flower classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "import torch.nn.functional as F\n",
    "import torchvision\n",
    "from torchvision import datasets, transforms, models\n",
    "import json\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/torchvision/transforms/transforms.py:693: UserWarning: The use of the transforms.RandomSizedCrop transform is deprecated, please use transforms.RandomResizedCrop instead.\n",
      "  warnings.warn(\"The use of the transforms.RandomSizedCrop transform is deprecated, \" +\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data: 6552 images / 103 batches\n",
      "Valid data: 818 images / 13 batches\n",
      "Test  data: 818 images / 13 batches\n"
     ]
    }
   ],
   "source": [
    "data_dir = 'flower_data'\n",
    "train_dir = data_dir + '/train'\n",
    "valid_dir = data_dir + '/valid'\n",
    "\n",
    "# arrays to normalization\n",
    "normalize_mean = np.array([0.485, 0.456, 0.406])\n",
    "normalize_std = np.array([0.229, 0.224, 0.225])\n",
    "\n",
    "# Define your transforms for the training and validation sets\n",
    "data_transforms = {}\n",
    "\n",
    "# transforms to train data set\n",
    "data_transforms['train'] = transforms.Compose([\n",
    "    transforms.RandomChoice([\n",
    "        transforms.RandomHorizontalFlip(p=0.5),\n",
    "        transforms.RandomVerticalFlip(p=0.5),\n",
    "        transforms.RandomRotation(30),\n",
    "        ]),\n",
    "    transforms.Resize(300),\n",
    "    transforms.RandomSizedCrop(224),\n",
    "    transforms.Resize(100),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize(\n",
    "        normalize_mean,\n",
    "        normalize_std)\n",
    "    ])\n",
    "\n",
    "# transforms to valid data set\n",
    "data_transforms['valid'] = transforms.Compose([\n",
    "    transforms.RandomChoice([\n",
    "    transforms.RandomHorizontalFlip(p=0.5),\n",
    "    transforms.RandomVerticalFlip(p=0.5),\n",
    "    transforms.RandomRotation(60),\n",
    "    ]),\n",
    "    transforms.Resize(300),\n",
    "    transforms.CenterCrop(224),\n",
    "    transforms.Resize(100),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize(\n",
    "        normalize_mean,\n",
    "        normalize_std)\n",
    "    ])\n",
    "\n",
    "# transforms to test data set\n",
    "data_transforms['test'] = transforms.Compose([\n",
    "    transforms.RandomChoice([\n",
    "        transforms.RandomRotation(45),\n",
    "        transforms.RandomRotation(75),\n",
    "        transforms.RandomRotation(90),\n",
    "        ]),\n",
    "    transforms.Resize(300),\n",
    "    transforms.CenterCrop(224),\n",
    "    transforms.Resize(100),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize(\n",
    "        normalize_mean,\n",
    "        normalize_std)\n",
    "    ])\n",
    "\n",
    "# Load the datasets with ImageFolder\n",
    "image_datasets = {}\n",
    "image_datasets['train_data'] = datasets.ImageFolder(data_dir + '/train', transform=data_transforms['train'])\n",
    "image_datasets['valid_data'] = datasets.ImageFolder(data_dir + '/valid', transform=data_transforms['valid'])\n",
    "image_datasets['test_data'] = datasets.ImageFolder(data_dir + '/valid', transform=data_transforms['test'])\n",
    "\n",
    "# Using the image datasets and the transforms, define the dataloaders\n",
    "dataloaders = {}\n",
    "dataloaders['train_data'] = torch.utils.data.DataLoader(image_datasets['train_data'], batch_size=64, shuffle=True)\n",
    "dataloaders['valid_data'] = torch.utils.data.DataLoader(image_datasets['valid_data'], batch_size=64, shuffle=False)\n",
    "dataloaders['test_data'] = torch.utils.data.DataLoader(image_datasets['test_data'], batch_size=64, shuffle=True)\n",
    "print(f\"Train data: {len(dataloaders['train_data'].dataset)} images / {len(dataloaders['train_data'])} batches\")\n",
    "print(f\"Valid data: {len(dataloaders['valid_data'].dataset)} images / {len(dataloaders['valid_data'])} batches\")\n",
    "print(f\"Test  data: {len(dataloaders['test_data'].dataset)} images / {len(dataloaders['test_data'])} batches\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'pink primrose', 1: 'globe thistle', 2: 'blanket flower', 3: 'trumpet creeper', 4: 'blackberry lily', 5: 'snapdragon', 6: \"colt's foot\", 7: 'king protea', 8: 'spear thistle', 9: 'yellow iris', 10: 'globe-flower', 11: 'purple coneflower', 12: 'peruvian lily', 13: 'balloon flower', 14: 'hard-leaved pocket orchid', 15: 'giant white arum lily', 16: 'fire lily', 17: 'pincushion flower', 18: 'fritillary', 19: 'red ginger', 20: 'grape hyacinth', 21: 'corn poppy', 22: 'prince of wales feathers', 23: 'stemless gentian', 24: 'artichoke', 25: 'canterbury bells', 26: 'sweet william', 27: 'carnation', 28: 'garden phlox', 29: 'love in the mist', 30: 'mexican aster', 31: 'alpine sea holly', 32: 'ruby-lipped cattleya', 33: 'cape flower', 34: 'great masterwort', 35: 'siam tulip', 36: 'sweet pea', 37: 'lenten rose', 38: 'barbeton daisy', 39: 'daffodil', 40: 'sword lily', 41: 'poinsettia', 42: 'bolero deep blue', 43: 'wallflower', 44: 'marigold', 45: 'buttercup', 46: 'oxeye daisy', 47: 'english marigold', 48: 'common dandelion', 49: 'petunia', 50: 'wild pansy', 51: 'primula', 52: 'sunflower', 53: 'pelargonium', 54: 'bishop of llandaff', 55: 'gaura', 56: 'geranium', 57: 'orange