yolo-collection-coco2017-train.ipynb

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   "source": [
    "# About\n",
    "This notebook enables you to easily train (currently) YOLOv{5,6,7} on MSCOCO2017 dataset.\n",
    "\n",
    "**Notes:**\n",
    "* *Notebook is written with Kaggle in mind, so most paths are absolute and hardcoded for kaggle. You are needed to make necessary changes if running on other platforms.*\n",
    "* *Training is set to last only one epoch, you can change that in `python train.py` lines.*\n",
    "* *Training, even for one epoch, lasts very long, consider running it in a batch session*\n",
    "* *Notebook was tested with GPU P100, if you get `No space left` or `CUDA out of memory`, consider lowering batch size.*\n",
    "* *Just starting this notebook without making changes takes about 7hrs.*\n",
    "* *After training/testing, all outputs are stored in default output directory.*\n",
    "# Directory structure:\n",
    "```shell\n",
    "/kaggle/\n",
    "├─ working/\n",
    "│  ├─ yolov5*/\n",
    "│  ├─ YOLOv6*/\n",
    "│  ├─ yolov7*/\n",
    "├─ datasets/ \n",
    "│  ├─ coco/\n",
    "│  │  ├─ images/\n",
    "│  │  ├─ annotations/\n",
    "│  │  ├─ labels/\n",
    "│  │  ├─ train2017.txt\n",
    "│  │  ├─ val2017.txt\n",
    "│  │  ├─ test-dev2017.txt\n",
    "```\n",
    "\\* - optional\n",
    "* **"
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   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "class YOLO_VERSIONS:\n",
    "    YOLOV5 = 'yolov5'\n",
    "    YOLOV6 = 'yolov6'\n",
    "    YOLOV7 = 'yolov7'"
   ]
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   "source": [
    "* **\n",
    "# Options\n",
    "Choose which **version** of YOLO to use and if you want **evaluation** after testing.\n",
    "* **"
   ]
  },
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   "source": [
    "# you may add multiple yolo versions, ex. current_version = [YOLO_VERSIONS.YOLOV5, YOLO_VERSIONS.YOLOV6]\n",
    "current_version = [YOLO_VERSIONS.YOLOV6]\n",
    "eval = True"
   ]
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     "text": [
      "/kaggle/datasets/coco/images\n",
      "--2023-03-29 04:01:46--  http://images.cocodataset.org/zips/train2017.zip\r\n",
      "Resolving images.cocodataset.org (images.cocodataset.org)... 54.231.198.17, 52.216.214.185, 54.231.164.1, ...\r\n",
      "Connecting to images.cocodataset.org (images.cocodataset.org)|54.231.198.17|:80... connected.\r\n",
      "HTTP request sent, awaiting response... 200 OK\r\n",
      "Length: 19336861798 (18G) [application/zip]\r\n",
      "Saving to: ‘train2017.zip’\r\n",
      "\r\n",
      "train2017.zip       100%[===================>]  18.01G  33.3MB/s    in 9m 22s  \r\n",
      "\r\n",
      "2023-03-29 04:11:08 (32.8 MB/s) - ‘train2017.zip’ saved [19336861798/19336861798]\r\n",
      "\r\n",
      "Unzipping train dataset...\n",
      "--2023-03-29 04:14:25--  http://images.cocodataset.org/zips/val2017.zip\r\n",
      "Resolving images.cocodataset.org (images.cocodataset.org)... 3.5.2.1, 3.5.16.171, 52.217.163.145, ...\r\n",
      "Connecting to images.cocodataset.org (images.cocodataset.org)|3.5.2.1|:80... connected.\r\n",
      "HTTP request sent, awaiting response... 200 OK\r\n",
      "Length: 815585330 (778M) [application/zip]\r\n",
      "Saving to: ‘val2017.zip’\r\n",
      "\r\n",
      "val2017.zip         100%[===================>] 777.80M  33.3MB/s    in 24s     \r\n",
      "\r\n",
