Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ResNet(\n",
       "  (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n",
       "  (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  (act1): ReLU(inplace=True)\n",
       "  (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n",
       "  (layer1): Sequential(\n",
       "    (0): BasicBlock(\n",
       "      (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "    )\n",
       "    (1): BasicBlock(\n",
       "      (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (layer2): Sequential(\n",
       "    (0): BasicBlock(\n",
       "      (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "        (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      )\n",
       "    )\n",
       "    (1): BasicBlock(\n",
       "      (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (layer3): Sequential(\n",
       "    (0): BasicBlock(\n",
       "      (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "        (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      )\n",
       "    )\n",
       "    (1): BasicBlock(\n",
       "      (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (layer4): Sequential(\n",
       "    (0): BasicBlock(\n",
       "      (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "        (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      )\n",
       "    )\n",
       "    (1): BasicBlock(\n",
       "      (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act1): ReLU(inplace=True)\n",
       "      (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (act2): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (global_pool): SelectAdaptivePool2d (pool_type=avg, flatten=Flatten(start_dim=1, end_dim=-1))\n",
       "  (fc): Linear(in_features=512, out_features=1000, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import timm\n",
    "model = timm.create_model('resnet18', pretrained=True)\n",
    "model.eval()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib\n",
    "from PIL import Image\n",
    "from timm.data import resolve_data_config\n",
    "from timm.data.transforms_factory import create_transform\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "config = resolve_data_config({}, model=model)\n",
    "#transform = create_transform(**config)\n",
    "transform = transforms.Compose([\n",
    "    transforms.Resize((224, 224)),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize(mean=[0.485, 0.456, 0.406],\n",
    "                       std=[0.229, 0.224, 0.225])])\n",
    "url, filename = (\"https://github.com/pytorch/hub/raw/master/images/dog.jpg\", \"dog.jpg\")\n",
    "urllib.request.urlretrieve(url, filename)\n",
    "img = Image.open(\"n01440764_ILSVRC2012_val_00048969.png\").convert('RGB')\n",
    "tensor = transform(img).unsqueeze(0) # transform and add batch dimension\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1000])\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "with torch.no_grad():\n",
    "    out = model(tensor)\n",
    "probabilities = torch.nn.functional.softmax(out[0], dim=0)\n",
    "print(probabilities.shape)\n",
    "# prints: torch.Size([1000])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tench 0.999580442905426\n",
      "barracouta 0.00040617931517772377\n",
      "coho 8.993477422336582e-06\n",
      "sturgeon 1.4182005543261766e-06\n",
      "gar 9.00422605809581e-07\n"
     ]
    }
   ],
   "source": [
    "# Get imagenet class mappings\n",
    "url, filename = (\"https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt\", \"imagenet_classes.txt\")\n",
    "urllib.request.urlretrieve(url, filename) \n",
    "with open(\"imagenet_classes.txt\", \"r\") as f:\n",
    "    categories = [s.strip() for s in f.readlines()]\n",
    "\n",
    "# Print top categories per image\n",
    "top5_prob, top5_catid = torch.topk(probabilities, 5)\n",
