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     "start_time": "2018-12-03T08:27:52.293917Z"
    }
   },
   "source": [
    "# Eval COCO Demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "path = Path(\"../src\").resolve()\n",
    "sys.path.extend([str(path)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "from pycocotools.coco import COCO\n",
    "from pycocotools.cocoeval import COCOeval\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-03T08:28:03.797211Z",
     "start_time": "2018-12-03T08:28:03.791205Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running demo for *bbox* results.\n"
     ]
    }
   ],
   "source": [
    "annType = ['segm', 'bbox', 'keypoints']\n",
    "annType = annType[1]  # specify type here\n",
    "prefix = 'person_keypoints' if annType == 'keypoints' else 'instances'\n",
    "print(f'Running demo for *{annType}* results.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初始化 COCO ground truth api："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading annotations into memory...\n",
      "Done (t=5.08s)\n",
      "creating index...\n",
      "index created!\n"
     ]
    }
   ],
   "source": [
    "dataDir = '/media/pc/data/4tb/lxw/tests/datasets/coco'\n",
    "dataType = 'val2014'\n",
    "annFile = f'{dataDir}/annotations/{prefix}_{dataType}.json'\n",
    "cocoGt = COCO(annFile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初始化 COCO 检测 api："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading and preparing results...\n",
      "DONE (t=0.05s)\n",
      "creating index...\n",
      "index created!\n"
     ]
    }
   ],
   "source": [
    "dataDir = '../results/' # 检测结果根目录\n",
    "dataType = 'val2014'\n",
    "prefix = \"instances\"\n",
    "resFile = f\"{dataDir}/{prefix}_{dataType}_fakebbox100_results.json\"\n",
    "cocoDt = cocoGt.loadRes(resFile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "imgIds = sorted(cocoGt.getImgIds())\n",
    "imgIds = imgIds[0:100]\n",
    "imgId = imgIds[np.random.randint(100)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "运行评估："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running per image evaluation...\n",
      "Evaluate annotation type *bbox*\n",
      "DONE (t=0.34s).\n",
      "Accumulating evaluation results...\n",
      "DONE (t=0.40s).\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.505\n",
      " Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.697\n",
      " Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.573\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.586\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.519\n",
      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.501\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.387\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.594\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.595\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.640\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.566\n",
      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.564\n"
     ]
    }
   ],
   "source": [
    "cocoEval = COCOeval(cocoGt, cocoDt, annType)\n",
    "cocoEval.params.imgIds  = imgIds\n",
    "cocoEval.evaluate()\n",
    "cocoEval.accumulate()\n",
    "cocoEval.summarize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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