dahlia', 58: 'tiger lily', 59: 'pink-yellow dahlia', 60: 'cautleya spicata', 61: 'japanese anemone', 62: 'black-eyed susan', 63: 'silverbush', 64: 'californian poppy', 65: 'osteospermum', 66: 'spring crocus', 67: 'bearded iris', 68: 'windflower', 69: 'moon orchid', 70: 'tree poppy', 71: 'gazania', 72: 'azalea', 73: 'water lily', 74: 'rose', 75: 'thorn apple', 76: 'morning glory', 77: 'passion flower', 78: 'lotus lotus', 79: 'toad lily', 80: 'bird of paradise', 81: 'anthurium', 82: 'frangipani', 83: 'clematis', 84: 'hibiscus', 85: 'columbine', 86: 'desert-rose', 87: 'tree mallow', 88: 'magnolia', 89: 'cyclamen', 90: 'watercress', 91: 'monkshood', 92: 'canna lily', 93: 'hippeastrum', 94: 'bee balm', 95: 'ball moss', 96: 'foxglove', 97: 'bougainvillea', 98: 'camellia', 99: 'mallow', 100: 'mexican petunia', 101: 'bromelia'}\n"
     ]
    }
   ],
   "source": [
    "with open('cat_to_name.json', 'r') as f:\n",
    "    cat_to_name = json.load(f)\n",
    "\n",
    "class_to_idx = image_datasets['train_data'].class_to_idx\n",
    "\n",
    "cat_label_to_name = {}\n",
    "for cat, label in class_to_idx.items():\n",
    "    cat_label_to_name[label] = cat_to_name.get(cat)\n",
    "\n",
    "print(cat_label_to_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# functions to show an image\n",
    "def imgview(img, title, ax):\n",
    "    # un-normalize\n",
    "    for i in range(img.shape[0]):\n",
    "        img[i] = img[i] * normalize_std[i] + normalize_mean[i]\n",
    "    # convert from Tensor image\n",
    "    ax.imshow(np.transpose(img, (1, 2, 0)))\n",
    "    ax.set_title(title)\n",
    "\n",
    "# obtain one batch of training images\n",
    "dataiter = iter(dataloaders['train_data'])\n",
    "images, labels = dataiter.next()\n",
    "images = images.numpy() # convert images to numpy for display\n",
    "\n",
    "# show some test images\n",
    "fig = plt.figure(figsize=(15, 15))\n",
    "fig_rows, fig_cols = 2,2\n",
    "for index in np.arange(fig_rows*fig_cols):\n",
    "    img = images[index]\n",
    "    label = labels[index].item()\n",
    "    title = f'Label: {label}\\n{cat_label_to_name[label].title()}'\n",
    "    ax = fig.add_subplot(fig_rows, fig_cols, index+1, xticks=[], yticks=[])\n",
    "    imgview(img, title, ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(3, 64, 5, padding = 3)\n",
    "        self.conv2 = nn.Conv2d(64, 128, 5, padding = 3)\n",
    "        self.conv3 = nn.Conv2d(128, 256, 3, padding = 1)\n",
    "        self.conv4 = nn.Conv2d(256, 512, 3, padding = 1)\n",
    "        self.conv5 = nn.Conv2d(512, 512, 3, padding = 2)\n",
    "        self.pool = nn.MaxPool2d(3, 2)\n",
    "        self.fc1 = nn.Linear(512 * 6 * 6, 1024)\n",
    "        self.fc2 = nn.Linear(1024, 512)\n",
    "        self.fc3 = nn.Linear(512, 102)\n",
    "        self.drop = nn.Dropout(p=0.5)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.pool(F.relu(self.conv1(x)))\n",
    "        x = self.pool(F.relu(self.conv2(x)))\n",
    "        x = self.pool(F.relu(self.conv3(x)))\n",
    "        x = F.relu(self.conv4(x))\n",
    "        x = self.pool(F.relu(self.conv5(x)))\n",
    "        x = x.view(-1, 512 * 6 * 6)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = self.drop(x)\n",
    "        x = F.relu(self.fc2(x))\n",
    "        x = self.drop(x)\n",
    "        x = self.fc3(x)\n",
    "        return x\n",
    "\n",
    "net = Net()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda:0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Net(\n",
       "  (conv1): Conv2d(3, 64, kernel_size=(5, 5), stride=(1, 1), padding=(3, 3))\n",
       "  (conv2): Conv2d(64, 128, kernel_size=(5, 5), stride=(1, 1), padding=(3, 3))\n",
       "  (conv3): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (conv4): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (conv5): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2))\n",
       "  (pool): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  (fc1): Linear(in_features=18432, out_features=1024, bias=True)\n",
       "  (fc2): Linear(in_features=1024, out_features=512, bias=True)\n",
       "  (fc3): Linear(in_features=512, out_features=102, bias=True)\n",
       "  (drop): Dropout(p=0.5, inplace=False)\n",
       ")"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "# Assuming that we are on a CUDA machine, this should print a CUDA device:\n",
    "print(device)\n",
    "net.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/800\n",
      "----------\n",
      "train Loss: 4.6224 Acc: 0.0099\n",
      "test Loss: 4.6188 Acc: 0.0220\n",
      "Epoch 2/800\n",
      "----------\n",
      "train Loss: 4.6172 Acc: 0.0285\n",
      "test Loss: 4.6129 Acc: 0.0342\n",
      "Epoch 3/800\n",
      "----------\n",
      "train Loss: 4.6113 Acc: 0.0305\n",
      "test Loss: 4.6078 Acc: 0.0355\n",
      "Epoch 4/800\n",
      "----------\n",
      "train Loss: 4.6030 Acc: 0.0319\n",
      "test Loss: 4.5931 Acc: 0.0342\n",
      "Epoch 5/800\n",
      "----------\n",
      "train Loss: 4.5782 Acc: 0.0299\n",
      "test Loss: 4.5476 Acc: 0.0244\n",
      "Epoch 6/800\n",
      "----------\n",
      "train Loss: 4.5364 Acc: 0.0313\n",
      "test Loss: 4.5184 Acc: 0.0330\n",
      "Epoch 7/800\n",
      "----------\n",
      "train Loss: 4.5295 Acc: 0.0302\n",
      "test Loss: 4.5044 Acc: 0.0330\n",