    "for i in range(top5_prob.size(0)):\n",
    "    print(categories[top5_catid[i]], top5_prob[i].item())\n",
    "# prints class names and probabilities like:\n",
    "# [('Samoyed', 0.6425196528434753), ('Pomeranian', 0.04062102362513542), ('keeshond', 0.03186424449086189), ('white wolf', 0.01739676296710968), ('Eskimo dog', 0.011717947199940681)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['tench',\n",
       " 'goldfish',\n",
       " 'great white shark',\n",
       " 'tiger shark',\n",
       " 'hammerhead',\n",
       " 'electric ray',\n",
       " 'stingray',\n",
       " 'cock',\n",
       " 'hen',\n",
       " 'ostrich',\n",
       " 'brambling',\n",
       " 'goldfinch',\n",
       " 'house finch',\n",
       " 'junco',\n",
       " 'indigo bunting',\n",
       " 'robin',\n",
       " 'bulbul',\n",
       " 'jay',\n",
       " 'magpie',\n",
       " 'chickadee',\n",
       " 'water ouzel',\n",
       " 'kite',\n",
       " 'bald eagle',\n",
       " 'vulture',\n",
       " 'great grey owl',\n",
       " 'European fire salamander',\n",
       " 'common newt',\n",
       " 'eft',\n",
       " 'spotted salamander',\n",
       " 'axolotl',\n",
       " 'bullfrog',\n",
       " 'tree frog',\n",
       " 'tailed frog',\n",
       " 'loggerhead',\n",
       " 'leatherback turtle',\n",
       " 'mud turtle',\n",
       " 'terrapin',\n",
       " 'box turtle',\n",
       " 'banded gecko',\n",
       " 'common iguana',\n",
       " 'American chameleon',\n",
       " 'whiptail',\n",
       " 'agama',\n",
       " 'frilled lizard',\n",
       " 'alligator lizard',\n",
       " 'Gila monster',\n",
       " 'green lizard',\n",
       " 'African chameleon',\n",
       " 'Komodo dragon',\n",
       " 'African crocodile',\n",
       " 'American alligator',\n",
       " 'triceratops',\n",
       " 'thunder snake',\n",
       " 'ringneck snake',\n",
       " 'hognose snake',\n",
       " 'green snake',\n",
       " 'king snake',\n",
       " 'garter snake',\n",
       " 'water snake',\n",
       " 'vine snake',\n",
       " 'night snake',\n",
       " 'boa constrictor',\n",
       " 'rock python',\n",
       " 'Indian cobra',\n",
       " 'green mamba',\n",
       " 'sea snake',\n",
       " 'horned viper',\n",
       " 'diamondback',\n",
       " 'sidewinder',\n",
       " 'trilobite',\n",
       " 'harvestman',\n",
       " 'scorpion',\n",
       " 'black and gold garden spider',\n",
       " 'barn spider',\n",
       " 'garden spider',\n",
       " 'black widow',\n",
       " 'tarantula',\n",
       " 'wolf spider',\n",
       " 'tick',\n",
       " 'centipede',\n",
       " 'black grouse',\n",
       " 'ptarmigan',\n",
       " 'ruffed grouse',\n",
       " 'prairie chicken',\n",
       " 'peacock',\n",
       " 'quail',\n",
       " 'partridge',\n",
       " 'African grey',\n",
       " 'macaw',\n",
       " 'sulphur-crested cockatoo',\n",
       " 'lorikeet',\n",
       " 'coucal',\n",
       " 'bee eater',\n",
       " 'hornbill',\n",
       " 'hummingbird',\n",
       " 'jacamar',\n",
       " 'toucan',\n",
       " 'drake',\n",
       " 'red-breasted merganser',\n",
       " 'goose',\n",
       " 'black swan',\n",
       " 'tusker',\n",
       " 'echidna',\n",
       " 'platypus',\n",
       " 'wallaby',\n",
       " 'koala',\n",
       " 'wombat',\n",
       " 'jellyfish',\n",
       " 'sea anemone',\n",
       " 'brain coral',\n",
       " 'flatworm',\n",
       " 'nematode',\n",
       " 'conch',\n",
       " 'snail',\n",
       " 'slug',\n",
       " 'sea slug',\n",
       " 'chiton',\n",
       " 'chambered nautilus',\n",
       " 'Dungeness crab',\n",
       " 'rock crab',\n",
       " 'fiddler crab',\n",
       " 'king crab',\n",
       " 'American lobster',\n",
       " 'spiny lobster',\n",
       " 'crayfish',\n",
       " 'hermit crab',\n",
       " 'isopod',\n",
       " 'white stork',\n",
       " 'black stork',\n",
