From db4ff2172a492021aa0b00b218617533258bfd7c Mon Sep 17 00:00:00 2001
From: Vitaliy Lyudvichenko <ludv1x@yandex.ru>
Date: Sat, 25 Jul 2015 22:26:29 +0300
Subject: [PATCH] Updated classification example

---
 modules/dnn/include/opencv2/dnn/blob.hpp      |    2 +-
 modules/dnn/include/opencv2/dnn/dict.hpp      |    2 +-
 modules/dnn/samples/bvlc_alexnet.prototxt     |  281 -----
 ...lexnet.cpp => classify_with_googlenet.cpp} |   27 +-
 modules/dnn/samples/space_shuttle.jpg         |  Bin 0 -> 27598 bytes
 modules/dnn/samples/synset_words.txt          | 1000 +++++++++++++++++
 modules/dnn/scripts/download_model.py         |   18 +-
 modules/dnn/src/caffe_importer.cpp            |    6 +-
 modules/dnn/src/dnn.cpp                       |    6 +-
 modules/dnn/src/layers/concat_layer.cpp       |    2 +-
 modules/dnn/src/layers/convolution_layer.cpp  |    2 +-
 modules/dnn/src/layers/elementwise_layers.cpp |    2 +-
 modules/dnn/src/layers/reshape_layer.cpp      |    4 +-
 modules/dnn/src/layers/slice_layer.cpp        |    2 +-
 modules/dnn/test/cnpy.cpp                     |   23 +-
 modules/dnn/test/cnpy.h                       |   12 +-
 modules/dnn/test/test_layers.cpp              |    2 +-
 17 files changed, 1053 insertions(+), 338 deletions(-)
 delete mode 100644 modules/dnn/samples/bvlc_alexnet.prototxt
 rename modules/dnn/samples/{alexnet.cpp => classify_with_googlenet.cpp} (70%)
 create mode 100644 modules/dnn/samples/space_shuttle.jpg
 create mode 100644 modules/dnn/samples/synset_words.txt

diff --git a/modules/dnn/include/opencv2/dnn/blob.hpp b/modules/dnn/include/opencv2/dnn/blob.hpp
index 4a4a70597..d830f3c78 100644
--- a/modules/dnn/include/opencv2/dnn/blob.hpp
+++ b/modules/dnn/include/opencv2/dnn/blob.hpp
@@ -83,7 +83,7 @@ namespace dnn
         @note Unlike ::xsize, if \p axis points to non-existing dimension then an error will be generated.
         */
         int size(int axis) const;
-        
+
         /** @brief returns number of elements
         @param startAxis starting axis (inverse indexing can be used)
         @param endAxis ending (excluded) axis
diff --git a/modules/dnn/include/opencv2/dnn/dict.hpp b/modules/dnn/include/opencv2/dnn/dict.hpp
index 3a58d990d..bdfe5e9ba 100644
--- a/modules/dnn/include/opencv2/dnn/dict.hpp
+++ b/modules/dnn/include/opencv2/dnn/dict.hpp
@@ -16,7 +16,7 @@ struct DictValue
     DictValue(unsigned p)       : type(Param::INT), pi(new AutoBuffer<int64,1>) { (*pi)[0] = p; }
     DictValue(double p)         : type(Param::REAL), pd(new AutoBuffer<double,1>) { (*pd)[0] = p; }
     DictValue(const String &p)  : type(Param::STRING), ps(new AutoBuffer<String,1>) { (*ps)[0] = p; }
-    
+
     template<typename TypeIter>
     static DictValue arrayInt(TypeIter begin, int size);
     template<typename TypeIter>
diff --git a/modules/dnn/samples/bvlc_alexnet.prototxt b/modules/dnn/samples/bvlc_alexnet.prototxt
deleted file mode 100644
index 83424f374..000000000
--- a/modules/dnn/samples/bvlc_alexnet.prototxt
+++ /dev/null
@@ -1,281 +0,0 @@
-name: "AlexNet"
-input: "data"
-input_dim: 10
-input_dim: 3
-input_dim: 227
-input_dim: 227
-
-layer {
-  name: "conv1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 96
-    kernel_size: 11
-    stride: 4
-  }
-}
-layer {
-  name: "relu1"
-  type: "ReLU"
-  bottom: "conv1"
-  top: "conv1"
-}
-layer {
-  name: "norm1"
-  type: "LRN"
-  bottom: "conv1"
-  top: "norm1"
-  lrn_param {
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-}
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "norm1"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 256
-    pad: 2
-    kernel_size: 5
-    group: 2
-  }
-}
-layer {
-  name: "relu2"
-  type: "ReLU"
-  bottom: "conv2"
-  top: "conv2"
-}
-layer {
-  name: "norm2"
-  type: "LRN"
-  bottom: "conv2"
-  top: "norm2"
-  lrn_param {
-    local_size: 5
-    alpha: 0.0001
-    beta: 0.75
-  }
-}
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "norm2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 384
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu3"
-  type: "ReLU"
-  bottom: "conv3"
-  top: "conv3"
-}
-
-layer {
-  name: "conv4"
-  type: "Convolution"
-  bottom: "conv3"
-  top: "conv4"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 384
-    pad: 1
-    kernel_size: 3
-    group: 2
-  }
-}
-layer {
-  name: "relu4"
-  type: "ReLU"
-  bottom: "conv4"
-  top: "conv4"
-}
-
-layer {
-  name: "conv5"
-  type: "Convolution"
-  bottom: "conv4"
-  top: "conv5"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  convolution_param {
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    group: 2
-  }
-}
-layer {
-  name: "relu5"
-  type: "ReLU"
-  bottom: "conv5"
-  top: "conv5"
-}
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5"
-  top: "pool5"
-  pooling_param {
-    pool: MAX
-    kernel_size: 3
-    stride: 2
-  }
-}
-layer {
-  name: "fc6"
-  type: "InnerProduct"
-  bottom: "pool5"
-  top: "fc6"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-layer {
-  name: "drop6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc61"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc7"
-  type: "InnerProduct"
-  bottom: "fc61"
-  top: "fc7"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-layer {
-  name: "drop7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc71"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc8"
-  type: "InnerProduct"
-  bottom: "fc71"
-  top: "fc8"
-  param {
-    lr_mult: 1
-    decay_mult: 1
-  }
-  param {
-    lr_mult: 2
-    decay_mult: 0
-  }
-  inner_product_param {
-    num_output: 1000
-  }
-}
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "fc8"
-  top: "prob"
-}
diff --git a/modules/dnn/samples/alexnet.cpp b/modules/dnn/samples/classify_with_googlenet.cpp
similarity index 70%
rename from modules/dnn/samples/alexnet.cpp
rename to modules/dnn/samples/classify_with_googlenet.cpp
index 1b55de253..9915f5a79 100644
--- a/modules/dnn/samples/alexnet.cpp
+++ b/modules/dnn/samples/classify_with_googlenet.cpp
@@ -25,53 +25,52 @@ std::vector<String> CLASES_NAMES;
 
 void initClassesNames()
 {
-    std::ifstream fp("ILSVRC2012_synsets.txt");
+    std::ifstream fp("synset_words.txt");
     CV_Assert(fp.is_open());
 
     std::string name;
     while (!fp.eof())
     {
         std::getline(fp, name);
-        CLASES_NAMES.push_back(name);
+        if (name.length())
+            CLASES_NAMES.push_back( name.substr(name.find(' ')+1) );
     }
 
-    CV_Assert(CLASES_NAMES.size() == 1000);
-
     fp.close();
 }
 
 
-int main(void)
+int main(int argc, char **argv)
 {
     Net net;
     {
-        Ptr<Importer> importer = createCaffeImporter("bvlc_alexnet.prototxt", "bvlc_alexnet.caffemodel");
+        Ptr<Importer> importer = createCaffeImporter("bvlc_googlenet.prototxt", "bvlc_googlenet.caffemodel");
         importer->populateNet(net);
     }
 
