DeepLearning_Materials/6_VisualizationCNN_Pytorch/CNNVisualisation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "nBSztV_ob01R"
   },
   "source": [
    "# Visualization of CNN Layers and Filters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "m81kFpzKZjAP"
   },
   "source": [
    "## Outline\n",
    "1. Using torchvision.datasets with a custom folder of images\n",
    "2. Occlusion analysis with pretrained model\n",
    "3. Filter visualisation with pretrained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1x6DI_8rIWdS"
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "BFT5lgx3b-Fs"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import torch \n",
    "import torch.nn as nn\n",
    "import torchvision\n",
    "#import datasets in torchvision\n",
    "import torchvision.datasets as datasets\n",
    "\n",
    "#import model zoo in torchvision\n",
    "import torchvision.models as models\n",
    "import torchvision.transforms as transforms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "hcLEEvrClfJc"
   },
   "source": [
    "## Load dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "uNeEwOLchv7v"
   },
   "outputs": [],
   "source": [
    "#reading the labels of data we uploaded\n",
    "with open(\"data/imagenet_labels.txt\") as f:\n",
    "    classes = eval(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 54
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 12039,
     "status": "ok",
     "timestamp": 1558629542735,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "xq9tKb9oCmJE",
    "outputId": "33a782a7-4f5d-4b1c-86e6-94d540497f35"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'tench, Tinca tinca', 1: 'goldfish, Carassius auratus', 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', 3: 'tiger shark, Galeocerdo cuvieri', 4: 'hammerhead, hammerhead shark', 5: 'electric ray, crampfish, numbfish, torpedo', 6: 'stingray', 7: 'cock', 8: 'hen', 9: 'ostrich, Struthio camelus', 10: 'brambling, Fringilla montifringilla', 11: 'goldfinch, Carduelis carduelis', 12: 'house finch, linnet, Carpodacus mexicanus', 13: 'junco, snowbird', 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea', 15: 'robin, American robin, Turdus migratorius', 16: 'bulbul', 17: 'jay', 18: 'magpie', 19: 'chickadee', 20: 'water ouzel, dipper', 21: 'kite', 22: 'bald eagle, American eagle, Haliaeetus leucocephalus', 23: 'vulture', 24: 'great grey owl, great gray owl, Strix nebulosa', 25: 'European fire salamander, Salamandra salamandra', 26: 'common newt, Triturus vulgaris', 27: 'eft', 28: 'spotted salamander, Ambystoma maculatum', 29: 'axolotl, mud puppy, Ambystoma mexicanum', 30: 'bullfrog, Rana catesbeiana', 31: 'tree frog, tree-frog', 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui', 33: 'loggerhead, loggerhead turtle, Caretta caretta', 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea', 35: 'mud turtle', 36: 'terrapin', 37: 'box turtle, box tortoise', 38: 'banded gecko', 39: 'common iguana, iguana, Iguana iguana', 40: 'American chameleon, anole, Anolis carolinensis', 41: 'whiptail, whiptail lizard', 42: 'agama', 43: 'frilled lizard, Chlamydosaurus kingi', 44: 'alligator lizard', 45: 'Gila monster, Heloderma suspectum', 46: 'green lizard, Lacerta viridis', 47: 'African chameleon, Chamaeleo chamaeleon', 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis', 49: 'African crocodile, Nile crocodile, Crocodylus niloticus', 50: 'American alligator, Alligator mississipiensis', 51: 'triceratops', 52: 'thunder snake, worm snake, Carphophis amoenus', 53: 'ringneck snake, ring-necked snake, ring snake', 54: 'hognose snake, puff adder, sand viper', 55: 'green snake, grass snake', 56: 'king snake, kingsnake', 57: 'garter snake, grass snake', 58: 'water snake', 59: 'vine snake', 60: 'night snake, Hypsiglena torquata', 61: 'boa constrictor, Constrictor constrictor', 62: 'rock python, rock snake, Python sebae', 63: 'Indian cobra, Naja naja', 64: 'green mamba', 65: 'sea snake', 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus', 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus', 68: 'sidewinder, horned rattlesnake, Crotalus cerastes', 69: 'trilobite', 70: 'harvestman, daddy longlegs, Phalangium opilio', 71: 'scorpion', 72: 'black and gold garden spider, Argiope aurantia', 73: 'barn spider, Araneus cavaticus', 74: 'garden spider, Aranea diademata', 75: 'black widow, Latrodectus mactans', 76: 'tarantula', 77: 'wolf spider, hunting spider', 78: 'tick', 79: 'centipede', 80: 'black grouse', 81: 'ptarmigan', 82: 'ruffed grouse, partridge, Bonasa umbellus', 83: 'prairie chicken, prairie grouse, prairie fowl', 84: 'peacock', 85: 'quail', 86: 'partridge', 87: 'African grey, African gray, Psittacus erithacus', 88: 'macaw', 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita', 90: 'lorikeet', 91: 'coucal', 92: 'bee eater', 93: 'hornbill', 94: 'hummingbird', 95: 'jacamar', 96: 'toucan', 97: 'drake', 98: 'red-breasted merganser, Mergus serrator', 99: 'goose', 100: 'black swan, Cygnus atratus', 101: 'tusker', 102: 'echidna, spiny anteater, anteater', 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus', 104: 'wallaby, brush kangaroo', 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus', 106: 'wombat', 107: 'jellyfish', 108: 'sea anemone, anemone', 109: 'brain coral', 110: 'flatworm, platyhelminth', 111: 'nematode, nematode worm, roundworm', 112: 'conch', 113: 'snail', 114: 'slug', 115: 'sea slug, nudibranch', 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore', 117: 'chambered nautilus, pearly nautilus, nautilus', 118: 'Dungeness crab, Cancer magister', 119: 'rock crab, Cancer irroratus', 120: 'fiddler crab', 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica', 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus', 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish', 124: 'crayfish, crawfish, crawdad, crawdaddy', 125: 'hermit crab', 126: 'isopod', 127: 'white stork, Ciconia ciconia', 128: 'black stork, Ciconia nigra', 129: 'spoonbill', 130: 'flamingo', 131: 'little blue heron, Egretta caerulea', 132: 'American egret, great white heron, Egretta albus', 