      "2023-03-29 04:14:50 (32.2 MB/s) - ‘val2017.zip’ saved [815585330/815585330]\r\n",
      "\r\n",
      "Unzipping val dataset...\n",
      "--2023-03-29 04:14:57--  http://images.cocodataset.org/zips/test2017.zip\r\n",
      "Resolving images.cocodataset.org (images.cocodataset.org)... 52.216.102.59, 52.216.32.25, 54.231.163.249, ...\r\n",
      "Connecting to images.cocodataset.org (images.cocodataset.org)|52.216.102.59|:80... connected.\r\n",
      "HTTP request sent, awaiting response... 200 OK\r\n",
      "Length: 6646970404 (6.2G) [application/zip]\r\n",
      "Saving to: ‘test2017.zip’\r\n",
      "\r\n",
      "test2017.zip        100%[===================>]   6.19G  32.9MB/s    in 3m 12s  \r\n",
      "\r\n",
      "2023-03-29 04:18:09 (33.1 MB/s) - ‘test2017.zip’ saved [6646970404/6646970404]\r\n",
      "\r\n",
      "Unzipping test dataset...\n"
     ]
    }
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   "source": [
    "# Download coco datasets and takes 30mins+ (~40gb unzipped).\n",
    "# NOTE: download directory should not be output, ie /kaggle/working as it's capacity is only ~19gb\n",
    "%mkdir -p ../datasets/coco/images\n",
    "%cd ../datasets/coco/images\n",
    "!wget http://images.cocodataset.org/zips/train2017.zip\n",
    "print(\"Unzipping train dataset...\")\n",
    "!unzip -q train2017.zip && rm -rf train2017.zip\n",
    "!wget http://images.cocodataset.org/zips/val2017.zip\n",
    "print(\"Unzipping val dataset...\")\n",
    "!unzip -q val2017.zip && rm -rf  val2017.zip\n",
    "!wget http://images.cocodataset.org/zips/test2017.zip\n",
    "print(\"Unzipping test dataset...\")\n",
    "!unzip -q test2017.zip && rm -rf test2017.zip"
   ]
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      "/kaggle\n",
      "/kaggle/tmp\n",
      "--2023-03-29 04:19:20--  https://github.com/meituan/YOLOv6/releases/download/0.1.0/coco2017labels.zip\r\n",
      "Resolving github.com (github.com)... 140.82.121.4\r\n",
      "Connecting to github.com (github.com)|140.82.121.4|:443... connected.\r\n",
      "HTTP request sent, awaiting response... 302 Found\r\n",
      "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/501076075/01f96845-f102-4163-ba33-ceab55dc9b0a?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230329%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230329T041920Z&X-Amz-Expires=300&X-Amz-Signature=e36ed059c35278a044d73dc01d228f94b4a2480c1f2c86969d2d4bfeb3664b0f&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=501076075&response-content-disposition=attachment%3B%20filename%3Dcoco2017labels.zip&response-content-type=application%2Foctet-stream [following]\r\n",
      "--2023-03-29 04:19:20--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/501076075/01f96845-f102-4163-ba33-ceab55dc9b0a?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230329%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230329T041920Z&X-Amz-Expires=300&X-Amz-Signature=e36ed059c35278a044d73dc01d228f94b4a2480c1f2c86969d2d4bfeb3664b0f&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=501076075&response-content-disposition=attachment%3B%20filename%3Dcoco2017labels.zip&response-content-type=application%2Foctet-stream\r\n",
      "Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.111.133, 185.199.110.133, 185.199.109.133, ...\r\n",
      "Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.111.133|:443... connected.\r\n",
      "HTTP request sent, awaiting response... 200 OK\r\n",
