed values are yolov5s, yolov5m, yolov5l, and yolov5x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up environment\n",
    "os.environ[\"DATASET_DIRECTORY\"] = \"/roboflow/datasets\"\n",
    "os.environ[\"ROBOFLOW_DATASET_API_KEY\"] = ROBOFLOW_DATASET_API_KEY\n",
    "os.environ[\"ROBOFLOW_DATASET_WORKSPACE\"] = ROBOFLOW_DATASET_WORKSPACE\n",
    "os.environ[\"ROBOFLOW_DATASET_PROJECT\"] = ROBOFLOW_DATASET_PROJECT\n",
    "os.environ[\"ROBOFLOW_DATASET_VERSION\"] = ROBOFLOW_DATASET_VERSION\n",
    "os.environ[\"IMAGE_SIZE\"] = IMAGE_SIZE\n",
    "os.environ[\"BATCH\"] = BATCH\n",
    "os.environ[\"EPOCH\"] = EPOCH\n",
    "os.environ[\"CONFIDENCE\"] = CONFIDENCE\n",
    "os.environ[\"IMAGE_EXTENSION\"] = IMAGE_EXTENSION\n",
    "os.environ[\"YOLO_V5_TYPE\"] = YOLO_V5_TYPE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "R2wGvjd4Z_92",
    "outputId": "9b100d09-654e-4c01-e77d-71d3ec4264c0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upload and label your dataset, and get an API KEY here: https://app.roboflow.com/?model=yolov5&ref=ultralytics\n"
     ]
    }
   ],
   "source": [
    "from roboflow import Roboflow\n",
    "rf = Roboflow(model_format=\"yolov5\", notebook=\"ultralytics\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "FwJcaoPGF4VI",
    "outputId": "4e22e5ac-6980-403e-a723-ba205596761c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading Roboflow workspace...\n",
      "loading Roboflow project...\n",
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 5% [24567808 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 16% [76709888 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 26% [119103488 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 34% [159186944 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 40% [186351616 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 44% [203694080 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 53% [243531776 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 61% [279609344 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 67% [309927936 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 71% [328187904 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 79% [365453312 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 87% [398876672 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 92% [421920768 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Dataset Version Zip in /roboflow/datasets/dummy2-1 to yolov5pytorch: 97% [443400192 / 456826583] bytes"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n",
      "Extracting Dataset Version Zip to /roboflow/datasets/dummy2-1 in yolov5pytorch:: 100%|██████████| 15758/15758 [00:03<00:00, 4060.02it/s]\n"
     ]
    }
   ],
   "source": [
    "from roboflow import Roboflow\n",
    "rf = Roboflow(api_key=ROBOFLOW_DATASET_API_KEY)\n",
    "project = rf.workspace(ROBOFLOW_DATASET_WORKSPACE).project(ROBOFLOW_DATASET_PROJECT)\n",
    "dataset = project.version(ROBOFLOW_DATASET_VERSION).download(\"yolov5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eaFNnxLJbq4J",
    "outputId": "cd10b508-268b-4091-e76e-8aa3acf2984b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "^C\n"
     ]
    }
   ],
   "source": [
    "!python train.py --img {IMAGE_SIZE} --batch {BATCH} --epochs {EPOCH} --data {dataset.location}/data.yaml --weights {YOLO_V5_TYPE} --cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "TWjjiBcic3Vz",
    "outputId": "fc66484e-02b7-4e81-af74-6703dfea7c6c"
   },
   "outputs": [],
   "source": [
    "!python detect.py --weights runs/train/exp/weights/best.pt --img {IMAGE_SIZE} --conf {CONFIDENCE} --source {dataset.location}/test/images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "ZbUn4_b9GCKO",
    "outputId": "70f601b7-d53d-4efd-fb97-6ae373b15b9f"
   },
   "outputs": [],
   "source": [
    "#display inference on ALL test images\n",
    "\n",
    "import glob\n",
    "from IPython.display import Image, display\n",
    "\n",
    "for imageName in glob.glob('/content/yolov5/runs/detect/exp/*.',IMAGE_EXTENSION): #assuming JPG\n",
    "    display(Image(filename=imageName))\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "rNn-obvOGITm"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "YOLOv5-Custom-Training.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10 (tags/v3.9.10:f2f3f53, Jan 17 2022, 15:14:21) [MSC v.1929 64 bit (AMD64)]"
  },
  "vscode": {
   "interpreter": {
    "hash": "6fff98fc3b3d81bd655c2cc48858186e4d9e2db7b515bf1c3221888f12a62f87"
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 },
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}