133: 'bittern', 134: 'crane', 135: 'limpkin, Aramus pictus', 136: 'European gallinule, Porphyrio porphyrio', 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana', 138: 'bustard', 139: 'ruddy turnstone, Arenaria interpres', 140: 'red-backed sandpiper, dunlin, Erolia alpina', 141: 'redshank, Tringa totanus', 142: 'dowitcher', 143: 'oystercatcher, oyster catcher', 144: 'pelican', 145: 'king penguin, Aptenodytes patagonica', 146: 'albatross, mollymawk', 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus', 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca', 149: 'dugong, Dugong dugon', 150: 'sea lion', 151: 'Chihuahua', 152: 'Japanese spaniel', 153: 'Maltese dog, Maltese terrier, Maltese', 154: 'Pekinese, Pekingese, Peke', 155: 'Shih-Tzu', 156: 'Blenheim spaniel', 157: 'papillon', 158: 'toy terrier', 159: 'Rhodesian ridgeback', 160: 'Afghan hound, Afghan', 161: 'basset, basset hound', 162: 'beagle', 163: 'bloodhound, sleuthhound', 164: 'bluetick', 165: 'black-and-tan coonhound', 166: 'Walker hound, Walker foxhound', 167: 'English foxhound', 168: 'redbone', 169: 'borzoi, Russian wolfhound', 170: 'Irish wolfhound', 171: 'Italian greyhound', 172: 'whippet', 173: 'Ibizan hound, Ibizan Podenco', 174: 'Norwegian elkhound, elkhound', 175: 'otterhound, otter hound', 176: 'Saluki, gazelle hound', 177: 'Scottish deerhound, deerhound', 178: 'Weimaraner', 179: 'Staffordshire bullterrier, Staffordshire bull terrier', 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier', 181: 'Bedlington terrier', 182: 'Border terrier', 183: 'Kerry blue terrier', 184: 'Irish terrier', 185: 'Norfolk terrier', 186: 'Norwich terrier', 187: 'Yorkshire terrier', 188: 'wire-haired fox terrier', 189: 'Lakeland terrier', 190: 'Sealyham terrier, Sealyham', 191: 'Airedale, Airedale terrier', 192: 'cairn, cairn terrier', 193: 'Australian terrier', 194: 'Dandie Dinmont, Dandie Dinmont terrier', 195: 'Boston bull, Boston terrier', 196: 'miniature schnauzer', 197: 'giant schnauzer', 198: 'standard schnauzer', 199: 'Scotch terrier, Scottish terrier, Scottie', 200: 'Tibetan terrier, chrysanthemum dog', 201: 'silky terrier, Sydney silky', 202: 'soft-coated wheaten terrier', 203: 'West Highland white terrier', 204: 'Lhasa, Lhasa apso', 205: 'flat-coated retriever', 206: 'curly-coated retriever', 207: 'golden retriever', 208: 'Labrador retriever', 209: 'Chesapeake Bay retriever', 210: 'German short-haired pointer', 211: 'vizsla, Hungarian pointer', 212: 'English setter', 213: 'Irish setter, red setter', 214: 'Gordon setter', 215: 'Brittany spaniel', 216: 'clumber, clumber spaniel', 217: 'English springer, English springer spaniel', 218: 'Welsh springer spaniel', 219: 'cocker spaniel, English cocker spaniel, cocker', 220: 'Sussex spaniel', 221: 'Irish water spaniel', 222: 'kuvasz', 223: 'schipperke', 224: 'groenendael', 225: 'malinois', 226: 'briard', 227: 'kelpie', 228: 'komondor', 229: 'Old English sheepdog, bobtail', 230: 'Shetland sheepdog, Shetland sheep dog, Shetland', 231: 'collie', 232: 'Border collie', 233: 'Bouvier des Flandres, Bouviers des Flandres', 234: 'Rottweiler', 235: 'German shepherd, German shepherd dog, German police dog, alsatian', 236: 'Doberman, Doberman pinscher', 237: 'miniature pinscher', 238: 'Greater Swiss Mountain dog', 239: 'Bernese mountain dog', 240: 'Appenzeller', 241: 'EntleBucher', 242: 'boxer', 243: 'bull mastiff', 244: 'Tibetan mastiff', 245: 'French bulldog', 246: 'Great Dane', 247: 'Saint Bernard, St Bernard', 248: 'Eskimo dog, husky', 249: 'malamute, malemute, Alaskan malamute', 250: 'Siberian husky', 251: 'dalmatian, coach dog, carriage dog', 252: 'affenpinscher, monkey pinscher, monkey dog', 253: 'basenji', 254: 'pug, pug-dog', 255: 'Leonberg', 256: 'Newfoundland, Newfoundland dog', 257: 'Great Pyrenees', 258: 'Samoyed, Samoyede', 259: 'Pomeranian', 260: 'chow, chow chow', 261: 'keeshond', 262: 'Brabancon griffon', 263: 'Pembroke, Pembroke Welsh corgi', 264: 'Cardigan, Cardigan Welsh corgi', 265: 'toy poodle', 266: 'miniature poodle', 267: 'standard poodle', 268: 'Mexican hairless', 269: 'timber wolf, grey wolf, gray wolf, Canis lupus', 270: 'white wolf, Arctic wolf, Canis lupus tundrarum', 271: 'red wolf, maned wolf, Canis rufus, Canis niger', 272: 'coyote, prairie wolf, brush wolf, Canis latrans', 273: 'dingo, warrigal, warragal, Canis dingo', 274: 'dhole, Cuon alpinus', 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus', 276: 'hyena, hyaena', 277: 'red fox, Vulpes vulpes', 278: 'kit fox, Vulpes macrotis', 279: 'Arctic fox, white fox, Alopex lagopus', 280: 'grey fox, gray fox, Urocyon cinereoargenteus', 281: 'tabby, tabby cat', 282: 'tiger cat', 283: 'Persian cat', 284: 'Siamese cat, Siamese', 285: 'Egyptian cat', 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor', 287: 'lynx, catamount', 288: 'leopard, Panthera pardus', 289: 'snow leopard, ounce, Panthera uncia', 290: 'jaguar, panther, Panthera onca, Felis onca', 291: 'lion, king of beasts, Panthera leo', 292: 'tiger, Panthera tigris', 293: 'cheetah, chetah, Acinonyx jubatus', 294: 'brown bear, bruin, Ursus arctos', 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus', 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus', 297: 'sloth bear, Melursus ursinus, Ursus ursinus', 298: 'mongoose', 299: 'meerkat, mierkat', 300: 'tiger beetle', 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle', 302: 'ground beetle, carabid beetle', 303: 'long-horned beetle, longicorn, longicorn beetle', 304: 'leaf beetle, chrysomelid', 305: 'dung beetle', 306: 'rhinoceros beetle', 307: 'weevil', 308: 'fly', 309: 'bee', 310: 'ant, emmet, pismire', 311: 'grasshopper, hopper', 312: 'cricket', 313: 'walking stick, walkingstick, stick insect', 314: 'cockroach, roach', 315: 'mantis, mantid', 316: 'cicada, cicala', 317: 'leafhopper', 318: 'lacewing, lacewing fly', 319: \"dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk\", 320: 'damselfly', 321: 'admiral', 322: 'ringlet, ringlet butterfly', 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus', 324: 'cabbage butterfly', 325: 'sulphur butterfly, sulfur butterfly', 326: 'lycaenid, lycaenid butterfly', 