      "Length: 71005511 (68M) [application/octet-stream]\r\n",
      "Saving to: ‘coco2017labels.zip’\r\n",
      "\r\n",
      "coco2017labels.zip  100%[===================>]  67.72M  56.3MB/s    in 1.2s    \r\n",
      "\r\n",
      "2023-03-29 04:19:22 (56.3 MB/s) - ‘coco2017labels.zip’ saved [71005511/71005511]\r\n",
      "\r\n",
      "Unzipping labels and annotations...\n",
      "\u001b[0m\u001b[01;34mdatasets\u001b[0m/  \u001b[01;34minput\u001b[0m/  \u001b[01;34mlib\u001b[0m/  \u001b[01;34msrc\u001b[0m/  \u001b[01;34mtmp\u001b[0m/  \u001b[01;34mworking\u001b[0m/\r\n",
      "__notebook__.ipynb\r\n",
      "/kaggle\n"
     ]
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   "source": [
    "# Downloading COCO labels and annotations\n",
    "%cd /kaggle\n",
    "%mkdir tmp\n",
    "%cd tmp\n",
    "!wget https://github.com/meituan/YOLOv6/releases/download/0.1.0/coco2017labels.zip\n",
    "print(\"Unzipping labels and annotations...\")\n",
    "!unzip -q coco2017labels.zip && rm -rf coco2017labels.zip\n",
    "%cp -r /kaggle/tmp/coco/annotations /kaggle/datasets/coco\n",
    "%cp -r /kaggle/tmp/coco/labels /kaggle/datasets/coco\n",
    "%cp -r /kaggle/tmp/coco/val2017.txt /kaggle/datasets/coco\n",
    "%cp -r /kaggle/tmp/coco/train2017.txt /kaggle/datasets/coco\n",
    "%cp -r /kaggle/tmp/coco/test-dev2017.txt /kaggle/datasets/coco\n",
    "%pwd\n",
    "%ls /kaggle\n",
    "%ls /kaggle/working\n",
    "%cd /kaggle\n",
    "%rm -rf /kaggle/tmp"
   ]
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      "/kaggle/working\n",
      "Cloning into 'YOLOv6'...\r\n",
      "remote: Enumerating objects: 3084, done.\u001b[K\r\n",
      "remote: Counting objects: 100% (90/90), done.\u001b[K\r\n",
      "remote: Compressing objects: 100% (62/62), done.\u001b[K\r\n",
      "remote: Total 3084 (delta 31), reused 72 (delta 27), pack-reused 2994\u001b[K\r\n",
      "Receiving objects: 100% (3084/3084), 46.29 MiB | 22.04 MiB/s, done.\r\n",
      "Resolving deltas: 100% (1752/1752), done.\r\n",
      "/kaggle/working/YOLOv6\n",
      "Requirement already satisfied: torch>=1.8.0 in /opt/conda/lib/python3.7/site-packages (from -r requirements.txt (line 4)) (1.11.0)\r\n",
      "Requirement already satisfied: torchvision>=0.9.0 in /opt/conda/lib/python3.7/site-packages (from -r requirements.txt (line 5)) (0.12.0)\r\n",
      "\u001b[31mERROR: Ignored the following versions that require a different python version: 1.22.0 Requires-Python >=3.8; 1.22.1 Requires-Python >=3.8; 1.22.2 Requires-Python >=3.8; 1.22.3 Requires-Python >=3.8; 1.22.4 Requires-Python >=3.8; 1.23.0 Requires-Python >=3.8; 1.23.0rc1 Requires-Python >=3.8; 1.23.0rc2 Requires-Python >=3.8; 1.23.0rc3 Requires-Python >=3.8; 1.23.1 Requires-Python >=3.8; 1.23.2 Requires-Python >=3.8; 1.23.3 Requires-Python >=3.8; 1.23.4 Requires-Python >=3.8; 1.23.5 Requires-Python >=3.8; 1.24.0 Requires-Python >=3.8; 1.24.0rc1 Requires-Python >=3.8; 1.24.0rc2 Requires-Python >=3.8; 1.24.1 Requires-Python >=3.8; 1.24.2 Requires-Python >=3.8\u001b[0m\u001b[31m\r\n",
      "\u001b[0m\u001b[31mERROR: Could not find a version that satisfies the requirement numpy>=1.24.0 (from versions: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.9.3, 1.10.0.post2, 1.10.1, 1.10.2, 1.10.4, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 1.13.3, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.6, 1.15.0, 1.15.1, 1.15.2, 1.15.3, 1.15.4, 1.16.0, 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5, 1.16.6, 1.17.0, 1.17.1, 1.17.2, 1.17.3, 1.17.4, 1.17.5, 1.18.0, 1.18.1, 1.18.2, 1.18.3, 1.18.4, 1.18.5, 1.19.0, 1.19.1, 1.19.2, 1.19.3, 1.19.4, 1.19.5, 1.20.0, 1.20.1, 1.20.2, 1.20.3, 1.21.0, 1.21.1, 1.21.2, 1.21.3, 1.21.4, 1.21.5, 1.21.6)\u001b[0m\u001b[31m\r\n",
