09.03 目标检测和边界框.ipynb

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   "source": [
    "\n",
    "\n",
    "在前面的一些章节中，我们介绍了诸多用于图像分类的模型。在图像分类任务里，我们假设图像里只有一个主体目标，并关注如何识别该目标的类别。然而，很多时候图像里有多个我们感兴趣的目标，我们不仅想知道它们的类别，还想得到它们在图像中的具体位置。在计算机视觉里，我们将这类任务称为目标检测（object detection）或物体检测。\n",
    "\n",
    "目标检测在多个领域中被广泛使用。例如，在无人驾驶里，我们需要通过识别拍摄到的视频图像里的车辆、行人、道路和障碍的位置来规划行进线路。机器人也常通过该任务来检测感兴趣的目标。安防领域则需要检测异常目标，如歹徒或者炸弹。\n",
    "\n",
    "在接下来的几节里，我们将介绍目标检测里的多个深度学习模型。在此之前，让我们来了解目标位置这个概念。先导入实验所需的包或模块。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-29T08:24:06.783567Z",
     "start_time": "2019-11-29T08:24:05.799215Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import d2lzh as d2l\n",
    "from mxnet import image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面加载本节将使用的示例图像。可以看到图像左边是一只狗，右边是一只猫。它们是这张图像里的两个主要目标。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-29T08:24:09.512087Z",
     "start_time": "2019-11-29T08:24:09.154696Z"
    }
   },
   "outputs": [
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   "source": [
    "d2l.set_figsize()\n",
    "img = image.imread('img/catdog.jpg').asnumpy()\n",
    "d2l.plt.imshow(img);  # 加分号只显示图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 边界框\n",
    "\n",
    "在目标检测里，我们通常使用边界框（bounding box）来描述目标位置。边界框是一个矩形框，可以由矩形左上角的$x$和$y$轴坐标与右下角的$x$和$y$轴坐标确定。我们根据上面的图的坐标信息来定义图中狗和猫的边界框。图中的坐标原点在图像的左上角，原点往右和往下分别为$x$轴和$y$轴的正方向。"
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
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   "source": [
    "# bbox是bounding box的缩写\n",
    "dog_bbox, cat_bbox = [60, 45, 378, 516], [400, 112, 655, 493]"
   ]
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   "metadata": {},
   "source": [
    "我们可以在图中将边界框画出来，以检查其是否准确。画之前，我们定义一个辅助函数`bbox_to_rect`。它将边界框表示成matplotlib的边界框格式。"
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  {
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   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
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   "source": [
    "def bbox_to_rect(bbox, color):  # 本函数已保存在d2lzh包中方便以后使用\n",
    "    # 将边界框(左上x, 左上y, 右下x, 右下y)格式转换成matplotlib格式：\n",
    "    # ((左上x, 左上y), 宽, 高)\n",
    "    return d2l.plt.Rectangle(\n",
    "        xy=(bbox[0], bbox[1]), width=bbox[2]-bbox[0], height=bbox[3]-bbox[1],\n",
    "        fill=False, edgecolor=color, linewidth=2)"
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   "metadata": {},
   "source": [
    "我们将边界框加载在图像上，可以看到目标的主要轮廓基本在框内。"
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   "source": [
    "fig = d2l.plt.imshow(img)\n",
    "fig.axes.add_patch(bbox_to_rect(dog_bbox, 'blue'))\n",
    "fig.axes.add_patch(bbox_to_rect(cat_bbox, 'red'));"
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    "## 小结\n",
    "\n",
    "* 在目标检测里不仅需要找出图像里面所有感兴趣的目标，而且要知道它们的位置。位置一般由矩形边界框来表示。\n",
    "\n",
    "## 练习\n",
    "\n",
    "* 找一些图像，尝试标注其中目标的边界框。比较标注边界框与标注类别所花时间的差异。\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "## 扫码直达[讨论区](https://discuss.gluon.ai/t/topic/7023)\n",
    "\n",
    "![](img/qr_bounding-box.svg)"
   ]
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