327: 'starfish, sea star', 328: 'sea urchin', 329: 'sea cucumber, holothurian', 330: 'wood rabbit, cottontail, cottontail rabbit', 331: 'hare', 332: 'Angora, Angora rabbit', 333: 'hamster', 334: 'porcupine, hedgehog', 335: 'fox squirrel, eastern fox squirrel, Sciurus niger', 336: 'marmot', 337: 'beaver', 338: 'guinea pig, Cavia cobaya', 339: 'sorrel', 340: 'zebra', 341: 'hog, pig, grunter, squealer, Sus scrofa', 342: 'wild boar, boar, Sus scrofa', 343: 'warthog', 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius', 345: 'ox', 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis', 347: 'bison', 348: 'ram, tup', 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis', 350: 'ibex, Capra ibex', 351: 'hartebeest', 352: 'impala, Aepyceros melampus', 353: 'gazelle', 354: 'Arabian camel, dromedary, Camelus dromedarius', 355: 'llama', 356: 'weasel', 357: 'mink', 358: 'polecat, fitch, foulmart, foumart, Mustela putorius', 359: 'black-footed ferret, ferret, Mustela nigripes', 360: 'otter', 361: 'skunk, polecat, wood pussy', 362: 'badger', 363: 'armadillo', 364: 'three-toed sloth, ai, Bradypus tridactylus', 365: 'orangutan, orang, orangutang, Pongo pygmaeus', 366: 'gorilla, Gorilla gorilla', 367: 'chimpanzee, chimp, Pan troglodytes', 368: 'gibbon, Hylobates lar', 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus', 370: 'guenon, guenon monkey', 371: 'patas, hussar monkey, Erythrocebus patas', 372: 'baboon', 373: 'macaque', 374: 'langur', 375: 'colobus, colobus monkey', 376: 'proboscis monkey, Nasalis larvatus', 377: 'marmoset', 378: 'capuchin, ringtail, Cebus capucinus', 379: 'howler monkey, howler', 380: 'titi, titi monkey', 381: 'spider monkey, Ateles geoffroyi', 382: 'squirrel monkey, Saimiri sciureus', 383: 'Madagascar cat, ring-tailed lemur, Lemur catta', 384: 'indri, indris, Indri indri, Indri brevicaudatus', 385: 'Indian elephant, Elephas maximus', 386: 'African elephant, Loxodonta africana', 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens', 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca', 389: 'barracouta, snoek', 390: 'eel', 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch', 392: 'rock beauty, Holocanthus tricolor', 393: 'anemone fish', 394: 'sturgeon', 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus', 396: 'lionfish', 397: 'puffer, pufferfish, blowfish, globefish', 398: 'abacus', 399: 'abaya', 400: \"academic gown, academic robe, judge's robe\", 401: 'accordion, piano accordion, squeeze box', 402: 'acoustic guitar', 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier', 404: 'airliner', 405: 'airship, dirigible', 406: 'altar', 407: 'ambulance', 408: 'amphibian, amphibious vehicle', 409: 'analog clock', 410: 'apiary, bee house', 411: 'apron', 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin', 413: 'assault rifle, assault gun', 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack', 415: 'bakery, bakeshop, bakehouse', 416: 'balance beam, beam', 417: 'balloon', 418: 'ballpoint, ballpoint pen, ballpen, Biro', 419: 'Band Aid', 420: 'banjo', 421: 'bannister, banister, balustrade, balusters, handrail', 422: 'barbell', 423: 'barber chair', 424: 'barbershop', 425: 'barn', 426: 'barometer', 427: 'barrel, cask', 428: 'barrow, garden cart, lawn cart, wheelbarrow', 429: 'baseball', 430: 'basketball', 431: 'bassinet', 432: 'bassoon', 433: 'bathing cap, swimming cap', 434: 'bath towel', 435: 'bathtub, bathing tub, bath, tub', 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon', 437: 'beacon, lighthouse, beacon light, pharos', 438: 'beaker', 439: 'bearskin, busby, shako', 440: 'beer bottle', 441: 'beer glass', 442: 'bell cote, bell cot', 443: 'bib', 444: 'bicycle-built-for-two, tandem bicycle, tandem', 445: 'bikini, two-piece', 446: 'binder, ring-binder', 447: 'binoculars, field glasses, opera glasses', 448: 'birdhouse', 449: 'boathouse', 450: 'bobsled, bobsleigh, bob', 451: 'bolo tie, bolo, bola tie, bola', 452: 'bonnet, poke bonnet', 453: 'bookcase', 454: 'bookshop, bookstore, bookstall', 455: 'bottlecap', 456: 'bow', 457: 'bow tie, bow-tie, bowtie', 458: 'brass, memorial tablet, plaque', 459: 'brassiere, bra, bandeau', 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty', 461: 'breastplate, aegis, egis', 462: 'broom', 463: 'bucket, pail', 464: 'buckle', 465: 'bulletproof vest', 466: 'bullet train, bullet', 467: 'butcher shop, meat market', 468: 'cab, hack, taxi, taxicab', 469: 'caldron, cauldron', 470: 'candle, taper, wax light', 471: 'cannon', 472: 'canoe', 473: 'can opener, tin opener', 474: 'cardigan', 475: 'car mirror', 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig', 477: \"carpenter's kit, tool kit\", 478: 'carton', 479: 'car wheel', 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM', 481: 'cassette', 482: 'cassette player', 483: 'castle', 484: 'catamaran', 485: 'CD player', 486: 'cello, violoncello', 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone', 488: 'chain', 489: 'chainlink fence', 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour', 491: 'chain saw, chainsaw', 492: 'chest', 493: 'chiffonier, commode', 494: 'chime, bell, gong', 495: 'china cabinet, china closet', 496: 'Christmas stocking', 497: 'church, church building', 498: 'cinema, movie theater, movie theatre, movie house, picture palace', 499: 'cleaver, meat cleaver, chopper', 500: 'cliff dwelling', 501: 'cloak', 502: 'clog, geta, patten, sabot', 503: 'cocktail shaker', 504: 'coffee mug', 505: 'coffeepot', 506: 'coil, spiral, volute, whorl, helix', 507: 'combination lock', 508: 'computer keyboard, keypad', 509: 'confectionery, confectionary, candy store', 510: 'container ship, containership, container vessel', 511: 'convertible', 512: 'corkscrew, bottle screw', 513: 'cornet, horn, trumpet, trump', 514: 'cowboy boot', 515: 'cowboy hat, ten-gallon hat', 516: 'cradle', 517: 'crane', 518: 'crash helmet', 519: 'crate', 520: 'crib, cot', 521: 'Crock Pot', 522: 'croquet ball', 523: 'crutch', 524: 'cuirass', 525: 'dam, dike, dyke', 526: 'desk', 527: 'desktop computer', 528: 'dial telephone, dial phone', 529: 'diaper, nappy, napkin', 530: 'digital clock', 531: 'digital