      "\u001b[0m\u001b[31mERROR: No matching distribution found for numpy>=1.24.0\u001b[0m\u001b[31m\r\n",
      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# Cloning necessary git repos\n",
    "\n",
    "if YOLO_VERSIONS.YOLOV5 in current_version:\n",
    "    %cd /kaggle/working\n",
    "    !git clone https://github.com/ultralytics/yolov5  # clone\n",
    "    %cd /kaggle/working/yolov5\n",
    "    %pip install -r requirements.txt\n",
    "if YOLO_VERSIONS.YOLOV6 in current_version:\n",
    "    %cd /kaggle/working\n",
    "    !git clone https://github.com/meituan/YOLOv6\n",
    "    %cd /kaggle/working/YOLOv6\n",
    "    %pip install -r requirements.txt\n",
    "if YOLO_VERSIONS.YOLOV7 in current_version:\n",
    "    %cd /kaggle/working\n",
    "    !git clone https://github.com/WongKinYiu/yolov7\n",
    "    %cd /kaggle/working/yolov7\n",
    "    %pip install -r requirements.txt"
   ]
  },
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      "\u001b[0m\u001b[01;34mYOLOv6\u001b[0m/  __notebook__.ipynb\r\n",
      "\u001b[0m\u001b[01;34mdatasets\u001b[0m/  \u001b[01;34minput\u001b[0m/  \u001b[01;34mlib\u001b[0m/  \u001b[01;34msrc\u001b[0m/  \u001b[01;34mworking\u001b[0m/\r\n"
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   "source": [
    "coco_path = '/kaggle/datasets/coco'\n",
    "%ls /kaggle/working\n",
    "%ls /kaggle\n",
    "# change train, val, and test datasets locations in coco.yaml\n",
    "if YOLO_VERSIONS.YOLOV5 in current_version:\n",
    "    %cp /kaggle/working/yolov5/data/coco.yaml /kaggle/working/yolov5/coco_original.yaml\n",
    "    with open('/kaggle/working/yolov5/data/coco.yaml', 'w') as new_file:\n",
    "        with open('/kaggle/working/yolov5/coco_original.yaml', 'r') as original_file:\n",
    "            for line in original_file:\n",
    "                if 'path:' in line:\n",
    "                    new_file.write(f'path: {coco_path}\\n')\n",
    "                else:\n",
    "                    new_file.write(line)\n",
    "if YOLO_VERSIONS.YOLOV6 in current_version:\n",
    "    %cp /kaggle/working/YOLOv6/data/coco.yaml /kaggle/working/YOLOv6/coco_original.yaml\n",
    "    with open('/kaggle/working/YOLOv6/data/coco.yaml', 'w') as new_file:\n",
    "        with open('/kaggle/working/YOLOv6/coco_original.yaml', 'r') as original_file:\n",
    "            for line in original_file:\n",
    "                if 'train:' in line:\n",
    "                    new_file.write(f'train: {coco_path}/images/train2017 # 118287 images\\n')\n",
    "                elif 'val:' in line:\n",
    "                    new_file.write(f'val: {coco_path}/images/val2017   # 5000 images\\n')\n",
    "                elif 'test:' in line:\n",
    "                    new_file.write(f'test: {coco_path}/images/test2017\\n')\n",
    "                elif 'anno_path:' in line:\n",
    "                    new_file.write(f'anno_path: {coco_path}/annotations/instances_val2017.json\\n')\n",
    "                else:\n",
    "                    new_file.write(line)\n",
    "                    \n",
    "if YOLO_VERSIONS.YOLOV7 in current_version:\n",
    "    %cp /kaggle/working/yolov7/data/coco.yaml /kaggle/working/yolov7/coco_original.yaml\n",