      "Epoch 8/800\n",
      "----------\n",
      "train Loss: 4.5173 Acc: 0.0311\n",
      "test Loss: 4.5009 Acc: 0.0293\n",
      "Epoch 9/800\n",
      "----------\n",
      "train Loss: 4.5116 Acc: 0.0324\n",
      "test Loss: 4.5011 Acc: 0.0257\n",
      "Epoch 10/800\n",
      "----------\n",
      "train Loss: 4.4936 Acc: 0.0411\n",
      "test Loss: 4.4634 Acc: 0.0403\n",
      "Epoch 11/800\n",
      "----------\n",
      "train Loss: 4.4043 Acc: 0.0508\n",
      "test Loss: 4.3041 Acc: 0.0526\n",
      "Epoch 12/800\n",
      "----------\n",
      "train Loss: 4.2655 Acc: 0.0505\n",
      "test Loss: 4.2054 Acc: 0.0391\n",
      "Epoch 13/800\n",
      "----------\n",
      "train Loss: 4.1981 Acc: 0.0475\n",
      "test Loss: 4.1413 Acc: 0.0428\n",
      "Epoch 14/800\n",
      "----------\n",
      "train Loss: 4.1455 Acc: 0.0545\n",
      "test Loss: 4.1283 Acc: 0.0465\n",
      "Epoch 15/800\n",
      "----------\n",
      "train Loss: 4.1041 Acc: 0.0549\n",
      "test Loss: 4.0430 Acc: 0.0587\n",
      "Epoch 16/800\n",
      "----------\n",
      "train Loss: 4.0385 Acc: 0.0620\n",
      "test Loss: 3.9641 Acc: 0.0575\n",
      "Epoch 17/800\n",
      "----------\n",
      "train Loss: 3.9683 Acc: 0.0691\n",
      "test Loss: 3.9127 Acc: 0.0660\n",
      "Epoch 18/800\n",
      "----------\n",
      "train Loss: 3.9029 Acc: 0.0791\n",
      "test Loss: 3.8170 Acc: 0.0868\n",
      "Epoch 19/800\n",
      "----------\n",
      "train Loss: 3.8447 Acc: 0.0823\n",
      "test Loss: 3.7667 Acc: 0.0892\n",
      "Epoch 20/800\n",
      "----------\n",
      "train Loss: 3.7665 Acc: 0.0923\n",
      "test Loss: 3.6709 Acc: 0.0795\n",
      "Epoch 21/800\n",
      "----------\n",
      "train Loss: 3.7405 Acc: 0.0896\n",
      "test Loss: 3.6539 Acc: 0.0966\n",
      "Epoch 22/800\n",
      "----------\n",
      "train Loss: 3.6884 Acc: 0.0955\n",
      "test Loss: 3.5913 Acc: 0.1161\n",
      "Epoch 23/800\n",
      "----------\n",
      "train Loss: 3.6351 Acc: 0.1090\n",
      "test Loss: 3.5567 Acc: 0.1051\n",
      "Epoch 24/800\n",
      "----------\n",
      "train Loss: 3.6052 Acc: 0.1045\n",
      "test Loss: 3.5694 Acc: 0.1088\n",
      "Epoch 25/800\n",
      "----------\n",
      "train Loss: 3.5976 Acc: 0.1107\n",
      "test Loss: 3.4927 Acc: 0.1112\n",
      "Epoch 26/800\n",
      "----------\n",
      "train Loss: 3.5447 Acc: 0.1145\n",
      "test Loss: 3.4801 Acc: 0.1027\n",
      "Epoch 27/800\n",
      "----------\n",
      "train Loss: 3.5153 Acc: 0.1216\n",
      "test Loss: 3.4706 Acc: 0.1149\n",
      "Epoch 28/800\n",
      "----------\n",
      "train Loss: 3.5047 Acc: 0.1201\n",
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      "Epoch 707/800\n",
      "----------\n",
      "train Loss: 0.3164 Acc: 0.9144\n",
      "test Loss: 1.0377 Acc: 0.8068\n",
      "Epoch 708/800\n",
      "----------\n",
      "train Loss: 0.2652 Acc: 0.9270\n",
      "test Loss: 1.1411 Acc: 0.7958\n",
      "Epoch 709/800\n",
      "----------\n",
      "train Loss: 0.2712 Acc: 0.9261\n",
      "test Loss: 1.1988 Acc: 0.7836\n",
      "Epoch 710/800\n",
      "----------\n",
      "train Loss: 0.2936 Acc: 0.9183\n",
      "test Loss: 1.2510 Acc: 0.7885\n",
      "Epoch 711/800\n",
      "----------\n",
      "train Loss: 0.2657 Acc: 0.9252\n",
      "test Loss: 1.0204 Acc: 0.8093\n",
      "Epoch 712/800\n",
      "----------\n",
      "train Loss: 0.2677 Acc: 0.9243\n",
      "test Loss: 1.0765 Acc: 0.8007\n",
      "Epoch 713/800\n",
      "----------\n",
      "train Loss: 0.2842 Acc: 0.9191\n",
      "test Loss: 1.1858 Acc: 0.7910\n",
      "Epoch 714/800\n",
      "----------\n",
      "train Loss: 0.2901 Acc: 0.9171\n",
      "test Loss: 1.1241 Acc: 0.7934\n",
      "Epoch 715/800\n",
      "----------\n",
      "train Loss: 0.2790 Acc: 0.9225\n",
      "test Loss: 1.0396 Acc: 0.7971\n",
      "Epoch 716/800\n",
      "----------\n",
      "train Loss: 0.2739 Acc: 0.9289\n",
      "test Loss: 1.1145 Acc: 0.7983\n",
      "Epoch 717/800\n",
      "----------\n",
      "train Loss: 0.2467 Acc: 0.9309\n",
      "test Loss: 1.1746 Acc: 0.7910\n",
      "Epoch 718/800\n",
      "----------\n",
      "train Loss: 0.2908 Acc: 0.9197\n",
      "test Loss: 1.1836 Acc: 0.7861\n",
      "Epoch 719/800\n",
      "----------\n",
      "train Loss: 0.2750 Acc: 0.9249\n",
      "test Loss: 1.0743 Acc: 0.8093\n",
      "Epoch 720/800\n",
      "----------\n",
      "train Loss: 0.2925 Acc: 0.9197\n",
      "test Loss: 1.0349 Acc: 0.8105\n",
      "Epoch 721/800\n",
      "----------\n",
      "train Loss: 0.2512 Acc: 0.9290\n",
      "test Loss: 1.0237 Acc: 0.8130\n",
      "Epoch 722/800\n",
      "----------\n",
      "train Loss: 0.2752 Acc: 0.9272\n",
      "test Loss: 1.0096 Acc: 0.8044\n",
      "Epoch 723/800\n",
      "----------\n",
      "train Loss: 0.2794 Acc: 0.9254\n",
      "test Loss: 1.0887 Acc: 0.7958\n",
      "Epoch 724/800\n",
      "----------\n",
      "train Loss: 0.2593 Acc: 0.9316\n",
      "test Loss: 1.1119 Acc: 0.7995\n",
      "Epoch 725/800\n",
      "----------\n",
      "train Loss: 0.2738 Acc: 0.9235\n",
      "test Loss: 1.0993 Acc: 0.8007\n",
      "Epoch 726/800\n",
      "----------\n",
      "train Loss: 0.2740 Acc: 0.9272\n",
      "test Loss: 1.0842 Acc: 0.7995\n",
      "Epoch 727/800\n",
      "----------\n",