watch', 532: 'dining table, board', 533: 'dishrag, dishcloth', 534: 'dishwasher, dish washer, dishwashing machine', 535: 'disk brake, disc brake', 536: 'dock, dockage, docking facility', 537: 'dogsled, dog sled, dog sleigh', 538: 'dome', 539: 'doormat, welcome mat', 540: 'drilling platform, offshore rig', 541: 'drum, membranophone, tympan', 542: 'drumstick', 543: 'dumbbell', 544: 'Dutch oven', 545: 'electric fan, blower', 546: 'electric guitar', 547: 'electric locomotive', 548: 'entertainment center', 549: 'envelope', 550: 'espresso maker', 551: 'face powder', 552: 'feather boa, boa', 553: 'file, file cabinet, filing cabinet', 554: 'fireboat', 555: 'fire engine, fire truck', 556: 'fire screen, fireguard', 557: 'flagpole, flagstaff', 558: 'flute, transverse flute', 559: 'folding chair', 560: 'football helmet', 561: 'forklift', 562: 'fountain', 563: 'fountain pen', 564: 'four-poster', 565: 'freight car', 566: 'French horn, horn', 567: 'frying pan, frypan, skillet', 568: 'fur coat', 569: 'garbage truck, dustcart', 570: 'gasmask, respirator, gas helmet', 571: 'gas pump, gasoline pump, petrol pump, island dispenser', 572: 'goblet', 573: 'go-kart', 574: 'golf ball', 575: 'golfcart, golf cart', 576: 'gondola', 577: 'gong, tam-tam', 578: 'gown', 579: 'grand piano, grand', 580: 'greenhouse, nursery, glasshouse', 581: 'grille, radiator grille', 582: 'grocery store, grocery, food market, market', 583: 'guillotine', 584: 'hair slide', 585: 'hair spray', 586: 'half track', 587: 'hammer', 588: 'hamper', 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier', 590: 'hand-held computer, hand-held microcomputer', 591: 'handkerchief, hankie, hanky, hankey', 592: 'hard disc, hard disk, fixed disk', 593: 'harmonica, mouth organ, harp, mouth harp', 594: 'harp', 595: 'harvester, reaper', 596: 'hatchet', 597: 'holster', 598: 'home theater, home theatre', 599: 'honeycomb', 600: 'hook, claw', 601: 'hoopskirt, crinoline', 602: 'horizontal bar, high bar', 603: 'horse cart, horse-cart', 604: 'hourglass', 605: 'iPod', 606: 'iron, smoothing iron', 607: \"jack-o'-lantern\", 608: 'jean, blue jean, denim', 609: 'jeep, landrover', 610: 'jersey, T-shirt, tee shirt', 611: 'jigsaw puzzle', 612: 'jinrikisha, ricksha, rickshaw', 613: 'joystick', 614: 'kimono', 615: 'knee pad', 616: 'knot', 617: 'lab coat, laboratory coat', 618: 'ladle', 619: 'lampshade, lamp shade', 620: 'laptop, laptop computer', 621: 'lawn mower, mower', 622: 'lens cap, lens cover', 623: 'letter opener, paper knife, paperknife', 624: 'library', 625: 'lifeboat', 626: 'lighter, light, igniter, ignitor', 627: 'limousine, limo', 628: 'liner, ocean liner', 629: 'lipstick, lip rouge', 630: 'Loafer', 631: 'lotion', 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system', 633: \"loupe, jeweler's loupe\", 634: 'lumbermill, sawmill', 635: 'magnetic compass', 636: 'mailbag, postbag', 637: 'mailbox, letter box', 638: 'maillot', 639: 'maillot, tank suit', 640: 'manhole cover', 641: 'maraca', 642: 'marimba, xylophone', 643: 'mask', 644: 'matchstick', 645: 'maypole', 646: 'maze, labyrinth', 647: 'measuring cup', 648: 'medicine chest, medicine cabinet', 649: 'megalith, megalithic structure', 650: 'microphone, mike', 651: 'microwave, microwave oven', 652: 'military uniform', 653: 'milk can', 654: 'minibus', 655: 'miniskirt, mini', 656: 'minivan', 657: 'missile', 658: 'mitten', 659: 'mixing bowl', 660: 'mobile home, manufactured home', 661: 'Model T', 662: 'modem', 663: 'monastery', 664: 'monitor', 665: 'moped', 666: 'mortar', 667: 'mortarboard', 668: 'mosque', 669: 'mosquito net', 670: 'motor scooter, scooter', 671: 'mountain bike, all-terrain bike, off-roader', 672: 'mountain tent', 673: 'mouse, computer mouse', 674: 'mousetrap', 675: 'moving van', 676: 'muzzle', 677: 'nail', 678: 'neck brace', 679: 'necklace', 680: 'nipple', 681: 'notebook, notebook computer', 682: 'obelisk', 683: 'oboe, hautboy, hautbois', 684: 'ocarina, sweet potato', 685: 'odometer, hodometer, mileometer, milometer', 686: 'oil filter', 687: 'organ, pipe organ', 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO', 689: 'overskirt', 690: 'oxcart', 691: 'oxygen mask', 692: 'packet', 693: 'paddle, boat paddle', 694: 'paddlewheel, paddle wheel', 695: 'padlock', 696: 'paintbrush', 697: \"pajama, pyjama, pj's, jammies\", 698: 'palace', 699: 'panpipe, pandean pipe, syrinx', 700: 'paper towel', 701: 'parachute, chute', 702: 'parallel bars, bars', 703: 'park bench', 704: 'parking meter', 705: 'passenger car, coach, carriage', 706: 'patio, terrace', 707: 'pay-phone, pay-station', 708: 'pedestal, plinth, footstall', 709: 'pencil box, pencil case', 710: 'pencil sharpener', 711: 'perfume, essence', 712: 'Petri dish', 713: 'photocopier', 714: 'pick, plectrum, plectron', 715: 'pickelhaube', 716: 'picket fence, paling', 717: 'pickup, pickup truck', 718: 'pier', 719: 'piggy bank, penny bank', 720: 'pill bottle', 721: 'pillow', 722: 'ping-pong ball', 723: 'pinwheel', 724: 'pirate, pirate ship', 725: 'pitcher, ewer', 726: \"plane, carpenter's plane, woodworking plane\", 727: 'planetarium', 728: 'plastic bag', 729: 'plate rack', 730: 'plow, plough', 731: \"plunger, plumber's helper\", 732: 'Polaroid camera, Polaroid Land camera', 733: 'pole', 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria', 735: 'poncho', 736: 'pool table, billiard table, snooker table', 737: 'pop bottle, soda bottle', 738: 'pot, flowerpot', 739: \"potter's wheel\", 740: 'power drill', 741: 'prayer rug, prayer mat', 742: 'printer', 743: 'prison, prison house', 744: 'projectile, missile', 745: 'projector', 746: 'puck, hockey puck', 747: 'punching bag, punch bag, punching ball, punchball', 748: 'purse', 749: 'quill, quill pen', 750: 'quilt, comforter, comfort, puff', 751: 'racer, race car, racing car', 752: 'racket, racquet', 753: 'radiator', 754: 'radio, wireless', 755: 'radio telescope, radio reflector', 756: 'rain barrel', 757: 'recreational vehicle, RV, R.V.', 758: 'reel', 759: 'reflex camera', 760: 'refrigerator, icebox', 761: 'remote control, remote', 762: 'restaurant, eating house, eating place, eatery', 763: 'revolver, six-gun, six-shooter', 764: 'rifle', 