-    Mat img = imread("zebra.jpg");
+    String filename = (argc > 1) ? argv[1] : "space_shuttle.jpg";
+
+    Mat img = imread(filename);
     CV_Assert(!img.empty());
     cvtColor(img, img, COLOR_BGR2RGB);
-    img.convertTo(img, CV_32F);
     resize(img, img, Size(227, 227));
-    subtract(img, cv::mean(img), img);
     Blob imgBlob(img);
 
-    net.setBlob("data", imgBlob);
+    net.setBlob(".data", imgBlob);
     net.forward();
 
-    Blob probBlob = net.getBlob("prob");
-    ClassProb bc = getMaxClass(probBlob);
+    Blob prob = net.getBlob("prob");
+    ClassProb bc = getMaxClass(prob);
 
     initClassesNames();
     std::string className = (bc.first < (int)CLASES_NAMES.size()) ? CLASES_NAMES[bc.first] : "unnamed";
 
     std::cout << "Best class:";
     std::cout << " #" << bc.first;
-    std::cout << " (from " << probBlob.total(1) << ")";
+    std::cout << " (from " << prob.total(1) << ")";
     std::cout << " \"" + className << "\"";
     std::cout <<  std::endl;
     std::cout << "Prob: " << bc.second * 100 << "%" << std::endl;
 