       " 'spoonbill',\n",
       " 'flamingo',\n",
       " 'little blue heron',\n",
       " 'American egret',\n",
       " 'bittern',\n",
       " 'crane',\n",
       " 'limpkin',\n",
       " 'European gallinule',\n",
       " 'American coot',\n",
       " 'bustard',\n",
       " 'ruddy turnstone',\n",
       " 'red-backed sandpiper',\n",
       " 'redshank',\n",
       " 'dowitcher',\n",
       " 'oystercatcher',\n",
       " 'pelican',\n",
       " 'king penguin',\n",
       " 'albatross',\n",
       " 'grey whale',\n",
       " 'killer whale',\n",
       " 'dugong',\n",
       " 'sea lion',\n",
       " 'Chihuahua',\n",
       " 'Japanese spaniel',\n",
       " 'Maltese dog',\n",
       " 'Pekinese',\n",
       " 'Shih-Tzu',\n",
       " 'Blenheim spaniel',\n",
       " 'papillon',\n",
       " 'toy terrier',\n",
       " 'Rhodesian ridgeback',\n",
       " 'Afghan hound',\n",
       " 'basset',\n",
       " 'beagle',\n",
       " 'bloodhound',\n",
       " 'bluetick',\n",
       " 'black-and-tan coonhound',\n",
       " 'Walker hound',\n",
       " 'English foxhound',\n",
       " 'redbone',\n",
       " 'borzoi',\n",
       " 'Irish wolfhound',\n",
       " 'Italian greyhound',\n",
       " 'whippet',\n",
       " 'Ibizan hound',\n",
       " 'Norwegian elkhound',\n",
       " 'otterhound',\n",
       " 'Saluki',\n",
       " 'Scottish deerhound',\n",
       " 'Weimaraner',\n",
       " 'Staffordshire bullterrier',\n",
       " 'American Staffordshire terrier',\n",
       " 'Bedlington terrier',\n",
       " 'Border terrier',\n",
       " 'Kerry blue terrier',\n",
       " 'Irish terrier',\n",
       " 'Norfolk terrier',\n",
       " 'Norwich terrier',\n",
       " 'Yorkshire terrier',\n",
       " 'wire-haired fox terrier',\n",
       " 'Lakeland terrier',\n",
       " 'Sealyham terrier',\n",
       " 'Airedale',\n",
       " 'cairn',\n",
       " 'Australian terrier',\n",
       " 'Dandie Dinmont',\n",
       " 'Boston bull',\n",
       " 'miniature schnauzer',\n",
       " 'giant schnauzer',\n",
       " 'standard schnauzer',\n",
       " 'Scotch terrier',\n",
       " 'Tibetan terrier',\n",
       " 'silky terrier',\n",
       " 'soft-coated wheaten terrier',\n",
       " 'West Highland white terrier',\n",
       " 'Lhasa',\n",
       " 'flat-coated retriever',\n",
       " 'curly-coated retriever',\n",
       " 'golden retriever',\n",
       " 'Labrador retriever',\n",
       " 'Chesapeake Bay retriever',\n",
       " 'German short-haired pointer',\n",
       " 'vizsla',\n",
       " 'English setter',\n",
       " 'Irish setter',\n",
       " 'Gordon setter',\n",
       " 'Brittany spaniel',\n",
       " 'clumber',\n",
       " 'English springer',\n",
       " 'Welsh springer spaniel',\n",
       " 'cocker spaniel',\n",
       " 'Sussex spaniel',\n",
       " 'Irish water spaniel',\n",
       " 'kuvasz',\n",
       " 'schipperke',\n",
       " 'groenendael',\n",
       " 'malinois',\n",
       " 'briard',\n",
       " 'kelpie',\n",
       " 'komondor',\n",
       " 'Old English sheepdog',\n",
       " 'Shetland sheepdog',\n",
       " 'collie',\n",
       " 'Border collie',\n",
       " 'Bouvier des Flandres',\n",
       " 'Rottweiler',\n",
       " 'German shepherd',\n",
       " 'Doberman',\n",
       " 'miniature pinscher',\n",
       " 'Greater Swiss Mountain dog',\n",
       " 'Bernese mountain dog',\n",
       " 'Appenzeller',\n",
       " 'EntleBucher',\n",
       " 'boxer',\n",
       " 'bull mastiff',\n",
       " 'Tibetan mastiff',\n",
       " 'French bulldog',\n",
       " 'Great Dane',\n",
       " 'Saint Bernard',\n",
       " 'Eskimo dog',\n",
       " 'malamute',\n",
       " 'Siberian husky',\n",
       " 'dalmatian',\n",
       " 'affenpinscher',\n",
       " 'basenji',\n",
       " 'pug',\n",
       " 'Leonberg',\n",
       " 'Newfoundland',\n",
       " 'Great Pyrenees',\n",
       " 'Samoyed',\n",