765: 'rocking chair, rocker', 766: 'rotisserie', 767: 'rubber eraser, rubber, pencil eraser', 768: 'rugby ball', 769: 'rule, ruler', 770: 'running shoe', 771: 'safe', 772: 'safety pin', 773: 'saltshaker, salt shaker', 774: 'sandal', 775: 'sarong', 776: 'sax, saxophone', 777: 'scabbard', 778: 'scale, weighing machine', 779: 'school bus', 780: 'schooner', 781: 'scoreboard', 782: 'screen, CRT screen', 783: 'screw', 784: 'screwdriver', 785: 'seat belt, seatbelt', 786: 'sewing machine', 787: 'shield, buckler', 788: 'shoe shop, shoe-shop, shoe store', 789: 'shoji', 790: 'shopping basket', 791: 'shopping cart', 792: 'shovel', 793: 'shower cap', 794: 'shower curtain', 795: 'ski', 796: 'ski mask', 797: 'sleeping bag', 798: 'slide rule, slipstick', 799: 'sliding door', 800: 'slot, one-armed bandit', 801: 'snorkel', 802: 'snowmobile', 803: 'snowplow, snowplough', 804: 'soap dispenser', 805: 'soccer ball', 806: 'sock', 807: 'solar dish, solar collector, solar furnace', 808: 'sombrero', 809: 'soup bowl', 810: 'space bar', 811: 'space heater', 812: 'space shuttle', 813: 'spatula', 814: 'speedboat', 815: \"spider web, spider's web\", 816: 'spindle', 817: 'sports car, sport car', 818: 'spotlight, spot', 819: 'stage', 820: 'steam locomotive', 821: 'steel arch bridge', 822: 'steel drum', 823: 'stethoscope', 824: 'stole', 825: 'stone wall', 826: 'stopwatch, stop watch', 827: 'stove', 828: 'strainer', 829: 'streetcar, tram, tramcar, trolley, trolley car', 830: 'stretcher', 831: 'studio couch, day bed', 832: 'stupa, tope', 833: 'submarine, pigboat, sub, U-boat', 834: 'suit, suit of clothes', 835: 'sundial', 836: 'sunglass', 837: 'sunglasses, dark glasses, shades', 838: 'sunscreen, sunblock, sun blocker', 839: 'suspension bridge', 840: 'swab, swob, mop', 841: 'sweatshirt', 842: 'swimming trunks, bathing trunks', 843: 'swing', 844: 'switch, electric switch, electrical switch', 845: 'syringe', 846: 'table lamp', 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle', 848: 'tape player', 849: 'teapot', 850: 'teddy, teddy bear', 851: 'television, television system', 852: 'tennis ball', 853: 'thatch, thatched roof', 854: 'theater curtain, theatre curtain', 855: 'thimble', 856: 'thresher, thrasher, threshing machine', 857: 'throne', 858: 'tile roof', 859: 'toaster', 860: 'tobacco shop, tobacconist shop, tobacconist', 861: 'toilet seat', 862: 'torch', 863: 'totem pole', 864: 'tow truck, tow car, wrecker', 865: 'toyshop', 866: 'tractor', 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi', 868: 'tray', 869: 'trench coat', 870: 'tricycle, trike, velocipede', 871: 'trimaran', 872: 'tripod', 873: 'triumphal arch', 874: 'trolleybus, trolley coach, trackless trolley', 875: 'trombone', 876: 'tub, vat', 877: 'turnstile', 878: 'typewriter keyboard', 879: 'umbrella', 880: 'unicycle, monocycle', 881: 'upright, upright piano', 882: 'vacuum, vacuum cleaner', 883: 'vase', 884: 'vault', 885: 'velvet', 886: 'vending machine', 887: 'vestment', 888: 'viaduct', 889: 'violin, fiddle', 890: 'volleyball', 891: 'waffle iron', 892: 'wall clock', 893: 'wallet, billfold, notecase, pocketbook', 894: 'wardrobe, closet, press', 895: 'warplane, military plane', 896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin', 897: 'washer, automatic washer, washing machine', 898: 'water bottle', 899: 'water jug', 900: 'water tower', 901: 'whiskey jug', 902: 'whistle', 903: 'wig', 904: 'window screen', 905: 'window shade', 906: 'Windsor tie', 907: 'wine bottle', 908: 'wing', 909: 'wok', 910: 'wooden spoon', 911: 'wool, woolen, woollen', 912: 'worm fence, snake fence, snake-rail fence, Virginia fence', 913: 'wreck', 914: 'yawl', 915: 'yurt', 916: 'web site, website, internet site, site', 917: 'comic book', 918: 'crossword puzzle, crossword', 919: 'street sign', 920: 'traffic light, traffic signal, stoplight', 921: 'book jacket, dust cover, dust jacket, dust wrapper', 922: 'menu', 923: 'plate', 924: 'guacamole', 925: 'consomme', 926: 'hot pot, hotpot', 927: 'trifle', 928: 'ice cream, icecream', 929: 'ice lolly, lolly, lollipop, popsicle', 930: 'French loaf', 931: 'bagel, beigel', 932: 'pretzel', 933: 'cheeseburger', 934: 'hotdog, hot dog, red hot', 935: 'mashed potato', 936: 'head cabbage', 937: 'broccoli', 938: 'cauliflower', 939: 'zucchini, courgette', 940: 'spaghetti squash', 941: 'acorn squash', 942: 'butternut squash', 943: 'cucumber, cuke', 944: 'artichoke, globe artichoke', 945: 'bell pepper', 946: 'cardoon', 947: 'mushroom', 948: 'Granny Smith', 949: 'strawberry', 950: 'orange', 951: 'lemon', 952: 'fig', 953: 'pineapple, ananas', 954: 'banana', 955: 'jackfruit, jak, jack', 956: 'custard apple', 957: 'pomegranate', 958: 'hay', 959: 'carbonara', 960: 'chocolate sauce, chocolate syrup', 961: 'dough', 962: 'meat loaf, meatloaf', 963: 'pizza, pizza pie', 964: 'potpie', 965: 'burrito', 966: 'red wine', 967: 'espresso', 968: 'cup', 969: 'eggnog', 970: 'alp', 971: 'bubble', 972: 'cliff, drop, drop-off', 973: 'coral reef', 974: 'geyser', 975: 'lakeside, lakeshore', 976: 'promontory, headland, head, foreland', 977: 'sandbar, sand bar', 978: 'seashore, coast, seacoast, sea-coast', 979: 'valley, vale', 980: 'volcano', 981: 'ballplayer, baseball player', 982: 'groom, bridegroom', 983: 'scuba diver', 984: 'rapeseed', 985: 'daisy', 986: \"yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum\", 987: 'corn', 988: 'acorn', 989: 'hip, rose hip, rosehip', 990: 'buckeye, horse chestnut, conker', 991: 'coral fungus', 992: 'agaric', 993: 'gyromitra', 994: 'stinkhorn, carrion fungus', 995: 'earthstar', 996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa', 997: 'bolete', 998: 'ear, spike, capitulum', 999: 'toilet tissue, toilet paper, bathroom tissue'}"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3QV2NMzafkrt"
   },
   "outputs": [],
   "source": [
    "#defining the transformations for the data\n",
    "\n",
    "transform = transforms.Compose([\n",
    "    transforms.Resize(224),\n",
    "    transforms.ToTensor(),\n",
    "    #normalize the images with imagenet data mean and std\n",
    "    transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "eyHqpaf6euAk"