      "train Loss: 0.2607 Acc: 0.9296\n",
      "test Loss: 1.0521 Acc: 0.8032\n",
      "Epoch 728/800\n",
      "----------\n",
      "train Loss: 0.3026 Acc: 0.9144\n",
      "test Loss: 1.1571 Acc: 0.7971\n",
      "Epoch 729/800\n",
      "----------\n",
      "train Loss: 0.2619 Acc: 0.9264\n",
      "test Loss: 1.0530 Acc: 0.7971\n",
      "Epoch 730/800\n",
      "----------\n",
      "train Loss: 0.2739 Acc: 0.9267\n",
      "test Loss: 1.1146 Acc: 0.7958\n",
      "Epoch 731/800\n",
      "----------\n",
      "train Loss: 0.2697 Acc: 0.9234\n",
      "test Loss: 1.0925 Acc: 0.8007\n",
      "Epoch 732/800\n",
      "----------\n",
      "train Loss: 0.2600 Acc: 0.9296\n",
      "test Loss: 0.9607 Acc: 0.8166\n",
      "Epoch 733/800\n",
      "----------\n",
      "train Loss: 0.2666 Acc: 0.9251\n",
      "test Loss: 1.0393 Acc: 0.8068\n",
      "Epoch 734/800\n",
      "----------\n",
      "train Loss: 0.2693 Acc: 0.9240\n",
      "test Loss: 1.1203 Acc: 0.8056\n",
      "Epoch 735/800\n",
      "----------\n",
      "train Loss: 0.2600 Acc: 0.9310\n",
      "test Loss: 1.1576 Acc: 0.7971\n",
      "Epoch 736/800\n",
      "----------\n",
      "train Loss: 0.2613 Acc: 0.9293\n",
      "test Loss: 1.0966 Acc: 0.7958\n",
      "Epoch 737/800\n",
      "----------\n",
      "train Loss: 0.2688 Acc: 0.9284\n",
      "test Loss: 1.2185 Acc: 0.7934\n",
      "Epoch 738/800\n",
      "----------\n",
      "train Loss: 0.2864 Acc: 0.9206\n",
      "test Loss: 1.2573 Acc: 0.7897\n",
      "Epoch 739/800\n",
      "----------\n",
      "train Loss: 0.2870 Acc: 0.9241\n",
      "test Loss: 1.2218 Acc: 0.7971\n",
      "Epoch 740/800\n",
      "----------\n",
      "train Loss: 0.2717 Acc: 0.9251\n",
      "test Loss: 1.0399 Acc: 0.8007\n",
      "Epoch 741/800\n",
      "----------\n",
      "train Loss: 0.2826 Acc: 0.9208\n",
      "test Loss: 1.0683 Acc: 0.8154\n",
      "Epoch 742/800\n",
      "----------\n",
      "train Loss: 0.2759 Acc: 0.9209\n",
      "test Loss: 1.1191 Acc: 0.7897\n",
      "Epoch 743/800\n",
      "----------\n",
      "train Loss: 0.2759 Acc: 0.9228\n",
      "test Loss: 1.1362 Acc: 0.7958\n",
      "Epoch 744/800\n",
      "----------\n",
      "train Loss: 0.2813 Acc: 0.9226\n",
      "test Loss: 1.1245 Acc: 0.8020\n",
      "Epoch 745/800\n",
      "----------\n",
      "train Loss: 0.2512 Acc: 0.9264\n",
      "test Loss: 1.1284 Acc: 0.7983\n",
      "Epoch 746/800\n",
      "----------\n",
      "train Loss: 0.2656 Acc: 0.9261\n",
      "test Loss: 1.1520 Acc: 0.8117\n",
      "Epoch 747/800\n",
      "----------\n",
      "train Loss: 0.2564 Acc: 0.9241\n",
      "test Loss: 1.1417 Acc: 0.8007\n",
      "Epoch 748/800\n",
      "----------\n",
      "train Loss: 0.2410 Acc: 0.9339\n",
      "test Loss: 1.0511 Acc: 0.8044\n",
      "Epoch 749/800\n",
      "----------\n",
      "train Loss: 0.2692 Acc: 0.9310\n",
      "test Loss: 1.1237 Acc: 0.8068\n",
      "Epoch 750/800\n",
      "----------\n",
      "train Loss: 0.2838 Acc: 0.9246\n",
      "test Loss: 1.0956 Acc: 0.8105\n",
      "Epoch 751/800\n",
      "----------\n",
      "train Loss: 0.2685 Acc: 0.9251\n",
      "test Loss: 1.2314 Acc: 0.7848\n",
      "Epoch 752/800\n",
      "----------\n",
      "train Loss: 0.2572 Acc: 0.9260\n",
      "test Loss: 1.0304 Acc: 0.8056\n",
      "Epoch 753/800\n",
      "----------\n",
      "train Loss: 0.2603 Acc: 0.9263\n",
      "test Loss: 1.1967 Acc: 0.7910\n",
      "Epoch 754/800\n",
      "----------\n",
      "train Loss: 0.2633 Acc: 0.9274\n",
      "test Loss: 1.0734 Acc: 0.7971\n",
      "Epoch 755/800\n",
      "----------\n",
      "train Loss: 0.2587 Acc: 0.9318\n",
      "test Loss: 1.0320 Acc: 0.8142\n",
      "Epoch 756/800\n",
      "----------\n",
      "train Loss: 0.2522 Acc: 0.9301\n",
      "test Loss: 1.0157 Acc: 0.8081\n",
      "Epoch 757/800\n",
      "----------\n",
      "train Loss: 0.2607 Acc: 0.9260\n",
      "test Loss: 1.1257 Acc: 0.7995\n",
      "Epoch 758/800\n",
      "----------\n",
      "train Loss: 0.2621 Acc: 0.9298\n",
      "test Loss: 1.0015 Acc: 0.7934\n",
      "Epoch 759/800\n",
      "----------\n",
      "train Loss: 0.2299 Acc: 0.9333\n",
      "test Loss: 1.1495 Acc: 0.8203\n",
      "Epoch 760/800\n",
      "----------\n",
      "train Loss: 0.2481 Acc: 0.9312\n",
      "test Loss: 1.1465 Acc: 0.7934\n",
      "Epoch 761/800\n",
      "----------\n",
      "train Loss: 0.2446 Acc: 0.9327\n",
      "test Loss: 1.0439 Acc: 0.8130\n",
      "Epoch 762/800\n",
      "----------\n",
      "train Loss: 0.2659 Acc: 0.9298\n",
      "test Loss: 1.0965 Acc: 0.8020\n",
      "Epoch 763/800\n",
      "----------\n",
      "train Loss: 0.2657 Acc: 0.9260\n",
      "test Loss: 1.0891 Acc: 0.8093\n",
      "Epoch 764/800\n",
      "----------\n",
      "train Loss: 0.2928 Acc: 0.9179\n",
      "test Loss: 1.0815 Acc: 0.7946\n",
      "Epoch 765/800\n",
      "----------\n",
      "train Loss: 0.2559 Acc: 0.9293\n",
      "test Loss: 1.0313 Acc: 0.8032\n",
      "Epoch 766/800\n",
      "----------\n",
      "train Loss: 0.2767 Acc: 0.9246\n",
      "test Loss: 1.2052 Acc: 0.7983\n",
      "Epoch 767/800\n",
      "----------\n",
      "train Loss: 0.2621 Acc: 0.9280\n",
      "test Loss: 1.1038 Acc: 0.8056\n",
      "Epoch 768/800\n",
      "----------\n",
      "train Loss: 0.2589 Acc: 0.9315\n",