       " 'Pomeranian',\n",
       " 'chow',\n",
       " 'keeshond',\n",
       " 'Brabancon griffon',\n",
       " 'Pembroke',\n",
       " 'Cardigan',\n",
       " 'toy poodle',\n",
       " 'miniature poodle',\n",
       " 'standard poodle',\n",
       " 'Mexican hairless',\n",
       " 'timber wolf',\n",
       " 'white wolf',\n",
       " 'red wolf',\n",
       " 'coyote',\n",
       " 'dingo',\n",
       " 'dhole',\n",
       " 'African hunting dog',\n",
       " 'hyena',\n",
       " 'red fox',\n",
       " 'kit fox',\n",
       " 'Arctic fox',\n",
       " 'grey fox',\n",
       " 'tabby',\n",
       " 'tiger cat',\n",
       " 'Persian cat',\n",
       " 'Siamese cat',\n",
       " 'Egyptian cat',\n",
       " 'cougar',\n",
       " 'lynx',\n",
       " 'leopard',\n",
       " 'snow leopard',\n",
       " 'jaguar',\n",
       " 'lion',\n",
       " 'tiger',\n",
       " 'cheetah',\n",
       " 'brown bear',\n",
       " 'American black bear',\n",
       " 'ice bear',\n",
       " 'sloth bear',\n",
       " 'mongoose',\n",
       " 'meerkat',\n",
       " 'tiger beetle',\n",
       " 'ladybug',\n",
       " 'ground beetle',\n",
       " 'long-horned beetle',\n",
       " 'leaf beetle',\n",
       " 'dung beetle',\n",
       " 'rhinoceros beetle',\n",
       " 'weevil',\n",
       " 'fly',\n",
       " 'bee',\n",
       " 'ant',\n",
       " 'grasshopper',\n",
       " 'cricket',\n",
       " 'walking stick',\n",
       " 'cockroach',\n",
       " 'mantis',\n",
       " 'cicada',\n",
       " 'leafhopper',\n",
       " 'lacewing',\n",
       " 'dragonfly',\n",
       " 'damselfly',\n",
       " 'admiral',\n",
       " 'ringlet',\n",
       " 'monarch',\n",
       " 'cabbage butterfly',\n",
       " 'sulphur butterfly',\n",
       " 'lycaenid',\n",
       " 'starfish',\n",
       " 'sea urchin',\n",
       " 'sea cucumber',\n",
       " 'wood rabbit',\n",
       " 'hare',\n",
       " 'Angora',\n",
       " 'hamster',\n",
       " 'porcupine',\n",
       " 'fox squirrel',\n",
       " 'marmot',\n",
       " 'beaver',\n",
       " 'guinea pig',\n",
       " 'sorrel',\n",
       " 'zebra',\n",
       " 'hog',\n",
       " 'wild boar',\n",
       " 'warthog',\n",
       " 'hippopotamus',\n",
       " 'ox',\n",
       " 'water buffalo',\n",
       " 'bison',\n",
       " 'ram',\n",
       " 'bighorn',\n",
       " 'ibex',\n",
       " 'hartebeest',\n",
       " 'impala',\n",
       " 'gazelle',\n",
       " 'Arabian camel',\n",
       " 'llama',\n",
       " 'weasel',\n",
       " 'mink',\n",
       " 'polecat',\n",
       " 'black-footed ferret',\n",
       " 'otter',\n",
       " 'skunk',\n",
       " 'badger',\n",
       " 'armadillo',\n",
       " 'three-toed sloth',\n",
       " 'orangutan',\n",
       " 'gorilla',\n",
       " 'chimpanzee',\n",
       " 'gibbon',\n",
       " 'siamang',\n",
       " 'guenon',\n",
       " 'patas',\n",
       " 'baboon',\n",
       " 'macaque',\n",
       " 'langur',\n",
       " 'colobus',\n",
       " 'proboscis monkey',\n",
       " 'marmoset',\n",
       " 'capuchin',\n",
       " 'howler monkey',\n",
       " 'titi',\n",
       " 'spider monkey',\n",
       " 'squirrel monkey',\n",
       " 'Madagascar cat',\n",
       " 'indri',\n",
       " 'Indian elephant',\n",
       " 'African elephant',\n",
       " 'lesser panda',\n",
       " 'giant panda',\n",
       " 'barracouta',\n",
       " 'eel',\n",
       " 'coho',\n",
       " 'rock beauty',\n",
       " 'anemone fish',\n",
       " 'sturgeon',\n",
       " 'gar',\n",
       " 'lionfish',\n",
       " 'puffer',\n",
       " 'abacus',\n",
       " 'abaya',\n",
       " 'academic gown',\n",
       " 'accordion',\n",
       " 'acoustic guitar',\n",
       " 'aircraft carrier',\n",
       " 'airliner',\n",
       " 'airship',\n",
       " 'altar',\n",
       " 'ambulance',\n",
       " 'amphibian',\n",
       " 'analog clock',\n",
       " 'apiary',\n",