   },
   "outputs": [],
   "source": [
    "#define the data we uploaded as evaluation data and apply the transformations\n",
    "\n",
    "evalset = torchvision.datasets.ImageFolder(root = \"./data/imagenet\", transform = transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "rl861jd9hyS4"
   },
   "outputs": [],
   "source": [
    "#create a data loader for evaluation\n",
    "\n",
    "batch_size=1 #batch size\n",
    "evalloader = torch.utils.data.DataLoader(evalset, batch_size = batch_size, shuffle = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 70
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 11988,
     "status": "ok",
     "timestamp": 1558629542751,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "dAZeEYjkhNi6",
    "outputId": "ea0b168a-59bf-41d5-e464-16cf1320d4db"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 3, 224, 224])\n",
      "torch.Size([3, 224, 224])\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "#looking at data using iter\n",
    "\n",
    "dataiter = iter(evalloader)\n",
    "images, labels = dataiter.next()\n",
    "\n",
    "#shape of images bunch\n",
    "print(images.shape)\n",
    "#shape of single image in a bunch\n",
    "print(images[0].shape)\n",
    "\n",
    "#label of the image\n",
    "print(labels[0].item())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "m8ibhXZNlbgn"
   },
   "source": [
    "## Load pretrained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "vN8T1NVzdbO7"
   },
   "outputs": [],
   "source": [
    "#for visualization we will use vgg16 pretrained on imagenet data\n",
    "\n",
    "model = models.vgg16(pretrained=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "IbWGtzk5ejXf",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VGG(\n",
       "  (features): Sequential(\n",
       "    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (1): ReLU(inplace)\n",
       "    (2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (3): ReLU(inplace)\n",
       "    (4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (6): ReLU(inplace)\n",
       "    (7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (8): ReLU(inplace)\n",
       "    (9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (11): ReLU(inplace)\n",
       "    (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (13): ReLU(inplace)\n",
       "    (14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (15): ReLU(inplace)\n",
       "    (16): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (17): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (18): ReLU(inplace)\n",
       "    (19): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (20): ReLU(inplace)\n",
       "    (21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (22): ReLU(inplace)\n",
       "    (23): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (24): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (25): ReLU(inplace)\n",
       "    (26): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (27): ReLU(inplace)\n",
       "    (28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (29): ReLU(inplace)\n",
       "    (30): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  )\n",
       "  (avgpool): AdaptiveAvgPool2d(output_size=(7, 7))\n",
       "  (classifier): Sequential(\n",
       "    (0): Linear(in_features=25088, out_features=4096, bias=True)\n",
       "    (1): ReLU(inplace)\n",
       "    (2): Dropout(p=0.5)\n",
       "    (3): Linear(in_features=4096, out_features=4096, bias=True)\n",
       "    (4): ReLU(inplace)\n",
       "    (5): Dropout(p=0.5)\n",
       "    (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "FxyVJKDKljdi"
   },
   "source": [
    "## Visualise image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "BmvCfwbsfVCR"
   },
   "outputs": [],
   "source": [
    "def imshow(img, title):\n",
    "  \n",
    "  \"\"\"Custom function to display the image using matplotlib\"\"\"\n",
    "  \n",
    "  #define std correction to be made\n",
    "  std_correction = np.asarray([0.229, 0.224, 0.225]).reshape(3, 1, 1)\n",
    "  \n",
    "  #define mean correction to be made\n",
    "  mean_correction = np.asarray([0.485, 0.456, 0.406]).reshape(3, 1, 1)\n",
    "  \n",
    "  #convert the tensor img to numpy img and de normalize \n",
    "  npimg = np.multiply(img.numpy(), std_correction) + mean_correction\n",
    "  \n",
    "  #plot the numpy image\n",
    "  plt.figure(figsize = (batch_size * 4, 4))\n",
    "  plt.axis(\"off\")\n",
    "  plt.imshow(np.transpose(npimg, (1, 2, 0)))\n",
    "  plt.title(title)\n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ETr82Xbshof_"
   },
   "outputs": [],
   "source": [
    "#custom function to fetch images from dataloader\n",
    "\n",
    "def show_batch_images(dataloader):\n",
    "  images,_ = next(iter(dataloader))\n",
    "  \n",
    "  #run the model on the images\n",
    "  outputs = model(images)\n",
    "  \n",
    "  #get the maximum class \n",
    "  _, pred = torch.max(outputs.data, 1)\n",
    "  \n",
    "  #make grid\n",
    "  img = torchvision.utils.make_grid(images)\n",
    "  \n",
    "  #call the function\n",
    "  imshow(img, title=[classes[x.item()] for x in pred])\n",
    "  \n",
    "  return images, pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2013,
     "status": "ok",
     "timestamp": 1558629717998,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "W1ZVKO_chtwB",
    "outputId": "d5894486-f8bb-4968-afb4-1cedb88f23db"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "images, pred = show_batch_images(evalloader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "RbE42pFStpOF"
   },
   "source": [
    "## Occlusion analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1161,
     "status": "ok",
     "timestamp": 1558630402604,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "Pv3v7u5ykk38",
    "outputId": "d81f1085-46b7-4930-8c62-7eb397f6e607"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 1000])\n",
      "0.8043237328529358\n"
     ]
    }
   ],
   "source": [
    "#running inference on the images without occlusion\n",