     return 0;
-}
\ No newline at end of file
+}
diff --git a/modules/dnn/samples/space_shuttle.jpg b/modules/dnn/samples/space_shuttle.jpg
new file mode 100644
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diff --git a/modules/dnn/samples/synset_words.txt b/modules/dnn/samples/synset_words.txt
new file mode 100644
index 000000000..a9e8c7f50
--- /dev/null
+++ b/modules/dnn/samples/synset_words.txt
@@ -0,0 +1,1000 @@
+n01440764 tench, Tinca tinca
+n01443537 goldfish, Carassius auratus
+n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
+n01491361 tiger shark, Galeocerdo cuvieri
+n01494475 hammerhead, hammerhead shark
+n01496331 electric ray, crampfish, numbfish, torpedo
+n01498041 stingray
+n01514668 cock
+n01514859 hen
+n01518878 ostrich, Struthio camelus
+n01530575 brambling, Fringilla montifringilla
+n01531178 goldfinch, Carduelis carduelis
+n01532829 house finch, linnet, Carpodacus mexicanus
+n01534433 junco, snowbird
+n01537544 indigo bunting, indigo finch, indigo bird, Passerina cyanea
+n01558993 robin, American robin, Turdus migratorius
+n01560419 bulbul
+n01580077 jay
+n01582220 magpie
+n01592084 chickadee
+n01601694 water ouzel, dipper
+n01608432 kite
+n01614925 bald eagle, American eagle, Haliaeetus leucocephalus
+n01616318 vulture
+n01622779 great grey owl, great gray owl, Strix nebulosa
+n01629819 European fire salamander, Salamandra salamandra
+n01630670 common newt, Triturus vulgaris
+n01631663 eft
+n01632458 spotted salamander, Ambystoma maculatum
+n01632777 axolotl, mud puppy, Ambystoma mexicanum
+n01641577 bullfrog, Rana catesbeiana
+n01644373 tree frog, tree-frog
+n01644900 tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui
+n01664065 loggerhead, loggerhead turtle, Caretta caretta
+n01665541 leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea
+n01667114 mud turtle
+n01667778 terrapin
+n01669191 box turtle, box tortoise
+n01675722 banded gecko
+n01677366 common iguana, iguana, Iguana iguana
+n01682714 American chameleon, anole, Anolis carolinensis
+n01685808 whiptail, whiptail lizard
+n01687978 agama
+n01688243 frilled lizard, Chlamydosaurus kingi
+n01689811 alligator lizard
+n01692333 Gila monster, Heloderma suspectum
+n01693334 green lizard, Lacerta viridis
+n01694178 African chameleon, Chamaeleo chamaeleon
+n01695060 Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis
+n01697457 African crocodile, Nile crocodile, Crocodylus niloticus
+n01698640 American alligator, Alligator mississipiensis
+n01704323 triceratops
+n01728572 thunder snake, worm snake, Carphophis amoenus
+n01728920 ringneck snake, ring-necked snake, ring snake
+n01729322 hognose snake, puff adder, sand viper
+n01729977 green snake, grass snake
+n01734418 king snake, kingsnake
+n01735189 garter snake, grass snake
+n01737021 water snake
+n01739381 vine snake
+n01740131 night snake, Hypsiglena torquata
+n01742172 boa constrictor, Constrictor constrictor
+n01744401 rock python, rock snake, Python sebae
+n01748264 Indian cobra, Naja naja
+n01749939 green mamba
+n01751748 sea snake
+n01753488 horned viper, cerastes, sand viper, horned asp, Cerastes cornutus
+n01755581 diamondback, diamondback rattlesnake, Crotalus adamanteus
+n01756291 sidewinder, horned rattlesnake, Crotalus cerastes
+n01768244 trilobite
+n01770081 harvestman, daddy longlegs, Phalangium opilio
+n01770393 scorpion
+n01773157 black and gold garden spider, Argiope aurantia
+n01773549 barn spider, Araneus cavaticus
+n01773797 garden spider, Aranea diademata
+n01774384 black widow, Latrodectus mactans
+n01774750 tarantula
+n01775062 wolf spider, hunting spider
+n01776313 tick
+n01784675 centipede
+n01795545 black grouse
+n01796340 ptarmigan
+n01797886 ruffed grouse, partridge, Bonasa umbellus
+n01798484 prairie chicken, prairie grouse, prairie fowl
+n01806143 peacock
+n01806567 quail
+n01807496 partridge
+n01817953 African grey, African gray, Psittacus erithacus
+n01818515 macaw
+n01819313 sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita
+n01820546 lorikeet
+n01824575 coucal
+n01828970 bee eater
+n01829413 hornbill
+n01833805 hummingbird
+n01843065 jacamar
+n01843383 toucan
+n01847000 drake
+n01855032 red-breasted merganser, Mergus serrator
+n01855672 goose
+n01860187 black swan, Cygnus atratus
+n01871265 tusker
+n01872401 echidna, spiny anteater, anteater
+n01873310 platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus
+n01877812 wallaby, brush kangaroo
+n01882714 koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus
+n01883070 wombat
+n01910747 jellyfish
+n01914609 sea anemone, anemone
+n01917289 brain coral
+n01924916 flatworm, platyhelminth
+n01930112 nematode, nematode worm, roundworm
+n01943899 conch
+n01944390 snail
+n01945685 slug
+n01950731 sea slug, nudibranch
+n01955084 chiton, coat-of-mail shell, sea cradle, polyplacophore
+n01968897 chambered nautilus, pearly nautilus, nautilus
+n01978287 Dungeness crab, Cancer magister
+n01978455 rock crab, Cancer irroratus
+n01980166 fiddler crab
+n01981276 king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica
+n01983481 American lobster, Northern lobster, Maine lobster, Homarus americanus
+n01984695 spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish
+n01985128 crayfish, crawfish, crawdad, crawdaddy
+n01986214 hermit crab
+n01990800 isopod
+n02002556 white stork, Ciconia ciconia
+n02002724 black stork, Ciconia nigra
+n02006656 spoonbill
+n02007558 flamingo
+n02009229 little blue heron, Egretta caerulea
+n02009912 American egret, great white heron, Egretta albus
+n02011460 bittern
+n02012849 crane
+n02013706 limpkin, Aramus pictus
+n02017213 European gallinule, Porphyrio porphyrio
+n02018207 American coot, marsh hen, mud hen, water hen, Fulica americana
+n02018795 bustard
+n02025239 ruddy turnstone, Arenaria interpres
+n02027492 red-backed sandpiper, dunlin, Erolia alpina
+n02028035 redshank, Tringa totanus
+n02033041 dowitcher
+n02037110 oystercatcher, oyster catcher
+n02051845 pelican
+n02056570 king penguin, Aptenodytes patagonica
+n02058221 albatross, mollymawk
+n02066245 grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus
+n02071294 killer whale, killer, orca, grampus, sea wolf, Orcinus orca
+n02074367 dugong, Dugong dugon
+n02077923 sea lion
+n02085620 Chihuahua
+n02085782 Japanese spaniel
+n02085936 Maltese dog, Maltese terrier, Maltese
+n02086079 Pekinese, Pekingese, Peke
+n02086240 Shih-Tzu
+n02086646 Blenheim spaniel
+n02086910 papillon
+n02087046 toy terrier
+n02087394 Rhodesian ridgeback
+n02088094 Afghan hound, Afghan
+n02088238 basset, basset hound
+n02088364 beagle
+n02088466 bloodhound, sleuthhound
+n02088632 bluetick
+n02089078 black-and-tan coonhound
+n02089867 Walker hound, Walker foxhound
+n02089973 English foxhound
+n02090379 redbone
+n02090622 borzoi, Russian wolfhound
+n02090721 Irish wolfhound
+n02091032 Italian greyhound
+n02091134 whippet
+n02091244 Ibizan hound, Ibizan Podenco
+n02091467 Norwegian elkhound, elkhound
+n02091635 otterhound, otter hound
+n02091831 Saluki, gazelle hound
+n02092002 Scottish deerhound, deerhound
+n02092339 Weimaraner
+n02093256 Staffordshire bullterrier, Staffordshire bull terrier
+n02093428 American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier
+n02093647 Bedlington terrier
+n02093754 Border terrier
+n02093859 Kerry blue terrier
+n02093991 Irish terrier
+n02094114 Norfolk terrier
+n02094258 Norwich terrier
+n02094433 Yorkshire terrier
+n02095314 wire-haired fox terrier
+n02095570 Lakeland terrier
+n02095889 Sealyham terrier, Sealyham
+n02096051 Airedale, Airedale terrier
+n02096177 cairn, cairn terrier
+n02096294 Australian terrier
+n02096437 Dandie Dinmont, Dandie Dinmont terrier
+n02096585 Boston bull, Boston terrier
+n02097047 miniature schnauzer
+n02097130 giant schnauzer
+n02097209 standard schnauzer
+n02097298 Scotch terrier, Scottish terrier, Scottie
+n02097474 Tibetan terrier, chrysanthemum dog
+n02097658 silky terrier, Sydney silky
+n02098105 soft-coated wheaten terrier
+n02098286 West Highland white terrier
+n02098413 Lhasa, Lhasa apso
+n02099267 flat-coated retriever
+n02099429 curly-coated retriever
+n02099601 golden retriever
+n02099712 Labrador retriever
+n02099849 Chesapeake Bay retriever
+n02100236 German short-haired pointer
+n02100583 vizsla, Hungarian pointer
+n02100735 English setter
+n02100877 Irish setter, red setter
+n02101006 Gordon setter
+n02101388 Brittany spaniel
+n02101556 clumber, clumber spaniel
+n02102040 English springer, English springer spaniel
+n02102177 Welsh springer spaniel
+n02102318 cocker spaniel, English cocker spaniel, cocker
+n02102480 Sussex spaniel
+n02102973 Irish water spaniel
+n02104029 kuvasz
+n02104365 schipperke
+n02105056 groenendael
+n02105162 malinois
+n02105251 briard
+n02105412 kelpie
+n02105505 komondor
+n02105641 Old English sheepdog, bobtail
+n02105855 Shetland sheepdog, Shetland sheep dog, Shetland
+n02106030 collie
+n02106166 Border collie
+n02106382 Bouvier des Flandres, Bouviers des Flandres
+n02106550 Rottweiler
+n02106662 German shepherd, German shepherd dog, German police dog, alsatian
+n02107142 Doberman, Doberman pinscher
+n02107312 miniature pinscher
+n02107574 Greater Swiss Mountain dog
+n02107683 Bernese mountain dog
+n02107908 Appenzeller
+n02108000 EntleBucher
+n02108089 boxer
+n02108422 bull mastiff
+n02108551 Tibetan mastiff
+n02108915 French bulldog
+n02109047 Great Dane
+n02109525 Saint Bernard, St Bernard
+n02109961 Eskimo dog, husky
+n02110063 malamute, malemute, Alaskan malamute
+n02110185 Siberian husky
+n02110341 dalmatian, coach dog, carriage dog
+n02110627 affenpinscher, monkey pinscher, monkey dog
+n02110806 basenji
+n02110958 pug, pug-dog
+n02111129 Leonberg
+n02111277 Newfoundland, Newfoundland dog
+n02111500 Great Pyrenees
+n02111889 Samoyed, Samoyede
+n02112018 Pomeranian
+n02112137 chow, chow chow
+n02112350 keeshond
+n02112706 Brabancon griffon
+n02113023 Pembroke, Pembroke Welsh corgi
+n02113186 Cardigan, Cardigan Welsh corgi
+n02113624 toy poodle
+n02113712 miniature poodle
+n02113799 standard poodle
+n02113978 Mexican hairless
+n02114367 timber wolf, grey wolf, gray wolf, Canis lupus
+n02114548 white wolf, Arctic wolf, Canis lupus tundrarum
+n02114712 red wolf, maned wolf, Canis rufus, Canis niger
+n02114855 coyote, prairie wolf, brush wolf, Canis latrans
+n02115641 dingo, warrigal, warragal, Canis dingo
+n02115913 dhole, Cuon alpinus
+n02116738 African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus
+n02117135 hyena, hyaena
+n02119022 red fox, Vulpes vulpes
+n02119789 kit fox, Vulpes macrotis
+n02120079 Arctic fox, white fox, Alopex lagopus
+n02120505 grey fox, gray fox, Urocyon cinereoargenteus
+n02123045 tabby, tabby cat
+n02123159 tiger cat
+n02123394 Persian cat
+n02123597 Siamese cat, Siamese
+n02124075 Egyptian cat
+n02125311 cougar, puma, catamount, mountain lion, painter, panther, Felis concolor
+n02127052 lynx, catamount
+n02128385 leopard, Panthera pardus
+n02128757 snow leopard, ounce, Panthera uncia
+n02128925 jaguar, panther, Panthera onca, Felis onca
+n02129165 lion, king of beasts, Panthera leo
+n02129604 tiger, Panthera tigris
+n02130308 cheetah, chetah, Acinonyx jubatus