       " 'apron',\n",
       " 'ashcan',\n",
       " 'assault rifle',\n",
       " 'backpack',\n",
       " 'bakery',\n",
       " 'balance beam',\n",
       " 'balloon',\n",
       " 'ballpoint',\n",
       " 'Band Aid',\n",
       " 'banjo',\n",
       " 'bannister',\n",
       " 'barbell',\n",
       " 'barber chair',\n",
       " 'barbershop',\n",
       " 'barn',\n",
       " 'barometer',\n",
       " 'barrel',\n",
       " 'barrow',\n",
       " 'baseball',\n",
       " 'basketball',\n",
       " 'bassinet',\n",
       " 'bassoon',\n",
       " 'bathing cap',\n",
       " 'bath towel',\n",
       " 'bathtub',\n",
       " 'beach wagon',\n",
       " 'beacon',\n",
       " 'beaker',\n",
       " 'bearskin',\n",
       " 'beer bottle',\n",
       " 'beer glass',\n",
       " 'bell cote',\n",
       " 'bib',\n",
       " 'bicycle-built-for-two',\n",
       " 'bikini',\n",
       " 'binder',\n",
       " 'binoculars',\n",
       " 'birdhouse',\n",
       " 'boathouse',\n",
       " 'bobsled',\n",
       " 'bolo tie',\n",
       " 'bonnet',\n",
       " 'bookcase',\n",
       " 'bookshop',\n",
       " 'bottlecap',\n",
       " 'bow',\n",
       " 'bow tie',\n",
       " 'brass',\n",
       " 'brassiere',\n",
       " 'breakwater',\n",
       " 'breastplate',\n",
       " 'broom',\n",
       " 'bucket',\n",
       " 'buckle',\n",
       " 'bulletproof vest',\n",
       " 'bullet train',\n",
       " 'butcher shop',\n",
       " 'cab',\n",
       " 'caldron',\n",
       " 'candle',\n",
       " 'cannon',\n",
       " 'canoe',\n",
       " 'can opener',\n",
       " 'cardigan',\n",
       " 'car mirror',\n",
       " 'carousel',\n",
       " \"carpenter's kit\",\n",
       " 'carton',\n",
       " 'car wheel',\n",
       " 'cash machine',\n",
       " 'cassette',\n",
       " 'cassette player',\n",
       " 'castle',\n",
       " 'catamaran',\n",
       " 'CD player',\n",
       " 'cello',\n",
       " 'cellular telephone',\n",
       " 'chain',\n",
       " 'chainlink fence',\n",
       " 'chain mail',\n",
       " 'chain saw',\n",
       " 'chest',\n",
       " 'chiffonier',\n",
       " 'chime',\n",
       " 'china cabinet',\n",
       " 'Christmas stocking',\n",
       " 'church',\n",
       " 'cinema',\n",
       " 'cleaver',\n",
       " 'cliff dwelling',\n",
       " 'cloak',\n",
       " 'clog',\n",
       " 'cocktail shaker',\n",
       " 'coffee mug',\n",
       " 'coffeepot',\n",
       " 'coil',\n",
       " 'combination lock',\n",
       " 'computer keyboard',\n",
       " 'confectionery',\n",
       " 'container ship',\n",
       " 'convertible',\n",
       " 'corkscrew',\n",
       " 'cornet',\n",
       " 'cowboy boot',\n",
       " 'cowboy hat',\n",
       " 'cradle',\n",
       " 'crane',\n",
       " 'crash helmet',\n",
       " 'crate',\n",
       " 'crib',\n",
       " 'Crock Pot',\n",
       " 'croquet ball',\n",
       " 'crutch',\n",
       " 'cuirass',\n",
       " 'dam',\n",
       " 'desk',\n",
       " 'desktop computer',\n",
       " 'dial telephone',\n",
       " 'diaper',\n",
       " 'digital clock',\n",
       " 'digital watch',\n",
       " 'dining table',\n",
       " 'dishrag',\n",
       " 'dishwasher',\n",
       " 'disk brake',\n",
       " 'dock',\n",
       " 'dogsled',\n",
       " 'dome',\n",
       " 'doormat',\n",
       " 'drilling platform',\n",
       " 'drum',\n",
       " 'drumstick',\n",
       " 'dumbbell',\n",
       " 'Dutch oven',\n",
       " 'electric fan',\n",
       " 'electric guitar',\n",
       " 'electric locomotive',\n",
       " 'entertainment center',\n",
       " 'envelope',\n",
       " 'espresso maker',\n",
       " 'face powder',\n",
       " 'feather boa',\n",
       " 'file',\n",
       " 'fireboat',\n",
       " 'fire engine',\n",
       " 'fire screen',\n",
       " 'flagpole',\n",
       " 'flute',\n",
       " 'folding chair',\n",
       " 'football helmet',\n",