      "test Loss: 1.1105 Acc: 0.7983\n",
      "Epoch 769/800\n",
      "----------\n",
      "train Loss: 0.2765 Acc: 0.9246\n",
      "test Loss: 1.2397 Acc: 0.7824\n",
      "Epoch 770/800\n",
      "----------\n",
      "train Loss: 0.2788 Acc: 0.9241\n",
      "test Loss: 1.2513 Acc: 0.7995\n",
      "Epoch 771/800\n",
      "----------\n",
      "train Loss: 0.2518 Acc: 0.9272\n",
      "test Loss: 1.0859 Acc: 0.8130\n",
      "Epoch 772/800\n",
      "----------\n",
      "train Loss: 0.2632 Acc: 0.9261\n",
      "test Loss: 1.1374 Acc: 0.7995\n",
      "Epoch 773/800\n",
      "----------\n",
      "train Loss: 0.2403 Acc: 0.9335\n",
      "test Loss: 1.0436 Acc: 0.8130\n",
      "Epoch 774/800\n",
      "----------\n",
      "train Loss: 0.2610 Acc: 0.9290\n",
      "test Loss: 1.2652 Acc: 0.7751\n",
      "Epoch 775/800\n",
      "----------\n",
      "train Loss: 0.2388 Acc: 0.9328\n",
      "test Loss: 1.1073 Acc: 0.8044\n",
      "Epoch 776/800\n",
      "----------\n",
      "train Loss: 0.2491 Acc: 0.9309\n",
      "test Loss: 1.1132 Acc: 0.8032\n",
      "Epoch 777/800\n",
      "----------\n",
      "train Loss: 0.2526 Acc: 0.9298\n",
      "test Loss: 1.1103 Acc: 0.8007\n",
      "Epoch 778/800\n",
      "----------\n",
      "train Loss: 0.2503 Acc: 0.9316\n",
      "test Loss: 1.1421 Acc: 0.8056\n",
      "Epoch 779/800\n",
      "----------\n",
      "train Loss: 0.2585 Acc: 0.9278\n",
      "test Loss: 1.2061 Acc: 0.7934\n",
      "Epoch 780/800\n",
      "----------\n",
      "train Loss: 0.2362 Acc: 0.9303\n",
      "test Loss: 1.0942 Acc: 0.8093\n",
      "Epoch 781/800\n",
      "----------\n",
      "train Loss: 0.2464 Acc: 0.9328\n",
      "test Loss: 1.1116 Acc: 0.8056\n",
      "Epoch 782/800\n",
      "----------\n",
      "train Loss: 0.2597 Acc: 0.9287\n",
      "test Loss: 1.1236 Acc: 0.7861\n",
      "Epoch 783/800\n",
      "----------\n",
      "train Loss: 0.2552 Acc: 0.9284\n",
      "test Loss: 1.1521 Acc: 0.7983\n",
      "Epoch 784/800\n",
      "----------\n",
      "train Loss: 0.2544 Acc: 0.9293\n",
      "test Loss: 1.2370 Acc: 0.7971\n",
      "Epoch 785/800\n",
      "----------\n",
      "train Loss: 0.2393 Acc: 0.9353\n",
      "test Loss: 1.1131 Acc: 0.8007\n",
      "Epoch 786/800\n",
      "----------\n",
      "train Loss: 0.2489 Acc: 0.9307\n",
      "test Loss: 1.1204 Acc: 0.8081\n",
      "Epoch 787/800\n",
      "----------\n",
      "train Loss: 0.2393 Acc: 0.9350\n",
      "test Loss: 1.1898 Acc: 0.7995\n",
      "Epoch 788/800\n",
      "----------\n",
      "train Loss: 0.2498 Acc: 0.9336\n",
      "test Loss: 1.1235 Acc: 0.7836\n",
      "Epoch 789/800\n",
      "----------\n",
      "train Loss: 0.2371 Acc: 0.9342\n",
      "test Loss: 1.0929 Acc: 0.8044\n",
      "Epoch 790/800\n",
      "----------\n",
      "train Loss: 0.2775 Acc: 0.9264\n",
      "test Loss: 1.1579 Acc: 0.8105\n",
      "Epoch 791/800\n",
      "----------\n",
      "train Loss: 0.2508 Acc: 0.9269\n",
      "test Loss: 1.1286 Acc: 0.8020\n",
      "Epoch 792/800\n",
      "----------\n",
      "train Loss: 0.2408 Acc: 0.9327\n",
      "test Loss: 1.1576 Acc: 0.7873\n",
      "Epoch 793/800\n",
      "----------\n",
      "train Loss: 0.2530 Acc: 0.9313\n",
      "test Loss: 1.1750 Acc: 0.8081\n",
      "Epoch 794/800\n",
      "----------\n",
      "train Loss: 0.2445 Acc: 0.9318\n",
      "test Loss: 1.1802 Acc: 0.7910\n",
      "Epoch 795/800\n",
      "----------\n",
      "train Loss: 0.2592 Acc: 0.9281\n",
      "test Loss: 0.9463 Acc: 0.8227\n",
      "Epoch 796/800\n",
      "----------\n",
      "train Loss: 0.2440 Acc: 0.9351\n",
      "test Loss: 1.0795 Acc: 0.8020\n",
      "Epoch 797/800\n",
      "----------\n",
      "train Loss: 0.2460 Acc: 0.9312\n",
      "test Loss: 1.1018 Acc: 0.8081\n",
      "Epoch 798/800\n",
      "----------\n",
      "train Loss: 0.2454 Acc: 0.9318\n",
      "test Loss: 1.2050 Acc: 0.8032\n",
      "Epoch 799/800\n",
      "----------\n",
      "train Loss: 0.2611 Acc: 0.9260\n",
      "test Loss: 1.0760 Acc: 0.8081\n",
      "Epoch 800/800\n",
      "----------\n",
      "train Loss: 0.2675 Acc: 0.9299\n",
      "test Loss: 1.0797 Acc: 0.8105\n",
      "Training complete in 1486m 47s\n",
      "Finished Training\n"
     ]
    }
   ],
   "source": [
    "trainloss = []\n",
    "trainacc = []\n",
    "testloss = []\n",
    "testacc = []\n",
    "since = time.time()\n",
    "for epoch in range(800):  # loop over the dataset multiple times\n",
    "    print('Epoch {}/{}'.format(epoch+1, 800))\n",
    "    print('-' * 10)\n",
    "\n",
    "    for phase in ['train','test']:\n",
    "        if phase == 'train':\n",
    "            dataloader = dataloaders['train_data']\n",
    "        elif phase == 'test':\n",
    "            dataloader = dataloaders['test_data']\n",
    "                \n",
    "        running_corrects = 0\n",
    "        running_loss = 0\n",
    "    \n",
    "        for data in dataloader:\n",
    "            # get the inputs; data is a list of [inputs, labels]\n",
    "            inputs, labels = data[0].to(device), data[1].to(device)\n",
    "            \n",
    "            # zero the parameter gradients\n",
    "            optimizer.zero_grad()\n",
    "\n",
    "            # forward + backward + optimize\n",
    "            outputs = net(inputs)\n",