+n02132136 brown bear, bruin, Ursus arctos
+n02133161 American black bear, black bear, Ursus americanus, Euarctos americanus
+n02134084 ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus
+n02134418 sloth bear, Melursus ursinus, Ursus ursinus
+n02137549 mongoose
+n02138441 meerkat, mierkat
+n02165105 tiger beetle
+n02165456 ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle
+n02167151 ground beetle, carabid beetle
+n02168699 long-horned beetle, longicorn, longicorn beetle
+n02169497 leaf beetle, chrysomelid
+n02172182 dung beetle
+n02174001 rhinoceros beetle
+n02177972 weevil
+n02190166 fly
+n02206856 bee
+n02219486 ant, emmet, pismire
+n02226429 grasshopper, hopper
+n02229544 cricket
+n02231487 walking stick, walkingstick, stick insect
+n02233338 cockroach, roach
+n02236044 mantis, mantid
+n02256656 cicada, cicala
+n02259212 leafhopper
+n02264363 lacewing, lacewing fly
+n02268443 dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk
+n02268853 damselfly
+n02276258 admiral
+n02277742 ringlet, ringlet butterfly
+n02279972 monarch, monarch butterfly, milkweed butterfly, Danaus plexippus
+n02280649 cabbage butterfly
+n02281406 sulphur butterfly, sulfur butterfly
+n02281787 lycaenid, lycaenid butterfly
+n02317335 starfish, sea star
+n02319095 sea urchin
+n02321529 sea cucumber, holothurian
+n02325366 wood rabbit, cottontail, cottontail rabbit
+n02326432 hare
+n02328150 Angora, Angora rabbit
+n02342885 hamster
+n02346627 porcupine, hedgehog
+n02356798 fox squirrel, eastern fox squirrel, Sciurus niger
+n02361337 marmot
+n02363005 beaver
+n02364673 guinea pig, Cavia cobaya
+n02389026 sorrel
+n02391049 zebra
+n02395406 hog, pig, grunter, squealer, Sus scrofa
+n02396427 wild boar, boar, Sus scrofa
+n02397096 warthog
+n02398521 hippopotamus, hippo, river horse, Hippopotamus amphibius
+n02403003 ox
+n02408429 water buffalo, water ox, Asiatic buffalo, Bubalus bubalis
+n02410509 bison
+n02412080 ram, tup
+n02415577 bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis
+n02417914 ibex, Capra ibex
+n02422106 hartebeest
+n02422699 impala, Aepyceros melampus
+n02423022 gazelle
+n02437312 Arabian camel, dromedary, Camelus dromedarius
+n02437616 llama
+n02441942 weasel
+n02442845 mink
+n02443114 polecat, fitch, foulmart, foumart, Mustela putorius
+n02443484 black-footed ferret, ferret, Mustela nigripes
+n02444819 otter
+n02445715 skunk, polecat, wood pussy
+n02447366 badger
+n02454379 armadillo
+n02457408 three-toed sloth, ai, Bradypus tridactylus
+n02480495 orangutan, orang, orangutang, Pongo pygmaeus
+n02480855 gorilla, Gorilla gorilla
+n02481823 chimpanzee, chimp, Pan troglodytes
+n02483362 gibbon, Hylobates lar
+n02483708 siamang, Hylobates syndactylus, Symphalangus syndactylus
+n02484975 guenon, guenon monkey
+n02486261 patas, hussar monkey, Erythrocebus patas
+n02486410 baboon
+n02487347 macaque
+n02488291 langur
+n02488702 colobus, colobus monkey
+n02489166 proboscis monkey, Nasalis larvatus
+n02490219 marmoset
+n02492035 capuchin, ringtail, Cebus capucinus
+n02492660 howler monkey, howler
+n02493509 titi, titi monkey
+n02493793 spider monkey, Ateles geoffroyi
+n02494079 squirrel monkey, Saimiri sciureus
+n02497673 Madagascar cat, ring-tailed lemur, Lemur catta
+n02500267 indri, indris, Indri indri, Indri brevicaudatus
+n02504013 Indian elephant, Elephas maximus
+n02504458 African elephant, Loxodonta africana
+n02509815 lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens
+n02510455 giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca
+n02514041 barracouta, snoek
+n02526121 eel
+n02536864 coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch
+n02606052 rock beauty, Holocanthus tricolor
+n02607072 anemone fish
+n02640242 sturgeon
+n02641379 gar, garfish, garpike, billfish, Lepisosteus osseus
+n02643566 lionfish
+n02655020 puffer, pufferfish, blowfish, globefish
+n02666196 abacus
+n02667093 abaya
+n02669723 academic gown, academic robe, judge's robe
+n02672831 accordion, piano accordion, squeeze box
+n02676566 acoustic guitar
+n02687172 aircraft carrier, carrier, flattop, attack aircraft carrier
+n02690373 airliner
+n02692877 airship, dirigible
+n02699494 altar
+n02701002 ambulance
+n02704792 amphibian, amphibious vehicle
+n02708093 analog clock
+n02727426 apiary, bee house
+n02730930 apron
+n02747177 ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin
+n02749479 assault rifle, assault gun
+n02769748 backpack, back pack, knapsack, packsack, rucksack, haversack
+n02776631 bakery, bakeshop, bakehouse
+n02777292 balance beam, beam
+n02782093 balloon
+n02783161 ballpoint, ballpoint pen, ballpen, Biro
+n02786058 Band Aid
+n02787622 banjo
+n02788148 bannister, banister, balustrade, balusters, handrail
+n02790996 barbell
+n02791124 barber chair
+n02791270 barbershop
+n02793495 barn
+n02794156 barometer
+n02795169 barrel, cask
+n02797295 barrow, garden cart, lawn cart, wheelbarrow
+n02799071 baseball
+n02802426 basketball
+n02804414 bassinet
+n02804610 bassoon
+n02807133 bathing cap, swimming cap
+n02808304 bath towel
+n02808440 bathtub, bathing tub, bath, tub
+n02814533 beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon
+n02814860 beacon, lighthouse, beacon light, pharos
+n02815834 beaker
+n02817516 bearskin, busby, shako
+n02823428 beer bottle
+n02823750 beer glass
+n02825657 bell cote, bell cot
+n02834397 bib
+n02835271 bicycle-built-for-two, tandem bicycle, tandem
+n02837789 bikini, two-piece
+n02840245 binder, ring-binder
+n02841315 binoculars, field glasses, opera glasses
+n02843684 birdhouse
+n02859443 boathouse
+n02860847 bobsled, bobsleigh, bob
+n02865351 bolo tie, bolo, bola tie, bola
+n02869837 bonnet, poke bonnet
+n02870880 bookcase
+n02871525 bookshop, bookstore, bookstall
+n02877765 bottlecap
+n02879718 bow
+n02883205 bow tie, bow-tie, bowtie
+n02892201 brass, memorial tablet, plaque
+n02892767 brassiere, bra, bandeau
+n02894605 breakwater, groin, groyne, mole, bulwark, seawall, jetty
+n02895154 breastplate, aegis, egis
+n02906734 broom
+n02909870 bucket, pail
+n02910353 buckle
+n02916936 bulletproof vest
+n02917067 bullet train, bullet
+n02927161 butcher shop, meat market
+n02930766 cab, hack, taxi, taxicab
+n02939185 caldron, cauldron
+n02948072 candle, taper, wax light
+n02950826 cannon
+n02951358 canoe
+n02951585 can opener, tin opener
+n02963159 cardigan
+n02965783 car mirror
+n02966193 carousel, carrousel, merry-go-round, roundabout, whirligig
+n02966687 carpenter's kit, tool kit
+n02971356 carton
+n02974003 car wheel
+n02977058 cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM
+n02978881 cassette
+n02979186 cassette player
+n02980441 castle
+n02981792 catamaran
+n02988304 CD player
+n02992211 cello, violoncello
+n02992529 cellular telephone, cellular phone, cellphone, cell, mobile phone
+n02999410 chain
+n03000134 chainlink fence
+n03000247 chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour
+n03000684 chain saw, chainsaw
+n03014705 chest
+n03016953 chiffonier, commode
+n03017168 chime, bell, gong
+n03018349 china cabinet, china closet
+n03026506 Christmas stocking
+n03028079 church, church building
+n03032252 cinema, movie theater, movie theatre, movie house, picture palace
+n03041632 cleaver, meat cleaver, chopper
+n03042490 cliff dwelling
+n03045698 cloak
+n03047690 clog, geta, patten, sabot
+n03062245 cocktail shaker
+n03063599 coffee mug
+n03063689 coffeepot
+n03065424 coil, spiral, volute, whorl, helix
+n03075370 combination lock
+n03085013 computer keyboard, keypad
+n03089624 confectionery, confectionary, candy store
+n03095699 container ship, containership, container vessel
+n03100240 convertible
+n03109150 corkscrew, bottle screw
+n03110669 cornet, horn, trumpet, trump
+n03124043 cowboy boot
+n03124170 cowboy hat, ten-gallon hat
+n03125729 cradle
+n03126707 crane
+n03127747 crash helmet
+n03127925 crate
+n03131574 crib, cot
+n03133878 Crock Pot
+n03134739 croquet ball
+n03141823 crutch
+n03146219 cuirass
+n03160309 dam, dike, dyke
+n03179701 desk
+n03180011 desktop computer
+n03187595 dial telephone, dial phone
+n03188531 diaper, nappy, napkin
+n03196217 digital clock
+n03197337 digital watch
+n03201208 dining table, board
+n03207743 dishrag, dishcloth
+n03207941 dishwasher, dish washer, dishwashing machine
+n03208938 disk brake, disc brake
+n03216828 dock, dockage, docking facility
+n03218198 dogsled, dog sled, dog sleigh
+n03220513 dome
+n03223299 doormat, welcome mat
+n03240683 drilling platform, offshore rig
+n03249569 drum, membranophone, tympan
+n03250847 drumstick
+n03255030 dumbbell
+n03259280 Dutch oven
+n03271574 electric fan, blower
+n03272010 electric guitar
+n03272562 electric locomotive
+n03290653 entertainment center
+n03291819 envelope
+n03297495 espresso maker
+n03314780 face powder
+n03325584 feather boa, boa
+n03337140 file, file cabinet, filing cabinet
+n03344393 fireboat
+n03345487 fire engine, fire truck
+n03347037 fire screen, fireguard
+n03355925 flagpole, flagstaff
+n03372029 flute, transverse flute
+n03376595 folding chair
+n03379051 football helmet
+n03384352 forklift
+n03388043 fountain
+n03388183 fountain pen
+n03388549 four-poster
+n03393912 freight car
+n03394916 French horn, horn
+n03400231 frying pan, frypan, skillet
+n03404251 fur coat
+n03417042 garbage truck, dustcart
+n03424325 gasmask, respirator, gas helmet
+n03425413 gas pump, gasoline pump, petrol pump, island dispenser
+n03443371 goblet
+n03444034 go-kart
+n03445777 golf ball
+n03445924 golfcart, golf cart
+n03447447 gondola
+n03447721 gong, tam-tam
+n03450230 gown
+n03452741 grand piano, grand
+n03457902 greenhouse, nursery, glasshouse
+n03459775 grille, radiator grille
+n03461385 grocery store, grocery, food market, market
+n03467068 guillotine
+n03476684 hair slide
+n03476991 hair spray
+n03478589 half track
+n03481172 hammer
+n03482405 hamper
+n03483316 hand blower, blow dryer, blow drier, hair dryer, hair drier
+n03485407 hand-held computer, hand-held microcomputer
+n03485794 handkerchief, hankie, hanky, hankey
+n03492542 hard disc, hard disk, fixed disk
+n03494278 harmonica, mouth organ, harp, mouth harp
+n03495258 harp
+n03496892 harvester, reaper
+n03498962 hatchet
+n03527444 holster
+n03529860 home theater, home theatre
+n03530642 honeycomb
+n03532672 hook, claw
+n03534580 hoopskirt, crinoline
+n03535780 horizontal bar, high bar
+n03538406 horse cart, horse-cart
+n03544143 hourglass
+n03584254 iPod
+n03584829 iron, smoothing iron
+n03590841 jack-o'-lantern
+n03594734 jean, blue jean, denim
+n03594945 jeep, landrover
+n03595614 jersey, T-shirt, tee shirt
+n03598930 jigsaw puzzle
+n03599486 jinrikisha, ricksha, rickshaw
+n03602883 joystick
+n03617480 kimono
+n03623198 knee pad
+n03627232 knot
+n03630383 lab coat, laboratory coat
+n03633091 ladle
+n03637318 lampshade, lamp shade
+n03642806 laptop, laptop computer
+n03649909 lawn mower, mower
+n03657121 lens cap, lens cover
+n03658185 letter opener, paper knife, paperknife
+n03661043 library
+n03662601 lifeboat
+n03666591 lighter, light, igniter, ignitor
+n03670208 limousine, limo
+n03673027 liner, ocean liner
+n03676483 lipstick, lip rouge
+n03680355 Loafer
+n03690938 lotion
