transforms.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import torchvision.transforms as T\n",
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch_transform = T.Compose([\n",
    "    T.RandomCrop(32, padding=4),\n",
    "    T.RandomHorizontalFlip(),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('data/cifar-10-batches-py/data_batch_1', 'rb') as f:\n",
    "    cifar10 = pickle.load(f, encoding='latin1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "np_image = cifar10['data'][0].reshape(3, 32, 32).transpose(1, 2, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f21a256d8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(np_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "pil_image = Image.fromarray(np_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1cafff98>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(pil_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1edd79b0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pil_image_transformed = torch_transform(pil_image)\n",
    "plt.imshow(pil_image_transformed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1efb5e48>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np_image_padded = np.pad(np_image, ((4, 4), (4,4), (0,0)), 'constant')\n",
    "plt.imshow(np_image_padded)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def crop(image, i, j, h, w):\n",
    "    return image[i: i + h, j: j+w]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1c8bd128>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np_image_cropped = crop(np_image_padded, 6, 1, 32, 32)\n",
    "plt.imshow(np_image_cropped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1edce128>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np_image_from_pil = np.asarray(pil_image_transformed)\n",
    "plt.imshow(np_image_from_pil)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array_equal(np_image_cropped, np_image_from_pil)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4f1c3b2cc0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(np.fliplr(np_image_cropped))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        ...,\n",
       "        [130,  92,  53],\n",
       "        [142, 105,  68],\n",
       "        [130,  94,  58]],\n",
       "\n",
       "       [[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        ...,\n",
       "        [132,  90,  49],\n",
       "        [135,  93,  51],\n",
       "        [130,  90,  50]],\n",
       "\n",
       "       [[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        ...,\n",
       "        [121,  79,  41],\n",
       "        [119,  79,  40],\n",
       "        [103,  67,  32]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        ...,\n",
       "        [ 92,  67,  46],\n",
       "        [103,  78,  57],\n",
       "        [170, 140, 104]],\n",
       "\n",
       "       [[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        ...,\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0]],\n",
       "\n",
       "       [[  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
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       "        [  0,   0,   0],\n",
       "        [  0,   0,   0],\n",
       "        [  0,   0,   0]]], dtype=uint8)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
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    "np_image_cropped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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