edge_extract.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def edge_extract(input, output):\n",
    "    #img = cv2.imread(\"labels_pixel/RGB-PanSharpen_AOI_2_Vegas_img10_mask.png\", 0)\n",
    "    img = cv2.imread(input, 0)\n",
    "    imgGau = cv2.GaussianBlur(img,(3,3),0)\n",
    "    gray_lap = cv2.Laplacian(imgGau, cv2.CV_16S, ksize=3)\n",
    "    dst = cv2.convertScaleAbs(gray_lap)\n",
    "    dst = cv2.resize(dst,(800,800))\n",
    "    dst[dst>0]=200\n",
    "    bond = numpy.hstack((img,dst))\n",
    "#     plt.rcParams['figure.dpi'] = 200\n",
    "#     plt.imshow(dst,cmap=plt.cm.gray)\n",
    "    cv2.imwrite(output,dst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def batch_edge_extract(in_dir,out_dir):\n",
    "    i = 1 \n",
    "    for img in tqdm(os.listdir(in_dir)):\n",
    "        if img.split('.')[-1]!='png':\n",
    "            continue\n",
    "        i+=1\n",
    "        crt_img = os.path.join(in_dir, img)\n",
    "        out_img = os.path.join(out_dir, img)\n",
    "        if os.path.exists(out_img):\n",
    "            print(out_img,'exists!\\n ')\n",
    "            continue\n",
    "        edge_extract(crt_img, out_img)\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 89%|████████▊ | 209/236 [00:00<00:00, 1913.41it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 236/236 [00:00<00:00, 521.03it/s] "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "236\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "batch_edge_extract('labels_pixel','labels_edge')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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