+n03691459 loudspeaker, speaker, speaker unit, loudspeaker system, speaker system
+n03692522 loupe, jeweler's loupe
+n03697007 lumbermill, sawmill
+n03706229 magnetic compass
+n03709823 mailbag, postbag
+n03710193 mailbox, letter box
+n03710637 maillot
+n03710721 maillot, tank suit
+n03717622 manhole cover
+n03720891 maraca
+n03721384 marimba, xylophone
+n03724870 mask
+n03729826 matchstick
+n03733131 maypole
+n03733281 maze, labyrinth
+n03733805 measuring cup
+n03742115 medicine chest, medicine cabinet
+n03743016 megalith, megalithic structure
+n03759954 microphone, mike
+n03761084 microwave, microwave oven
+n03763968 military uniform
+n03764736 milk can
+n03769881 minibus
+n03770439 miniskirt, mini
+n03770679 minivan
+n03773504 missile
+n03775071 mitten
+n03775546 mixing bowl
+n03776460 mobile home, manufactured home
+n03777568 Model T
+n03777754 modem
+n03781244 monastery
+n03782006 monitor
+n03785016 moped
+n03786901 mortar
+n03787032 mortarboard
+n03788195 mosque
+n03788365 mosquito net
+n03791053 motor scooter, scooter
+n03792782 mountain bike, all-terrain bike, off-roader
+n03792972 mountain tent
+n03793489 mouse, computer mouse
+n03794056 mousetrap
+n03796401 moving van
+n03803284 muzzle
+n03804744 nail
+n03814639 neck brace
+n03814906 necklace
+n03825788 nipple
+n03832673 notebook, notebook computer
+n03837869 obelisk
+n03838899 oboe, hautboy, hautbois
+n03840681 ocarina, sweet potato
+n03841143 odometer, hodometer, mileometer, milometer
+n03843555 oil filter
+n03854065 organ, pipe organ
+n03857828 oscilloscope, scope, cathode-ray oscilloscope, CRO
+n03866082 overskirt
+n03868242 oxcart
+n03868863 oxygen mask
+n03871628 packet
+n03873416 paddle, boat paddle
+n03874293 paddlewheel, paddle wheel
+n03874599 padlock
+n03876231 paintbrush
+n03877472 pajama, pyjama, pj's, jammies
+n03877845 palace
+n03884397 panpipe, pandean pipe, syrinx
+n03887697 paper towel
+n03888257 parachute, chute
+n03888605 parallel bars, bars
+n03891251 park bench
+n03891332 parking meter
+n03895866 passenger car, coach, carriage
+n03899768 patio, terrace
+n03902125 pay-phone, pay-station
+n03903868 pedestal, plinth, footstall
+n03908618 pencil box, pencil case
+n03908714 pencil sharpener
+n03916031 perfume, essence
+n03920288 Petri dish
+n03924679 photocopier
+n03929660 pick, plectrum, plectron
+n03929855 pickelhaube
+n03930313 picket fence, paling
+n03930630 pickup, pickup truck
+n03933933 pier
+n03935335 piggy bank, penny bank
+n03937543 pill bottle
+n03938244 pillow
+n03942813 ping-pong ball
+n03944341 pinwheel
+n03947888 pirate, pirate ship
+n03950228 pitcher, ewer
+n03954731 plane, carpenter's plane, woodworking plane
+n03956157 planetarium
+n03958227 plastic bag
+n03961711 plate rack
+n03967562 plow, plough
+n03970156 plunger, plumber's helper
+n03976467 Polaroid camera, Polaroid Land camera
+n03976657 pole
+n03977966 police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria
+n03980874 poncho
+n03982430 pool table, billiard table, snooker table
+n03983396 pop bottle, soda bottle
+n03991062 pot, flowerpot
+n03992509 potter's wheel
+n03995372 power drill
+n03998194 prayer rug, prayer mat
+n04004767 printer
+n04005630 prison, prison house
+n04008634 projectile, missile
+n04009552 projector
+n04019541 puck, hockey puck
+n04023962 punching bag, punch bag, punching ball, punchball
+n04026417 purse
+n04033901 quill, quill pen
+n04033995 quilt, comforter, comfort, puff
+n04037443 racer, race car, racing car
+n04039381 racket, racquet
+n04040759 radiator
+n04041544 radio, wireless
+n04044716 radio telescope, radio reflector
+n04049303 rain barrel
+n04065272 recreational vehicle, RV, R.V.
+n04067472 reel
+n04069434 reflex camera
+n04070727 refrigerator, icebox
+n04074963 remote control, remote
+n04081281 restaurant, eating house, eating place, eatery
+n04086273 revolver, six-gun, six-shooter
+n04090263 rifle
+n04099969 rocking chair, rocker
+n04111531 rotisserie
+n04116512 rubber eraser, rubber, pencil eraser
+n04118538 rugby ball
+n04118776 rule, ruler
+n04120489 running shoe
+n04125021 safe
+n04127249 safety pin
+n04131690 saltshaker, salt shaker
+n04133789 sandal
+n04136333 sarong
+n04141076 sax, saxophone
+n04141327 scabbard
+n04141975 scale, weighing machine
+n04146614 school bus
+n04147183 schooner
+n04149813 scoreboard
+n04152593 screen, CRT screen
+n04153751 screw
+n04154565 screwdriver
+n04162706 seat belt, seatbelt
+n04179913 sewing machine
+n04192698 shield, buckler
+n04200800 shoe shop, shoe-shop, shoe store
+n04201297 shoji
+n04204238 shopping basket
+n04204347 shopping cart
+n04208210 shovel
+n04209133 shower cap
+n04209239 shower curtain
+n04228054 ski
+n04229816 ski mask
+n04235860 sleeping bag
+n04238763 slide rule, slipstick
+n04239074 sliding door
+n04243546 slot, one-armed bandit
+n04251144 snorkel
+n04252077 snowmobile
+n04252225 snowplow, snowplough
+n04254120 soap dispenser
+n04254680 soccer ball
+n04254777 sock
+n04258138 solar dish, solar collector, solar furnace
+n04259630 sombrero
+n04263257 soup bowl
+n04264628 space bar
+n04265275 space heater
+n04266014 space shuttle
+n04270147 spatula
+n04273569 speedboat
+n04275548 spider web, spider's web
+n04277352 spindle
+n04285008 sports car, sport car
+n04286575 spotlight, spot
+n04296562 stage
+n04310018 steam locomotive
+n04311004 steel arch bridge
+n04311174 steel drum
+n04317175 stethoscope
+n04325704 stole
+n04326547 stone wall
+n04328186 stopwatch, stop watch
+n04330267 stove
+n04332243 strainer
+n04335435 streetcar, tram, tramcar, trolley, trolley car
+n04336792 stretcher
+n04344873 studio couch, day bed
+n04346328 stupa, tope
+n04347754 submarine, pigboat, sub, U-boat
+n04350905 suit, suit of clothes
+n04355338 sundial
+n04355933 sunglass
+n04356056 sunglasses, dark glasses, shades
+n04357314 sunscreen, sunblock, sun blocker
+n04366367 suspension bridge
+n04367480 swab, swob, mop
+n04370456 sweatshirt
+n04371430 swimming trunks, bathing trunks
+n04371774 swing
+n04372370 switch, electric switch, electrical switch
+n04376876 syringe
+n04380533 table lamp
+n04389033 tank, army tank, armored combat vehicle, armoured combat vehicle
+n04392985 tape player
+n04398044 teapot
+n04399382 teddy, teddy bear
+n04404412 television, television system
+n04409515 tennis ball
+n04417672 thatch, thatched roof
+n04418357 theater curtain, theatre curtain
+n04423845 thimble
+n04428191 thresher, thrasher, threshing machine
+n04429376 throne
+n04435653 tile roof
+n04442312 toaster
+n04443257 tobacco shop, tobacconist shop, tobacconist
+n04447861 toilet seat
+n04456115 torch
+n04458633 totem pole
+n04461696 tow truck, tow car, wrecker
+n04462240 toyshop
+n04465501 tractor
+n04467665 trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi
+n04476259 tray
+n04479046 trench coat
+n04482393 tricycle, trike, velocipede
+n04483307 trimaran
+n04485082 tripod
+n04486054 triumphal arch
+n04487081 trolleybus, trolley coach, trackless trolley
+n04487394 trombone
+n04493381 tub, vat
+n04501370 turnstile
+n04505470 typewriter keyboard
+n04507155 umbrella
+n04509417 unicycle, monocycle
+n04515003 upright, upright piano
+n04517823 vacuum, vacuum cleaner
+n04522168 vase
+n04523525 vault
+n04525038 velvet
+n04525305 vending machine
+n04532106 vestment
+n04532670 viaduct
+n04536866 violin, fiddle
+n04540053 volleyball
+n04542943 waffle iron
+n04548280 wall clock
+n04548362 wallet, billfold, notecase, pocketbook
+n04550184 wardrobe, closet, press
+n04552348 warplane, military plane
+n04553703 washbasin, handbasin, washbowl, lavabo, wash-hand basin
+n04554684 washer, automatic washer, washing machine
+n04557648 water bottle
+n04560804 water jug
+n04562935 water tower
+n04579145 whiskey jug
+n04579432 whistle
+n04584207 wig
+n04589890 window screen
+n04590129 window shade
+n04591157 Windsor tie
+n04591713 wine bottle
+n04592741 wing
+n04596742 wok
+n04597913 wooden spoon
+n04599235 wool, woolen, woollen
+n04604644 worm fence, snake fence, snake-rail fence, Virginia fence
+n04606251 wreck
+n04612504 yawl
+n04613696 yurt
+n06359193 web site, website, internet site, site
+n06596364 comic book
+n06785654 crossword puzzle, crossword
+n06794110 street sign
+n06874185 traffic light, traffic signal, stoplight
+n07248320 book jacket, dust cover, dust jacket, dust wrapper
+n07565083 menu
+n07579787 plate
+n07583066 guacamole
+n07584110 consomme
+n07590611 hot pot, hotpot
+n07613480 trifle
+n07614500 ice cream, icecream
+n07615774 ice lolly, lolly, lollipop, popsicle
+n07684084 French loaf
+n07693725 bagel, beigel
+n07695742 pretzel
+n07697313 cheeseburger
+n07697537 hotdog, hot dog, red hot
+n07711569 mashed potato
+n07714571 head cabbage
+n07714990 broccoli
+n07715103 cauliflower
+n07716358 zucchini, courgette
+n07716906 spaghetti squash
+n07717410 acorn squash
+n07717556 butternut squash
+n07718472 cucumber, cuke
+n07718747 artichoke, globe artichoke
+n07720875 bell pepper
+n07730033 cardoon
+n07734744 mushroom
+n07742313 Granny Smith
+n07745940 strawberry
+n07747607 orange
+n07749582 lemon
+n07753113 fig
+n07753275 pineapple, ananas
+n07753592 banana
+n07754684 jackfruit, jak, jack
+n07760859 custard apple
+n07768694 pomegranate
+n07802026 hay
+n07831146 carbonara
+n07836838 chocolate sauce, chocolate syrup
+n07860988 dough
+n07871810 meat loaf, meatloaf
+n07873807 pizza, pizza pie
+n07875152 potpie
+n07880968 burrito
+n07892512 red wine
+n07920052 espresso
+n07930864 cup
+n07932039 eggnog
+n09193705 alp
+n09229709 bubble
+n09246464 cliff, drop, drop-off
+n09256479 coral reef
+n09288635 geyser
+n09332890 lakeside, lakeshore
+n09399592 promontory, headland, head, foreland
+n09421951 sandbar, sand bar
+n09428293 seashore, coast, seacoast, sea-coast
+n09468604 valley, vale
+n09472597 volcano
+n09835506 ballplayer, baseball player
+n10148035 groom, bridegroom
+n10565667 scuba diver
+n11879895 rapeseed
+n11939491 daisy
+n12057211 yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum
+n12144580 corn
+n12267677 acorn
+n12620546 hip, rose hip, rosehip
+n12768682 buckeye, horse chestnut, conker
+n12985857 coral fungus
+n12998815 agaric
+n13037406 gyromitra
+n13040303 stinkhorn, carrion fungus
+n13044778 earthstar
+n13052670 hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa
+n13054560 bolete
+n13133613 ear, spike, capitulum
+n15075141 toilet tissue, toilet paper, bathroom tissue
diff --git a/modules/dnn/scripts/download_model.py b/modules/dnn/scripts/download_model.py
index 723aae414..d2951f5ea 100644
--- a/modules/dnn/scripts/download_model.py
+++ b/modules/dnn/scripts/download_model.py
@@ -21,15 +21,15 @@ def reporthook(count, block_size, total_size):
     duration = max(1, time.time() - start_time)
     if int(duration) == int(prev_duration):
         return
-    
+
     progress_size = int(count * block_size)
     speed = int(progress_size / (1024 * duration))
     percent = int(count * block_size * 100 / total_size)
-    sys.stdout.write("\r...%d%%, %d MB, %d KB/s, %d seconds passed" % 
+    sys.stdout.write("\r...%d%%, %d MB, %d KB/s, %d seconds passed" %
                      (percent, progress_size / (1024 * 1024), speed, duration))
     sys.stdout.flush()
     prev_duration = duration
-    
+
 