       " 'forklift',\n",
       " 'fountain',\n",
       " 'fountain pen',\n",
       " 'four-poster',\n",
       " 'freight car',\n",
       " 'French horn',\n",
       " 'frying pan',\n",
       " 'fur coat',\n",
       " 'garbage truck',\n",
       " 'gasmask',\n",
       " 'gas pump',\n",
       " 'goblet',\n",
       " 'go-kart',\n",
       " 'golf ball',\n",
       " 'golfcart',\n",
       " 'gondola',\n",
       " 'gong',\n",
       " 'gown',\n",
       " 'grand piano',\n",
       " 'greenhouse',\n",
       " 'grille',\n",
       " 'grocery store',\n",
       " 'guillotine',\n",
       " 'hair slide',\n",
       " 'hair spray',\n",
       " 'half track',\n",
       " 'hammer',\n",
       " 'hamper',\n",
       " 'hand blower',\n",
       " 'hand-held computer',\n",
       " 'handkerchief',\n",
       " 'hard disc',\n",
       " 'harmonica',\n",
       " 'harp',\n",
       " 'harvester',\n",
       " 'hatchet',\n",
       " 'holster',\n",
       " 'home theater',\n",
       " 'honeycomb',\n",
       " 'hook',\n",
       " 'hoopskirt',\n",
       " 'horizontal bar',\n",
       " 'horse cart',\n",
       " 'hourglass',\n",
       " 'iPod',\n",
       " 'iron',\n",
       " \"jack-o'-lantern\",\n",
       " 'jean',\n",
       " 'jeep',\n",
       " 'jersey',\n",
       " 'jigsaw puzzle',\n",
       " 'jinrikisha',\n",
       " 'joystick',\n",
       " 'kimono',\n",
       " 'knee pad',\n",
       " 'knot',\n",
       " 'lab coat',\n",
       " 'ladle',\n",
       " 'lampshade',\n",
       " 'laptop',\n",
       " 'lawn mower',\n",
       " 'lens cap',\n",
       " 'letter opener',\n",
       " 'library',\n",
       " 'lifeboat',\n",
       " 'lighter',\n",
       " 'limousine',\n",
       " 'liner',\n",
       " 'lipstick',\n",
       " 'Loafer',\n",
       " 'lotion',\n",
       " 'loudspeaker',\n",
       " 'loupe',\n",
       " 'lumbermill',\n",
       " 'magnetic compass',\n",
       " 'mailbag',\n",
       " 'mailbox',\n",
       " 'maillot',\n",
       " 'maillot',\n",
       " 'manhole cover',\n",
       " 'maraca',\n",
       " 'marimba',\n",
       " 'mask',\n",
       " 'matchstick',\n",
       " 'maypole',\n",
       " 'maze',\n",
       " 'measuring cup',\n",
       " 'medicine chest',\n",
       " 'megalith',\n",
       " 'microphone',\n",
       " 'microwave',\n",
       " 'military uniform',\n",
       " 'milk can',\n",
       " 'minibus',\n",
       " 'miniskirt',\n",
       " 'minivan',\n",
       " 'missile',\n",
       " 'mitten',\n",
       " 'mixing bowl',\n",
       " 'mobile home',\n",
       " 'Model T',\n",
       " 'modem',\n",
       " 'monastery',\n",
       " 'monitor',\n",
       " 'moped',\n",
       " 'mortar',\n",
       " 'mortarboard',\n",
       " 'mosque',\n",
       " 'mosquito net',\n",
       " 'motor scooter',\n",
       " 'mountain bike',\n",
       " 'mountain tent',\n",
       " 'mouse',\n",
       " 'mousetrap',\n",
       " 'moving van',\n",
       " 'muzzle',\n",
       " 'nail',\n",
       " 'neck brace',\n",
       " 'necklace',\n",
       " 'nipple',\n",
       " 'notebook',\n",
       " 'obelisk',\n",
       " 'oboe',\n",
       " 'ocarina',\n",
       " 'odometer',\n",
       " 'oil filter',\n",
       " 'organ',\n",
       " 'oscilloscope',\n",
       " 'overskirt',\n",
       " 'oxcart',\n",
       " 'oxygen mask',\n",
       " 'packet',\n",
       " 'paddle',\n",
       " 'paddlewheel',\n",
       " 'padlock',\n",
       " 'paintbrush',\n",
       " 'pajama',\n",
       " 'palace',\n",
       " 'panpipe',\n",
       " 'paper towel',\n",
       " 'parachute',\n",
       " 'parallel bars',\n",
       " 'park bench',\n",
       " 'parking meter',\n",
       " 'passenger car',\n",
       " 'patio',\n",
       " 'pay-phone',\n",
       " 'pedestal',\n",
       " 'pencil box',\n",
       " 'pencil sharpener',\n",
       " 'perfume',\n",
       " 'Petri dish',\n",
       " 'photocopier',\n",