    "\n",
    "#vgg16 pretrained model\n",
    "outputs = model(images)\n",
    "print(outputs.shape)\n",
    "\n",
    "#passing the outputs through softmax to interpret them as probability\n",
    "outputs = nn.functional.softmax(outputs, dim = 1)\n",
    "\n",
    "#getting the maximum predicted label\n",
    "prob_no_occ, pred = torch.max(outputs.data, 1)\n",
    "\n",
    "#get the first item\n",
    "prob_no_occ = prob_no_occ[0].item()\n",
    "\n",
    "print(prob_no_occ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "AqonWK0Mmt87"
   },
   "outputs": [],
   "source": [
    "#custom function to conduct occlusion experiments\n",
    "\n",
    "def occlusion(model, image, label, occ_size = 50, occ_stride = 50, occ_pixel = 0.5):\n",
    "  \n",
    "    #get the width and height of the image\n",
    "    width, height = image.shape[-2], image.shape[-1]\n",
    "  \n",
    "    #setting the output image width and height\n",
    "    output_height = int(np.ceil((height-occ_size)/occ_stride))\n",
    "    output_width = int(np.ceil((width-occ_size)/occ_stride))\n",
    "  \n",
    "    #create a white image of sizes we defined\n",
    "    heatmap = torch.zeros((output_height, output_width))\n",
    "    \n",
    "    #iterate all the pixels in each column\n",
    "    for h in range(0, height):\n",
    "        for w in range(0, width):\n",
    "            \n",
    "            h_start = h*occ_stride\n",
    "            w_start = w*occ_stride\n",
    "            h_end = min(height, h_start + occ_size)\n",
    "            w_end = min(width, w_start + occ_size)\n",
    "            \n",
    "            if (w_end) >= width or (h_end) >= height:\n",
    "                continue\n",
    "            \n",
    "            input_image = image.clone().detach()\n",
    "            \n",
    "            #replacing all the pixel information in the image with occ_pixel(grey) in the specified location\n",
    "            input_image[:, :, w_start:w_end, h_start:h_end] = occ_pixel\n",
    "            \n",
    "            #run inference on modified image\n",
    "            output = model(input_image)\n",
    "            output = nn.functional.softmax(output, dim=1)\n",
    "            prob = output.tolist()[0][label]\n",
    "            \n",
    "            #setting the heatmap location to probability value\n",
    "            heatmap[h, w] = prob \n",
    "\n",
    "    return heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gdzEyz4Upf8M"
   },
   "outputs": [],
   "source": [
    "heatmap = occlusion(model, images, pred[0].item(), 32, 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 255
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2053,
     "status": "ok",
     "timestamp": 1558632613986,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "Lh1n930Us4bI",
    "outputId": "51007c76-c092-4f5c-c174-81852f272d6d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#displaying the image using seaborn heatmap and also setting the maximum value of gradient to probability\n",
    "imgplot = sns.heatmap(heatmap, xticklabels=False, yticklabels=False, vmax=prob_no_occ)\n",
    "figure = imgplot.get_figure()    \n",
    "figure.savefig('svm_conf.png', dpi=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "nQN3po0AtrWr"
   },
   "source": [
    "## Filter visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 8861,
     "status": "ok",
     "timestamp": 1558632409901,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "AOI2LLPGtfRq",
    "outputId": "54d922de-efcf-4d98-be1c-383872ae5f4e"
   },
   "outputs": [],
   "source": [
    "#for filter visualization, we will use alexnet pretrained with imagenet data\n",
    "\n",
    "alexnet = models.alexnet(pretrained=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 492
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2049,
     "status": "ok",
     "timestamp": 1558632652953,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "okY6ytTp7ELd",
    "outputId": "0e1613f8-e6d0-437d-a991-3746895d75a1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AlexNet(\n",
      "  (features): Sequential(\n",
      "    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
      "    (1): ReLU(inplace)\n",
      "    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (4): ReLU(inplace)\n",
      "    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (7): ReLU(inplace)\n",
      "    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (9): ReLU(inplace)\n",
      "    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (11): ReLU(inplace)\n",
      "    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  )\n",
      "  (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
      "  (classifier): Sequential(\n",
      "    (0): Dropout(p=0.5)\n",
      "    (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
      "    (2): ReLU(inplace)\n",
      "    (3): Dropout(p=0.5)\n",
      "    (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
      "    (5): ReLU(inplace)\n",
      "    (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
      "  )\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "#structure of the alexnet\n",
    "print(alexnet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "WT_VW8v8CR7V"
   },
   "outputs": [],
   "source": [
    "def plot_filters_single_channel_big(t):\n",
    "    \n",
    "    #setting the rows and columns\n",
    "    nrows = t.shape[0]*t.shape[2]\n",
    "    ncols = t.shape[1]*t.shape[3]\n",
    "    \n",
    "    \n",
    "    npimg = np.array(t.numpy(), np.float32)\n",
    "    npimg = npimg.transpose((0, 2, 1, 3))\n",
    "    npimg = npimg.ravel().reshape(nrows, ncols)\n",
    "    \n",
    "    npimg = npimg.T\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(ncols/10, nrows/200))    \n",
    "    imgplot = sns.heatmap(npimg, xticklabels=False, yticklabels=False, cmap='gray', ax=ax, cbar=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "6BYCjgBYwyAQ"
   },
   "outputs": [],
   "source": [
    "def plot_filters_single_channel(t):\n",
    "    \n",
    "    #kernels depth * number of kernels\n",