 # Function for checking SHA1.
 def model_checks_out(filename, sha1):
@@ -41,14 +41,14 @@ def model_download(filename, url, sha1):
     if os.path.exists(filename) and model_checks_out(filename, sha1):
         print("Model {} already exists.".format(filename))
         return
-    
+
     # Download and verify model.
     urllib.urlretrieve(url, filename, reporthook)
     print model_checks_out(filename, sha1)
     if not model_checks_out(filename, sha1):
         print("ERROR: model {} did not download correctly!".format(url))
         sys.exit(1)
-    
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(description="Downloading trained model binaries.")
     parser.add_argument("download_list")
@@ -58,22 +58,22 @@ if __name__ == '__main__':
     if not test_dir:
         print "ERROR: OPENCV_TEST_DATA_PATH environment not specified"
         sys.exit(1)
-    
+
     try:
         with open(args.download_list, 'r') as f:
             models_to_download = json.load(f)
     except:
         print "ERROR: Can't pasrse {}".format(args.download_list)
         sys.exit(1)
-        
+
     for model_name in models_to_download:
         model = models_to_download[model_name]
-        
+
         dst_dir = os.path.join(test_dir, os.path.dirname(model['file']))
         dst_file = os.path.join(test_dir, model['file'])
         if not os.path.exists(dst_dir):
             print "ERROR: Can't find module testdata path '{}'".format(dst_dir)
             sys.exit(1)
-            
+
         print "Downloading model '{}' to {} from {} ...".format(model_name, dst_file, model['url'])
         model_download(dst_file, model['url'], model['sha1'])
\ No newline at end of file
diff --git a/modules/dnn/src/caffe_importer.cpp b/modules/dnn/src/caffe_importer.cpp
index 5542b7e03..a91bde284 100644
--- a/modules/dnn/src/caffe_importer.cpp
+++ b/modules/dnn/src/caffe_importer.cpp
@@ -202,7 +202,7 @@ namespace
 