    "            _, preds = torch.max(outputs.data, 1)\n",
    "            loss = criterion(outputs, labels)\n",
    "            \n",
    "            if phase == 'train':\n",
    "                loss.backward()\n",
    "                optimizer.step()\n",
    "\n",
    "            # acc loss\n",
    "            running_loss  += loss.item()\n",
    "            running_corrects += torch.sum(preds == labels.data).item()\n",
    "            \n",
    "        if phase==\"train\":\n",
    "            epoch_loss = running_loss / len(dataloaders['train_data'])\n",
    "            epoch_acc = running_corrects / len(image_datasets['train_data'])\n",
    "            trainloss.append(epoch_loss)\n",
    "            trainacc.append(epoch_acc)\n",
    "\n",
    "        elif phase == 'test':\n",
    "            epoch_loss = running_loss / len(dataloaders['test_data'])\n",
    "            epoch_acc = running_corrects / len(image_datasets['test_data'])\n",
    "            testloss.append(epoch_loss)\n",
    "            testacc.append(epoch_acc)\n",
    "        \n",
    "        print('{} Loss: {:.4f} Acc: {:.4f}'.format(phase, epoch_loss, epoch_acc))\n",
    "    \n",
    "time_elapsed = time.time() - since\n",
    "print('Training complete in {:.0f}m {:.0f}s'.format(time_elapsed // 60, time_elapsed % 60))\n",
    "print('Finished Training')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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": [
    "x = [i for i in range(len(trainacc))]\n",
    "\n",
    "ax = plt.gca()\n",
    "\n",
    "plt.title('my CNN')\n",
    "ax.plot(x, trainacc,color='green', label='train accuracy')\n",
    "ax.plot(x, testacc,color='red', label='test accuracy')\n",
    "plt.legend()\n",
    "plt.xlabel('epochs')\n",
    "plt.ylabel('rate')\n",
    "plt.savefig('cnn acc.png')\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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": [
    "y = [i for i in range(len(trainloss))]\n",
    "\n",
    "ay = plt.gca()\n",
    "plt.title('my CNN')\n",
    "ay.plot(y, trainloss, color='green', label='train loss')\n",
    "ay.plot(y, testloss, color='red', label='test loss')\n",
    "plt.legend()\n",
    "plt.xlabel('epochs')\n",
    "plt.ylabel('loss')\n",
    "plt.savefig('cnn loss.png')\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "data_loss = pd.DataFrame({'trainloss': trainloss, 'testloss': testloss})\n",
    "data_acc = pd.DataFrame({'trainacc': trainacc, 'testacc': testacc})\n",
    "data_loss.to_csv('cnn loss.csv')\n",
    "data_acc.to_csv(\"cnn acc.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH = './flower_cnn.pth'\n",
    "torch.save(net.state_dict(), PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# obtain one batch of training images\n",
    "dataiter = iter(dataloaders['test_data'])\n",
    "images, labels = dataiter.next()\n",
    "npimg = images.numpy() # convert images to numpy for display\n",
    "\n",
    "# show some test images\n",
    "fig = plt.figure(figsize=(15, 15))\n",
    "fig_rows, fig_cols = 2,2\n",
    "for index in np.arange(fig_rows*fig_cols):\n",
    "    img = npimg[index]\n",
    "    label = labels[index].item()\n",
    "    title = f'Label: {label}\\n{cat_label_to_name[label].title()}'\n",
    "    ax = fig.add_subplot(fig_rows, fig_cols, index+1, xticks=[], yticks=[])\n",
    "    imgview(img, title, ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net = Net()\n",
    "net.load_state_dict(torch.load(PATH))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs = net(images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted:  hippeastrum, hippeastrum,  rose, hippeastrum\n"
     ]
    }
   ],
   "source": [
    "_, predicted = torch.max(outputs, 1)\n",
    "predicted = predicted.numpy()\n",
    "print('Predicted: ', ', '.join('%5s' % cat_label_to_name[predicted[j]] for j in range(4)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the network on the 409 test images: 79.951100 %\n"
     ]
    }
   ],
   "source": [
    "correct = 0\n",
    "total = 0\n",
    "with torch.no_grad():\n",
    "    for data in dataloaders['test_data']:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs.data, 1)\n",
    "        total += labels.size(0)\n",
    "        correct += (predicted == labels).sum().item()\n",
    "\n",
    "print('Accuracy of the network on the 409 test images: %f %%' % (100 * correct / total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of pink primrose : 87 %\n",
      "Accuracy of globe thistle : 75 %\n",
      "Accuracy of blanket flower : 100 %\n",
      "Accuracy of trumpet creeper : 60 %\n",
      "Accuracy of blackberry lily : 100 %\n",
      "Accuracy of snapdragon : 80 %\n",
      "Accuracy of colt's foot : 60 %\n",
      "Accuracy of king protea : 60 %\n",
      "Accuracy of spear thistle : 100 %\n",
      "Accuracy of yellow iris : 85 %\n",
      "Accuracy of globe-flower :  0 %\n",
      "Accuracy of purple coneflower : 87 %\n",
      "Accuracy of peruvian lily : 63 %\n",
      "Accuracy of balloon flower : 75 %\n",
      "Accuracy of hard-leaved pocket orchid : 83 %\n",
      "Accuracy of giant white arum lily : 71 %\n",
      "Accuracy of fire lily : 50 %\n",
      "Accuracy of pincushion flower : 87 %\n",
      "Accuracy of fritillary : 91 %\n",
      "Accuracy of red ginger : 60 %\n",
