PNG_preparation_mini_assignment_answers.ipynb

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   "execution_count": null,
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   "source": [
    "standardized_images=[]\n",
    "for i in range(20):\n",
    "    img=resize_images_PIL_jpg[i]\n",
    "    img=(img-img.mean())/img.std()\n",
    "    standardized_images.append(img)\n",
    "standardized_images=np.array(standardized_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa59e610",
   "metadata": {},
   "outputs": [],
   "source": [
    "from skimage.exposure import histogram\n",
    "fig = plt.figure(figsize=(20, 15))\n",
    "rows = 5\n",
    "columns = 4\n",
    "for i in range(20):\n",
    "    fig.add_subplot(rows, columns, i+1)\n",
    "    img=standardized_images[i]\n",
    "    hist_0,edges_0=histogram(img[:,:,0])\n",
    "    hist_1,edges_1=histogram(img[:,:,1])\n",
    "    hist_2,edges_2=histogram(img[:,:,2])\n",
    "    plt.plot(edges_0,hist_0)\n",
    "    plt.plot(edges_1,hist_1)\n",
    "    plt.plot(edges_2,hist_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "032c782f",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(20, 15))\n",
    "rows = 5\n",
    "columns = 4\n",
    "for i in range(20):\n",
    "    fig.add_subplot(rows, columns, i+1)\n",
    "    img=standardized_images[i]\n",
    "    plt.imshow(img)\n",
    "    plt.axis('off')\n",
    "    plt.title(img.shape)"
   ]
  }
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