         struct BlobNote
         {
-            BlobNote(const std::string &_name, int _layerId, int _outNum) : 
+            BlobNote(const std::string &_name, int _layerId, int _outNum) :
                 name(_name.c_str()), layerId(_layerId), outNum(_outNum) {}
 
             const char *name;
@@ -237,7 +237,7 @@ namespace
                 extractBinaryLayerParms(layer, layerParams);
 
                 int id = dstNet.addLayer(name, type, layerParams);
-                
+
                 for (int inNum = 0; inNum < layer.bottom_size(); inNum++)
                     addInput(layer.bottom(inNum), id, inNum, dstNet, addedBlobs);
 
@@ -249,7 +249,7 @@ namespace
         void addOutput(const caffe::LayerParameter &layer, int layerId, int outNum, std::vector<BlobNote> &addedBlobs)
         {
             const std::string &name = layer.top(outNum);
-            
+
             bool haveDups = false;
             for (int idx = (int)addedBlobs.size() - 1; idx >= 0; idx--)
             {
diff --git a/modules/dnn/src/dnn.cpp b/modules/dnn/src/dnn.cpp
index 68ec61d01..f0750464f 100644
--- a/modules/dnn/src/dnn.cpp
+++ b/modules/dnn/src/dnn.cpp
@@ -32,7 +32,7 @@ struct LayerPin
 
     LayerPin(int layerId = -1, int outputId = -1)
         : lid(layerId), oid(outputId) {}
-    
+
     bool valid() const
     {
         return (lid >= 0 && oid >= 0);
@@ -104,7 +104,7 @@ private:
 struct Net::Impl
 {
     Impl()
-    {   
+    {
         //allocate fake net input layer
         netInputLayer = Ptr<NetInputLayer>(new NetInputLayer());
         LayerData &inpl = layers.insert( make_pair(0, LayerData()) ).first->second;
@@ -171,7 +171,7 @@ struct Net::Impl
     LayerData& getLayerData(int id)
     {
         MapIdToLayerData::iterator it = layers.find(id);
-        
+
         if (it == layers.end())
             CV_Error(Error::StsError, "Layer with requested id=" + toString(id) + " not found");
 
diff --git a/modules/dnn/src/layers/concat_layer.cpp b/modules/dnn/src/layers/concat_layer.cpp
index 3dc3267be..dfa45a5be 100644
--- a/modules/dnn/src/layers/concat_layer.cpp
+++ b/modules/dnn/src/layers/concat_layer.cpp
@@ -28,7 +28,7 @@ namespace dnn
     void ConcatLayer::allocate(const std::vector<Blob *> &inputs, std::vector<Blob> &outputs)
     {
         CV_Assert(inputs.size() > 0);
-        
+
         int refType = inputs[0]->type();
         BlobShape refShape = inputs[0]->shape();
         CV_Assert(axis < refShape.dims());
diff --git a/modules/dnn/src/layers/convolution_layer.cpp b/modules/dnn/src/layers/convolution_layer.cpp
index f8468ac43..65fa9d43f 100644
--- a/modules/dnn/src/layers/convolution_layer.cpp
+++ b/modules/dnn/src/layers/convolution_layer.cpp
@@ -197,7 +197,7 @@ namespace dnn
                 for (int g = 0; g < group; g++)
                 {
                     Mat dstMat(inpGroupCn, inpH*inpW, decnBlob.type(), decnBlob.ptrRaw(n, g*inpGroupCn));
-                    
+
                     if (is1x1())
                         colMat = dstMat;
 
diff --git a/modules/dnn/src/layers/elementwise_layers.cpp b/modules/dnn/src/layers/elementwise_layers.cpp
index 02e63a23e..7d7869989 100644
--- a/modules/dnn/src/layers/elementwise_layers.cpp
+++ b/modules/dnn/src/layers/elementwise_layers.cpp
@@ -84,7 +84,7 @@ namespace dnn
             return tanh(x);
         }
     };
-    
+
     struct SigmoidFunctor
     {
         SigmoidFunctor(LayerParams&) {}
diff --git a/modules/dnn/src/layers/reshape_layer.cpp b/modules/dnn/src/layers/reshape_layer.cpp
index 2c7ba862d..1a6363746 100644
--- a/modules/dnn/src/layers/reshape_layer.cpp
+++ b/modules/dnn/src/layers/reshape_layer.cpp
@@ -8,7 +8,7 @@ namespace dnn
 
 //TODO: Extend cv::Mat::reshape method
 class ReshapeLayer : public Layer
-{   
+{
 public:
     ReshapeLayer(LayerParams &params);
 