       " 'pick',\n",
       " 'pickelhaube',\n",
       " 'picket fence',\n",
       " 'pickup',\n",
       " 'pier',\n",
       " 'piggy bank',\n",
       " 'pill bottle',\n",
       " 'pillow',\n",
       " 'ping-pong ball',\n",
       " 'pinwheel',\n",
       " 'pirate',\n",
       " 'pitcher',\n",
       " 'plane',\n",
       " 'planetarium',\n",
       " 'plastic bag',\n",
       " 'plate rack',\n",
       " 'plow',\n",
       " 'plunger',\n",
       " 'Polaroid camera',\n",
       " 'pole',\n",
       " 'police van',\n",
       " 'poncho',\n",
       " 'pool table',\n",
       " 'pop bottle',\n",
       " 'pot',\n",
       " \"potter's wheel\",\n",
       " 'power drill',\n",
       " 'prayer rug',\n",
       " 'printer',\n",
       " 'prison',\n",
       " 'projectile',\n",
       " 'projector',\n",
       " 'puck',\n",
       " 'punching bag',\n",
       " 'purse',\n",
       " 'quill',\n",
       " 'quilt',\n",
       " 'racer',\n",
       " 'racket',\n",
       " 'radiator',\n",
       " 'radio',\n",
       " 'radio telescope',\n",
       " 'rain barrel',\n",
       " 'recreational vehicle',\n",
       " 'reel',\n",
       " 'reflex camera',\n",
       " 'refrigerator',\n",
       " 'remote control',\n",
       " 'restaurant',\n",
       " 'revolver',\n",
       " 'rifle',\n",
       " 'rocking chair',\n",
       " 'rotisserie',\n",
       " 'rubber eraser',\n",
       " 'rugby ball',\n",
       " 'rule',\n",
       " 'running shoe',\n",
       " 'safe',\n",
       " 'safety pin',\n",
       " 'saltshaker',\n",
       " 'sandal',\n",
       " 'sarong',\n",
       " 'sax',\n",
       " 'scabbard',\n",
       " 'scale',\n",
       " 'school bus',\n",
       " 'schooner',\n",
       " 'scoreboard',\n",
       " 'screen',\n",
       " 'screw',\n",
       " 'screwdriver',\n",
       " 'seat belt',\n",
       " 'sewing machine',\n",
       " 'shield',\n",
       " 'shoe shop',\n",
       " 'shoji',\n",
       " 'shopping basket',\n",
       " 'shopping cart',\n",
       " 'shovel',\n",
       " 'shower cap',\n",
       " 'shower curtain',\n",
       " 'ski',\n",
       " 'ski mask',\n",
       " 'sleeping bag',\n",
       " 'slide rule',\n",
       " 'sliding door',\n",
       " 'slot',\n",
       " 'snorkel',\n",
       " 'snowmobile',\n",
       " 'snowplow',\n",
       " 'soap dispenser',\n",
       " 'soccer ball',\n",
       " 'sock',\n",
       " 'solar dish',\n",
       " 'sombrero',\n",
       " 'soup bowl',\n",
       " 'space bar',\n",
       " 'space heater',\n",
       " 'space shuttle',\n",
       " 'spatula',\n",
       " 'speedboat',\n",
       " 'spider web',\n",
       " 'spindle',\n",
       " 'sports car',\n",
       " 'spotlight',\n",
       " 'stage',\n",
       " 'steam locomotive',\n",
       " 'steel arch bridge',\n",
       " 'steel drum',\n",
       " 'stethoscope',\n",
       " 'stole',\n",
       " 'stone wall',\n",
       " 'stopwatch',\n",
       " 'stove',\n",
       " 'strainer',\n",
       " 'streetcar',\n",
       " 'stretcher',\n",
       " 'studio couch',\n",
       " 'stupa',\n",
       " 'submarine',\n",
       " 'suit',\n",
       " 'sundial',\n",
       " 'sunglass',\n",
       " 'sunglasses',\n",
       " 'sunscreen',\n",
       " 'suspension bridge',\n",
       " 'swab',\n",
       " 'sweatshirt',\n",
       " 'swimming trunks',\n",
       " 'swing',\n",
       " 'switch',\n",
       " 'syringe',\n",
       " 'table lamp',\n",
       " 'tank',\n",
       " 'tape player',\n",
       " 'teapot',\n",
       " 'teddy',\n",
       " 'television',\n",
       " 'tennis ball',\n",
       " 'thatch',\n",
       " 'theater curtain',\n",
       " 'thimble',\n",
       " 'thresher',\n",
       " 'throne',\n",
       " 'tile roof',\n",
       " 'toaster',\n",
       " 'tobacco shop',\n",
       " 'toilet seat',\n",
       " 'torch',\n",
       " 'totem pole',\n",
       " 'tow truck',\n",