      "Accuracy of grape hyacinth : 100 %\n",
      "Accuracy of corn poppy : 100 %\n",
      "Accuracy of prince of wales feathers : 100 %\n",
      "Accuracy of stemless gentian : 100 %\n",
      "Accuracy of artichoke : 85 %\n",
      "Accuracy of canterbury bells : 50 %\n",
      "Accuracy of sweet william : 60 %\n",
      "Accuracy of carnation : 50 %\n",
      "Accuracy of garden phlox : 66 %\n",
      "Accuracy of love in the mist : 42 %\n",
      "Accuracy of mexican aster : 85 %\n",
      "Accuracy of alpine sea holly : 50 %\n",
      "Accuracy of ruby-lipped cattleya : 66 %\n",
      "Accuracy of cape flower : 100 %\n",
      "Accuracy of great masterwort : 75 %\n",
      "Accuracy of siam tulip :  0 %\n",
      "Accuracy of sweet pea : 33 %\n",
      "Accuracy of lenten rose : 80 %\n",
      "Accuracy of barbeton daisy : 68 %\n",
      "Accuracy of daffodil : 83 %\n",
      "Accuracy of sword lily : 50 %\n",
      "Accuracy of poinsettia : 77 %\n",
      "Accuracy of bolero deep blue : 75 %\n",
      "Accuracy of wallflower : 94 %\n",
      "Accuracy of marigold : 100 %\n",
      "Accuracy of buttercup : 55 %\n",
      "Accuracy of oxeye daisy : 87 %\n",
      "Accuracy of english marigold : 85 %\n",
      "Accuracy of common dandelion : 90 %\n",
      "Accuracy of petunia : 75 %\n",
      "Accuracy of wild pansy : 80 %\n",
      "Accuracy of primula : 88 %\n",
      "Accuracy of sunflower : 100 %\n",
      "Accuracy of pelargonium : 100 %\n",
      "Accuracy of bishop of llandaff : 100 %\n",
      "Accuracy of gaura : 100 %\n",
      "Accuracy of geranium : 100 %\n",
      "Accuracy of orange dahlia : 100 %\n",
      "Accuracy of tiger lily : 100 %\n",
      "Accuracy of pink-yellow dahlia : 100 %\n",
      "Accuracy of cautleya spicata : 100 %\n",
      "Accuracy of japanese anemone : 66 %\n",
      "Accuracy of black-eyed susan : 100 %\n",
      "Accuracy of silverbush : 100 %\n",
      "Accuracy of californian poppy : 100 %\n",
      "Accuracy of osteospermum : 100 %\n",
      "Accuracy of spring crocus : 100 %\n",
      "Accuracy of bearded iris : 75 %\n",
      "Accuracy of windflower : 80 %\n",
      "Accuracy of moon orchid :  0 %\n",
      "Accuracy of tree poppy : 71 %\n",
      "Accuracy of gazania : 100 %\n",
      "Accuracy of azalea : 62 %\n",
      "Accuracy of water lily : 100 %\n",
      "Accuracy of  rose : 80 %\n",
      "Accuracy of thorn apple : 91 %\n",
      "Accuracy of morning glory : 60 %\n",
      "Accuracy of passion flower : 95 %\n",
      "Accuracy of lotus lotus : 100 %\n",
      "Accuracy of toad lily : 75 %\n",
      "Accuracy of bird of paradise : 80 %\n",
      "Accuracy of anthurium : 41 %\n",
      "Accuracy of frangipani : 94 %\n",
      "Accuracy of clematis : 53 %\n",
      "Accuracy of hibiscus : 84 %\n",
      "Accuracy of columbine : 70 %\n",
      "Accuracy of desert-rose : 80 %\n",
      "Accuracy of tree mallow : 100 %\n",
      "Accuracy of magnolia : 100 %\n",
      "Accuracy of cyclamen : 68 %\n",
      "Accuracy of watercress : 87 %\n",
      "Accuracy of monkshood : 33 %\n",
      "Accuracy of canna lily : 100 %\n",
      "Accuracy of hippeastrum : 66 %\n",
      "Accuracy of bee balm : 50 %\n",
      "Accuracy of ball moss : 66 %\n",
      "Accuracy of foxglove : 85 %\n",
      "Accuracy of bougainvillea : 46 %\n",
      "Accuracy of camellia : 80 %\n",
      "Accuracy of mallow : 71 %\n",
      "Accuracy of mexican petunia : 100 %\n",
      "Accuracy of bromelia : 83 %\n"
     ]
    }
   ],
   "source": [
    "class_correct = list(0. for i in range(102))\n",
    "class_total = list(0. for i in range(102))\n",
    "with torch.no_grad():\n",
    "    for data in dataloaders['test_data']:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs, 1)\n",
    "        c = (predicted == labels).squeeze()\n",
    "        for i in range(len(c)):\n",
    "            label = labels[i]\n",
    "            class_correct[label] += c[i].item()\n",
    "            class_total[label] += 1\n",
    "\n",
    "for i in range(102):\n",
    "    print('Accuracy of %5s : %2d %%' % (\n",
    "        cat_label_to_name[i], 100 * class_correct[i] / class_total[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "name_list = list(cat_label_to_name.values())\n",
    "num_list = [100 * class_correct[i] / class_total[i] for i in range(len(class_total))]\n",
    "plt.bar(name_list, num_list, color='lightgreen')\n",
    "plt.xlabel('flower')\n",
    "plt.ylabel('accuracy(%)')\n",
    "plt.title('accuracy per flower')\n",
    "plt.xticks(size= 'small',rotation=60,fontsize=2)\n",
    "plt.savefig('accuracy per flower.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "apf = {'flower': name_list, 'accuracy': num_list}\n",
    "floweracc = pd.DataFrame(apf)\n",
    "floweracc.to_csv('floweracc.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>flower</th>\n",
       "      <th>accuracy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pink primrose</td>\n",
       "      <td>87.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>globe thistle</td>\n",
