Lecture 13 Threshold.ipynb

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   "cell_type": "code",
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   "source": [
    "import cv2\n",
    "import numpy as np"
   ]
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   "source": [
    "## Simple Threshold"
   ]
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    "img = cv2.imread(\"fb.jpg\")\n",
    "img = cv2.resize(img , (550,500))\n",
    "img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)    # convert gray\n",
    "\n",
    "_,th = cv2.threshold(img, 90, 255, cv2.THRESH_BINARY) \n",
    "# _,th = cv2.threshold(img, 60, 255, cv2.THRESH_BINARY_INV) \n",
    "\n",
    "cv2.imshow(\"Threshold\", th)\n",
    "cv2.imshow(\"Children\", img)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8d2a027",
   "metadata": {},
   "source": [
    "## Otsu's Binarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4b1db4cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "e05a0326",
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv2.imread(\"lf.jpg\")\n",
    "img = cv2.resize(img , (550,500))\n",
    "img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)    # convert gray\n",
    "\n",
    "# hist = cv2.calcHist([img], [0], None, [255], [0,255])\n",
    "# plt.plot(hist)\n",
    "# plt.show()\n",
    "\n",
    "_,th = cv2.threshold(img, 170, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) \n",
    "\n",
    "cv2.imshow(\"Threshold\", th)\n",
    "cv2.imshow(\"boy\", img)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "cd9c498c",
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   "cell_type": "code",
   "execution_count": null,
   "id": "630e7e73",
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   "outputs": [],
   "source": []
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