    "    nplots = t.shape[0]*t.shape[1]\n",
    "    ncols = 12\n",
    "    \n",
    "    nrows = 1 + nplots//ncols\n",
    "    #convert tensor to numpy image\n",
    "    npimg = np.array(t.numpy(), np.float32)\n",
    "    \n",
    "    count = 0\n",
    "    fig = plt.figure(figsize=(ncols, nrows))\n",
    "    \n",
    "    #looping through all the kernels in each channel\n",
    "    for i in range(t.shape[0]):\n",
    "        for j in range(t.shape[1]):\n",
    "            count += 1\n",
    "            ax1 = fig.add_subplot(nrows, ncols, count)\n",
    "            npimg = np.array(t[i, j].numpy(), np.float32)\n",
    "            npimg = (npimg - np.mean(npimg)) / np.std(npimg)\n",
    "            npimg = np.minimum(1, np.maximum(0, (npimg + 0.5)))\n",
    "            ax1.imshow(npimg)\n",
    "            ax1.set_title(str(i) + ',' + str(j))\n",
    "            ax1.axis('off')\n",
    "            ax1.set_xticklabels([])\n",
    "            ax1.set_yticklabels([])\n",
    "   \n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "qv-nJbDFuNuN"
   },
   "outputs": [],
   "source": [
    "def plot_filters_multi_channel(t):\n",
    "    \n",
    "    #get the number of kernals\n",
    "    num_kernels = t.shape[0]    \n",
    "    \n",
    "    #define number of columns for subplots\n",
    "    num_cols = 12\n",
    "    #rows = num of kernels\n",
    "    num_rows = num_kernels\n",
    "    \n",
    "    #set the figure size\n",
    "    fig = plt.figure(figsize=(num_cols,num_rows))\n",
    "    \n",
    "    #looping through all the kernels\n",
    "    for i in range(t.shape[0]):\n",
    "        ax1 = fig.add_subplot(num_rows,num_cols,i+1)\n",
    "        \n",
    "        #for each kernel, we convert the tensor to numpy \n",
    "        npimg = np.array(t[i].numpy(), np.float32)\n",
    "        #standardize the numpy image\n",
    "        npimg = (npimg - np.mean(npimg)) / np.std(npimg)\n",
    "        npimg = np.minimum(1, np.maximum(0, (npimg + 0.5)))\n",
    "        npimg = npimg.transpose((1, 2, 0))\n",
    "        ax1.imshow(npimg)\n",
    "        ax1.axis('off')\n",
    "        ax1.set_title(str(i))\n",
    "        ax1.set_xticklabels([])\n",
    "        ax1.set_yticklabels([])\n",
    "        \n",
    "    plt.savefig('myimage.png', dpi=100)    \n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "cWmfCalUvzbS"
   },
   "outputs": [],
   "source": [
    "def plot_weights(model, layer_num, single_channel = True, collated = False):\n",
    "  \n",
    "  #extracting the model features at the particular layer number\n",
    "  layer = model.features[layer_num]\n",
    "  \n",
    "  #checking whether the layer is convolution layer or not \n",
    "  if isinstance(layer, nn.Conv2d):\n",
    "    #getting the weight tensor data\n",
    "    weight_tensor = model.features[layer_num].weight.data\n",
    "    \n",
    "    if single_channel:\n",
    "      if collated:\n",
    "        plot_filters_single_channel_big(weight_tensor)\n",
    "      else:\n",
    "        plot_filters_single_channel(weight_tensor)\n",
    "        \n",
    "    else:\n",
    "      if weight_tensor.shape[1] == 3:\n",
    "        plot_filters_multi_channel(weight_tensor)\n",
    "      else:\n",
    "        print(\"Can only plot weights with three channels with single channel = False\")\n",
    "        \n",
    "  else:\n",
    "    print(\"Can only visualize layers which are convolutional\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 451
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 4198,
     "status": "ok",
     "timestamp": 1558634323846,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "oY9qbCOEP3Mn",
    "outputId": "bebd8e35-0abf-4f10-ecbc-8d9c93ed1618"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x4608 with 64 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize weights for alexnet - first conv layer\n",
    "\n",
    "plot_weights(alexnet, 0, single_channel = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1162
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 11365,
     "status": "ok",
     "timestamp": 1558634356311,
     "user": {
      "displayName": "Niranjan Kumar",
      "photoUrl": "https://lh6.googleusercontent.com/-jG7xdAyoAHA/AAAAAAAAAAI/AAAAAAAACC0/kLGvK19ZcEE/s64/photo.jpg",
      "userId": "17478295942378541022"
     },
     "user_tz": -330
    },
    "id": "uQI9jHcP6xfP",
    "outputId": "692d873b-bfda-4a5e-f96c-56ef533707dd"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1224 with 192 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting single channel images\n",
    "\n",
    "plot_weights(alexnet, 0, single_channel = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KfLwcbTOVVgv"
   },
   "outputs": [],
   "source": [
    "#plot for 3rd layer -> 2nd conv layer\n",
    "plot_weights(alexnet, 3, single_channel = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2aXqciCmP5ch"
   },
   "outputs": [],
   "source": [
    " plot_weights(alexnet, 0, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "e2co0L_wUcgq"
   },
   "outputs": [],
   "source": [
    "plot_weights(alexnet, 3, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "s78jt1lyUrPE"
   },
   "outputs": [],
   "source": [
    "plot_weights(alexnet, 6, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1D0hfAosRT5S"
   },
   "outputs": [],
   "source": [
    "#for vgg16\n",
    "\n",
    "plot_weights(model, 0, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "SwPM0-idRn3Q"
   },
   "outputs": [],
   "source": [
    "plot_weights(model, 2, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "16xv9OJ4R-MQ"
   },
   "outputs": [],
   "source": [
    "plot_weights(model, 5, single_channel = True, collated = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "NSor2Z4r2nHA"
   },
   "outputs": [],
   "source": [
    "plot_weights(model, 0, single_channel = False, collated = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "_bD1sDup2sfc"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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