13_开运算与闭运算.ipynb

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   "source": [
    "# 开运算与闭运算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. 开运算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2 #opencv的缩写为cv2\n",
    "import matplotlib.pyplot as plt # matplotlib库用于绘图展示\n",
    "import numpy as np   # numpy数值计算工具包\n",
    "\n",
    "# 魔法指令，直接展示图，Jupyter notebook特有\n",
    "%matplotlib inline   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 开：先腐蚀，再膨胀\n",
    "img = cv2.imread('01_Picture/05_Dige.png')\n",
    "\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "opening = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel) \n",
    "\n",
    "cv2.imshow('opening',opening)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. 闭运算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 闭：先膨胀，再腐蚀\n",
    "img = cv2.imread('01_Picture/05_Dige.png')\n",
    "\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "closing = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel) \n",
    "\n",
    "cv2.imshow('closing',closing)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. 梯度运算"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 梯度 = 腐蚀-膨胀\n",
    "pie = cv2.imread('01_Picture/06_pie.png')\n",
    "\n",
    "kernel = np.ones((7,7),np.uint8)\n",
    "dilate = cv2.dilate(pie,kernel,iterations=5) \n",
    "erosion = cv2.erode(pie,kernel,iterations=5) \n",
    "\n",
    "res = np.hstack((dilate,erosion))\n",
    "\n",
    "cv2.imshow('res',res)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "gradient = cv2.morphologyEx(pie,cv2.MORPH_GRADIENT,kernel)\n",
    "cv2.imshow('gradient',gradient)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  }
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