    "    with open('/kaggle/working/yolov7/data/coco.yaml', 'w') as new_file:\n",
    "        with open('/kaggle/working/yolov7/coco_original.yaml', 'r') as original_file:\n",
    "            for line in original_file:\n",
    "                if 'train:' in line:\n",
    "                    new_file.write(f'train: {coco_path}/images/train2017 # 118287 images\\n')\n",
    "                elif 'val:' in line:\n",
    "                    new_file.write(f'val: {coco_path}/images/val2017  # 5000 images\\n')\n",
    "                elif 'test:' in line:\n",
    "                    new_file.write(f'test: {coco_path}/test2017\\n')\n",
    "                elif 'anno_path:' in line:\n",
    "                    new_file.write(f'anno_path: {coco_path}/annotations/instances_val2017.json\\n')\n",
    "                else:\n",
    "                    new_file.write(line)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "77a1167d",
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    "execution": {
     "iopub.execute_input": "2023-03-29T04:20:09.090444Z",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "env: WANDB_MODE=dryrun\n",
      "Collecting pycocotools\r\n",
      "  Downloading pycocotools-2.0.6.tar.gz (24 kB)\r\n",
      "  Installing build dependencies ... \u001b[?25l-\b \b\\\b \b|\b \b/\b \b-\b \b\\\b \b|\b \bdone\r\n",
      "\u001b[?25h  Getting requirements to build wheel ... \u001b[?25l-\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Preparing metadata (pyproject.toml) ... \u001b[?25l-\b \bdone\r\n",
      "\u001b[?25hRequirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from pycocotools) (1.21.6)\r\n",
      "Requirement already satisfied: matplotlib>=2.1.0 in /opt/conda/lib/python3.7/site-packages (from pycocotools) (3.5.3)\r\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (22.0)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (2.8.2)\r\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (4.33.3)\r\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (0.11.0)\r\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (3.0.9)\r\n",
      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (9.1.1)\r\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.1.0->pycocotools) (1.4.3)\r\n",
      "Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib>=2.1.0->pycocotools) (4.1.1)\r\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.7/site-packages (from python-dateutil>=2.7->matplotlib>=2.1.0->pycocotools) (1.15.0)\r\n",
      "Building wheels for collected packages: pycocotools\r\n",
      "  Building wheel for pycocotools (pyproject.toml) ... \u001b[?25l-\b \b\\\b \b|\b \b/\b \b-\b \b\\\b \b|\b \bdone\r\n",
      "\u001b[?25h  Created wheel for pycocotools: filename=pycocotools-2.0.6-cp37-cp37m-linux_x86_64.whl size=373770 sha256=bf8d87f7ec695239cb4078637994292f1df2184f2c4c368de4749ee89c59e50a\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/06/f6/f9/9cc49c6de8e3cf27dfddd91bf46595a057141d4583a2adaf03\r\n",
      "Successfully built pycocotools\r\n",
      "Installing collected packages: pycocotools\r\n",
      "Successfully installed pycocotools-2.0.6\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n",
      "/kaggle/working/YOLOv6\n",
      "Traceback (most recent call last):\r\n",
      "  File \"tools/train.py\", line 17, in <module>\r\n",
      "    from yolov6.core.engine import Trainer\r\n",
      "  File \"/kaggle/working/YOLOv6/yolov6/core/engine.py\", line 19, in <module>\r\n",