       " 'toyshop',\n",
       " 'tractor',\n",
       " 'trailer truck',\n",
       " 'tray',\n",
       " 'trench coat',\n",
       " 'tricycle',\n",
       " 'trimaran',\n",
       " 'tripod',\n",
       " 'triumphal arch',\n",
       " 'trolleybus',\n",
       " 'trombone',\n",
       " 'tub',\n",
       " 'turnstile',\n",
       " 'typewriter keyboard',\n",
       " 'umbrella',\n",
       " 'unicycle',\n",
       " 'upright',\n",
       " 'vacuum',\n",
       " 'vase',\n",
       " 'vault',\n",
       " 'velvet',\n",
       " 'vending machine',\n",
       " 'vestment',\n",
       " 'viaduct',\n",
       " 'violin',\n",
       " 'volleyball',\n",
       " 'waffle iron',\n",
       " 'wall clock',\n",
       " 'wallet',\n",
       " 'wardrobe',\n",
       " 'warplane',\n",
       " 'washbasin',\n",
       " 'washer',\n",
       " 'water bottle',\n",
       " 'water jug',\n",
       " 'water tower',\n",
       " 'whiskey jug',\n",
       " 'whistle',\n",
       " 'wig',\n",
       " 'window screen',\n",
       " 'window shade',\n",
       " 'Windsor tie',\n",
       " 'wine bottle',\n",
       " 'wing',\n",
       " 'wok',\n",
       " 'wooden spoon',\n",
       " 'wool',\n",
       " 'worm fence',\n",
       " 'wreck',\n",
       " 'yawl',\n",
       " 'yurt',\n",
       " 'web site',\n",
       " 'comic book',\n",
       " 'crossword puzzle',\n",
       " 'street sign',\n",
       " 'traffic light',\n",
       " 'book jacket',\n",
       " 'menu',\n",
       " 'plate',\n",
       " 'guacamole',\n",
       " 'consomme',\n",
       " 'hot pot',\n",
       " 'trifle',\n",
       " 'ice cream',\n",
       " 'ice lolly',\n",
       " 'French loaf',\n",
       " 'bagel',\n",
       " 'pretzel',\n",
       " 'cheeseburger',\n",
       " 'hotdog',\n",
       " 'mashed potato',\n",
       " 'head cabbage',\n",
       " 'broccoli',\n",
       " 'cauliflower',\n",
       " 'zucchini',\n",
       " 'spaghetti squash',\n",
       " 'acorn squash',\n",
       " 'butternut squash',\n",
       " 'cucumber',\n",
       " 'artichoke',\n",
       " 'bell pepper',\n",
       " 'cardoon',\n",
       " 'mushroom',\n",
       " 'Granny Smith',\n",
       " 'strawberry',\n",
       " 'orange',\n",
       " 'lemon',\n",
       " 'fig',\n",
       " 'pineapple',\n",
       " 'banana',\n",
       " 'jackfruit',\n",
       " 'custard apple',\n",
       " 'pomegranate',\n",
       " 'hay',\n",
       " 'carbonara',\n",
       " 'chocolate sauce',\n",
       " 'dough',\n",
       " 'meat loaf',\n",
       " 'pizza',\n",
       " 'potpie',\n",
       " 'burrito',\n",
       " 'red wine',\n",
       " 'espresso',\n",
       " 'cup',\n",
       " 'eggnog',\n",
       " 'alp',\n",
       " 'bubble',\n",
       " 'cliff',\n",
       " 'coral reef',\n",
       " 'geyser',\n",
       " 'lakeside',\n",
       " 'promontory',\n",
       " 'sandbar',\n",
       " 'seashore',\n",
       " 'valley',\n",
       " 'volcano',\n",
       " 'ballplayer',\n",
       " 'groom',\n",
       " 'scuba diver',\n",
       " 'rapeseed',\n",
       " 'daisy',\n",
       " \"yellow lady's slipper\",\n",
       " 'corn',\n",
       " 'acorn',\n",
       " 'hip',\n",
       " 'buckeye',\n",
       " 'coral fungus',\n",
       " 'agaric',\n",
       " 'gyromitra',\n",
       " 'stinkhorn',\n",
       " 'earthstar',\n",
       " 'hen-of-the-woods',\n",
       " 'bolete',\n",
       " 'ear',\n",
       " 'toilet tissue']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([  0, 389, 391, 395, 394])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top5_catid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'input_size': (3, 224, 224),\n",
       " 'interpolation': 'bilinear',\n",
       " 'mean': (0.485, 0.456, 0.406),\n",
       " 'std': (0.229, 0.224, 0.225),\n",
       " 'crop_pct': 0.875}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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