       "      <td>75.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>blanket flower</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>trumpet creeper</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>blackberry lily</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>snapdragon</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>colt's foot</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>king protea</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>spear thistle</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>yellow iris</td>\n",
       "      <td>85.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>globe-flower</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>purple coneflower</td>\n",
       "      <td>87.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>peruvian lily</td>\n",
       "      <td>63.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>balloon flower</td>\n",
       "      <td>75.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>hard-leaved pocket orchid</td>\n",
       "      <td>83.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>giant white arum lily</td>\n",
       "      <td>71.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>fire lily</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>pincushion flower</td>\n",
       "      <td>87.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>fritillary</td>\n",
       "      <td>91.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>red ginger</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>grape hyacinth</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>corn poppy</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>prince of wales feathers</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>stemless gentian</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>artichoke</td>\n",
       "      <td>85.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>canterbury bells</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>sweet william</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>carnation</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>garden phlox</td>\n",
       "      <td>66.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>love in the mist</td>\n",
       "      <td>42.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>azalea</td>\n",
       "      <td>62.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>water lily</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>rose</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>thorn apple</td>\n",
       "      <td>91.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>morning glory</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>passion flower</td>\n",
       "      <td>95.238095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>lotus lotus</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>toad lily</td>\n",
       "      <td>75.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>bird of paradise</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>anthurium</td>\n",
       "      <td>41.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>frangipani</td>\n",
       "      <td>94.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>clematis</td>\n",
       "      <td>53.846154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>hibiscus</td>\n",
       "      <td>84.615385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>columbine</td>\n",
       "      <td>70.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>desert-rose</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>tree mallow</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>magnolia</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>cyclamen</td>\n",
       "      <td>68.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>watercress</td>\n",
       "      <td>87.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>monkshood</td>\n",
       "      <td>33.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>canna lily</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>hippeastrum</td>\n",
       "      <td>66.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>bee balm</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>ball moss</td>\n",
       "      <td>66.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>foxglove</td>\n",
       "      <td>85.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>bougainvillea</td>\n",
       "      <td>46.153846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>camellia</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>mallow</td>\n",
       "      <td>71.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>mexican petunia</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>bromelia</td>\n",
       "      <td>83.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>102 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              flower    accuracy\n",
       "0      pink primrose   87.500000\n",
       "1      globe thistle   75.000000\n",
       "2     blanket flower  100.000000\n",
       "3    trumpet creeper   60.000000\n",
       "4    blackberry lily  100.000000\n",
       "..               ...         ...\n",
       "97     bougainvillea   46.153846\n",
       "98          camellia   80.000000\n",
       "99            mallow   71.428571\n",
       "100  mexican petunia  100.000000\n",
       "101         bromelia   83.333333\n",
       "\n",
       "[102 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "floweracc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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