@@ -121,7 +121,7 @@ void ReshapeLayer::computeOutputShape(int startAxis, int endAxis, BlobShape &inp
 Ptr<Layer> createFlattenLayer(LayerParams&)
 {
     LayerParams params;
-    
+
     int shapeDesc[] = {0, -1};
     params.set("dim", DictValue::arrayInt(shapeDesc, 2));
 
diff --git a/modules/dnn/src/layers/slice_layer.cpp b/modules/dnn/src/layers/slice_layer.cpp
index fcd1d1f9d..7be41602c 100644
--- a/modules/dnn/src/layers/slice_layer.cpp
+++ b/modules/dnn/src/layers/slice_layer.cpp
@@ -45,7 +45,7 @@ void SliceLayer::allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &o
     int axis = inpBlob.canonicalAxis(inAxis);
     int axisSize = inpBlob.size(axis);
     BlobShape inpShape = inpBlob.shape();
-    
+
     if (slicePoints.size()) //divide blob with respect to passed parameters
     {
         std::vector<int> outAxisSize;
diff --git a/modules/dnn/test/cnpy.cpp b/modules/dnn/test/cnpy.cpp
index 45abec6a4..bd5aaddd8 100644
--- a/modules/dnn/test/cnpy.cpp
+++ b/modules/dnn/test/cnpy.cpp
@@ -57,9 +57,9 @@ template<> std::vector<char>& cnpy::operator+=(std::vector<char>& lhs, const cha
     return lhs;
 }
 
-void cnpy::parse_npy_header(FILE* fp, unsigned int& word_size, unsigned int*& shape, unsigned int& ndims, bool& fortran_order) {  
+void cnpy::parse_npy_header(FILE* fp, unsigned int& word_size, unsigned int*& shape, unsigned int& ndims, bool& fortran_order) {
     char buffer[256];
-    size_t res = fread(buffer,sizeof(char),11,fp);       
+    size_t res = fread(buffer,sizeof(char),11,fp);
     if(res != 11)
         throw std::runtime_error("parse_npy_header: failed fread");
     std::string header = fgets(buffer,256,fp);
@@ -85,7 +85,7 @@ void cnpy::parse_npy_header(FILE* fp, unsigned int& word_size, unsigned int*& sh
     }
 
     //endian, word size, data type
-    //byte order code | stands for not applicable. 
+    //byte order code | stands for not applicable.
     //not sure when this applies except for byte array
     loc1 = header.find("descr")+9;
     bool littleEndian = (header[loc1] == '<' || header[loc1] == '|' ? true : false);
@@ -134,7 +134,7 @@ cnpy::NpyArray load_the_npy_file(FILE* fp) {
     arr.word_size = word_size;
     arr.shape = std::vector<unsigned int>(shape,shape+ndims);
     delete[] shape;
-    arr.data = new char[size*word_size];    
+    arr.data = new char[size*word_size];
     arr.fortran_order = fortran_order;
     size_t nread = fread(arr.data,word_size,size,fp);
     if(nread != size)
@@ -148,7 +148,7 @@ cnpy::npz_t cnpy::npz_load(std::string fname) {
     if(!fp) printf("npz_load: Error! Unable to open file %s!\n",fname.c_str());
     assert(fp);
 
-    cnpy::npz_t arrays;  
+    cnpy::npz_t arrays;
 
     while(1) {
         std::vector<char> local_header(30);
@@ -166,7 +166,7 @@ cnpy::npz_t cnpy::npz_load(std::string fname) {
         if(vname_res != name_len)
             throw std::runtime_error("npz_load: failed fread");
 
-        //erase the lagging .npy        
+        //erase the lagging .npy
         varname.erase(varname.end()-4,varname.end());
 
         //read in the extra field
@@ -182,7 +182,7 @@ cnpy::npz_t cnpy::npz_load(std::string fname) {
     }
 
     fclose(fp);
-    return arrays;  
+    return arrays;
 }
 
 cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) {
@@ -191,7 +191,7 @@ cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) {
     if(!fp) {
         printf("npz_load: Error! Unable to open file %s!\n",fname.c_str());
         abort();
-    }       
+    }
 
     while(1) {
         std::vector<char> local_header(30);
@@ -205,7 +205,7 @@ cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) {
         //read in the variable name
         unsigned short name_len = *(unsigned short*) &local_header[26];
         std::string vname(name_len,' ');
-        size_t vname_res = fread(&vname[0],sizeof(char),name_len,fp);      
+        size_t vname_res = fread(&vname[0],sizeof(char),name_len,fp);
         if(vname_res != name_len)
             throw std::runtime_error("npz_load: failed fread");
         vname.erase(vname.end()-4,vname.end()); //erase the lagging .npy
@@ -237,7 +237,7 @@ cnpy::NpyArray cnpy::npy_load(std::string fname) {
 
     if(!fp) {
         printf("npy_load: Error! Unable to open file %s!\n",fname.c_str());
-        abort();  
+        abort();
     }
 
     NpyArray arr = load_the_npy_file(fp);
@@ -245,6 +245,3 @@ cnpy::NpyArray cnpy::npy_load(std::string fname) {
     fclose(fp);
     return arr;
 }
-
-
-
diff --git a/modules/dnn/test/cnpy.h b/modules/dnn/test/cnpy.h
index 90006adb9..dfddde7e4 100644
--- a/modules/dnn/test/cnpy.h
+++ b/modules/dnn/test/cnpy.h
@@ -27,7 +27,7 @@ namespace cnpy {
         bool fortran_order;
         void destruct() {delete[] data;}
     };
-    
+
     struct npz_t : public std::map<std::string, NpyArray>
     {
         void destruct()
@@ -49,14 +49,14 @@ namespace cnpy {
     template<typename T> std::vector<char>& operator+=(std::vector<char>& lhs, const T rhs) {
         //write in little endian
         for(char byte = 0; byte < sizeof(T); byte++) {
-            char val = *((char*)&rhs+byte); 
+            char val = *((char*)&rhs+byte);
             lhs.push_back(val);
         }
         return lhs;
     }
 
-    template<> std::vector<char>& operator+=(std::vector<char>& lhs, const std::string rhs); 
-    template<> std::vector<char>& operator+=(std::vector<char>& lhs, const char* rhs); 
+    template<> std::vector<char>& operator+=(std::vector<char>& lhs, const std::string rhs);
+    template<> std::vector<char>& operator+=(std::vector<char>& lhs, const char* rhs);
 
 
     template<typename T> std::string tostring(T i, int = 0, char = ' ') {
@@ -131,7 +131,7 @@ namespace cnpy {
         if(fp) {
             //zip file exists. we need to add a new npy file to it.
             //first read the footer. this gives us the offset and size of the global header
-            //then read and store the global header. 
+            //then read and store the global header.
             //below, we will write the the new data at the start of the global header then append the global header and footer below it
             unsigned int global_header_size;
             parse_zip_footer(fp,nrecs,global_header_size,global_header_offset);
@@ -201,7 +201,7 @@ namespace cnpy {
         footer += (unsigned int) (global_header_offset + nbytes + local_header.size()); //offset of start of global headers, since global header now starts after newly written array
         footer += (unsigned short) 0; //zip file comment length
 
-        //write everything      
+        //write everything
         fwrite(&local_header[0],sizeof(char),local_header.size(),fp);
         fwrite(&npy_header[0],sizeof(char),npy_header.size(),fp);
         fwrite(data,sizeof(T),nels,fp);
diff --git a/modules/dnn/test/test_layers.cpp b/modules/dnn/test/test_layers.cpp
index 9aafc10bd..a2dd72998 100644
--- a/modules/dnn/test/test_layers.cpp
+++ b/modules/dnn/test/test_layers.cpp
@@ -95,7 +95,7 @@ TEST(Layer_Reshape_Split_Slice_Test, Accuracy)
     net.setBlob(".input", input);
     net.forward();
     Blob output = net.getBlob("output");
-    
+
     input.fill(shape, CV_32F, inputMat.data);
     normAssert(input, output);
 }