      "    import tools.eval as eval\r\n",
      "  File \"/kaggle/working/YOLOv6/tools/eval.py\", line 16, in <module>\r\n",
      "    from yolov6.utils.config import Config\r\n",
      "  File \"/kaggle/working/YOLOv6/yolov6/utils/config.py\", line 12, in <module>\r\n",
      "    from addict import Dict\r\n",
      "ModuleNotFoundError: No module named 'addict'\r\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "# comment this if you want to use wandb (note that in that case wandb-api must be provided [add-ons->secrets])\n",
    "%env WANDB_MODE=dryrun\n",
    "%pip install pycocotools\n",
    "if YOLO_VERSIONS.YOLOV5 in current_version:\n",
    "    %cd /kaggle/working/yolov5\n",
    "    !python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  --batch-size 32\n",
    "if YOLO_VERSIONS.YOLOV6 in current_version:\n",
    "    %cd /kaggle/working/YOLOv6\n",
    "    !python tools/train.py --img 640 --batch 32 --epochs 40 --conf configs/yolov6s.py --data data/coco.yaml\n",
    "if YOLO_VERSIONS.YOLOV7 in current_version:\n",
    "    %cd /kaggle/working/yolov7\n",
    "    # echo 'x' - user choice (replace x with one of the available options)\n",
    "    #         wandb: (1) Create a W&B account\n",
    "    #         wandb: (2) Use an existing W&B account\n",
    "    #         wandb: (3) Don't visualize my results\n",
    "    # NOTE: weights flag with value '' means weights are randomly initialized\n",
    "    !echo \"3\" | python train.py --workers 8 --device 0 --batch-size 16 --epochs 1 --cfg cfg/training/yolov7.yaml --data data/coco.yaml --img 640 640 --cfg cfg/training/yolov7.yaml --weights '' --name yolov7 --hyp data/hyp.scratch.p5.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2793daf0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-29T04:20:49.902051Z",
     "iopub.status.busy": "2023-03-29T04:20:49.901247Z",
     "iopub.status.idle": "2023-03-29T04:20:52.140325Z",
     "shell.execute_reply": "2023-03-29T04:20:52.139112Z"
    },
    "papermill": {
     "duration": 2.433622,
     "end_time": "2023-03-29T04:20:52.142864",
     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/working/YOLOv6\n",
      "Traceback (most recent call last):\r\n",
      "  File \"tools/eval.py\", line 16, in <module>\r\n",
      "    from yolov6.utils.config import Config\r\n",
      "  File \"/kaggle/working/YOLOv6/yolov6/utils/config.py\", line 12, in <module>\r\n",
      "    from addict import Dict\r\n",
      "ModuleNotFoundError: No module named 'addict'\r\n"
     ]
    }
   ],
   "source": [
    "#eval\n",
    "#TODO: requires testing\n",
    "if eval:\n",
    "    if YOLO_VERSIONS.YOLOV5 in current_version:\n",
    "        %cd /kaggle/working/yolov5\n",
    "        %cat data/coco.yaml\n",
    "        !python val.py --weights /kaggle/working/yolov5/runs/train/exp/weights/best.pt --data coco.yaml --img 640\n",
    "    if YOLO_VERSIONS.YOLOV6 in current_version:\n",
    "        %cd /kaggle/working/YOLOv6\n",
    "        !python tools/eval.py --data data/coco.yaml  --weights /kaggle/working/YOLOv6/runs/train/exp/weights/best_ckpt.pt --task val --device 0\n",
    "    if YOLO_VERSIONS.YOLOV7 in current_version:\n",
    "        %cd /kaggle/working/yolov7\n",
    "        !python test.py --data data/coco.yaml --img 640 --batch 32 --conf 0.001 --iou 0.65 --device 0 --weights /kaggle/working/yolov7/runs/train/yolov7/weights/best.pt --name yolov7_640_val\n"
   ]
  }
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