H/hog-feature-extraction/hog.ipynb

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 "metadata": {
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    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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 "nbformat": 4,
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 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing required libraries\n",
    "from skimage.io import imread\n",
    "from skimage.transform import resize\n",
    "from skimage.feature import hog\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reading the image\n",
    "img = imread('cat.jpg')\n",
    "plt.axis(\"off\")\n",
    "plt.imshow(img)\n",
    "print(img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#resizing image\n",
    "resized_img = resize(img, (128*4, 64*4))\n",
    "plt.axis(\"off\")\n",
    "plt.imshow(resized_img)\n",
    "print(resized_img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating hog features\n",
    "fd, hog_image = hog(resized_img, orientations=9, pixels_per_cell=(8, 8),\n",
    "                \tcells_per_block=(2, 2), visualize=True, multichannel=True)\n",
    "print(fd.shape)\n",
    "plt.axis(\"off\")\n",
    "plt.imshow(hog_image, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the images\n",
    "plt.imsave(\"resized_img.jpg\", resized_img)\n",
    "plt.imsave(\"hog_image.jpg\", hog_image, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}