From 193f9a5a5c04b6c6bbabbdb153132615802fab23 Mon Sep 17 00:00:00 2001
From: Mohamed Amine Ben Ammar <hiddentn@outlook.com>
Date: Thu, 16 Aug 2018 13:29:00 +0100
Subject: [PATCH 1/5] added darknet reference and darknet tiny classifiers

---
 src/ImageClassifier/darknet.js        |  143 ++++
 src/ImageClassifier/index.js          |   26 +-
 src/utils/IMAGENET_CLASSES_DARKNET.js | 1008 +++++++++++++++++++++++++
 3 files changed, 1170 insertions(+), 7 deletions(-)
 create mode 100644 src/ImageClassifier/darknet.js
 create mode 100644 src/utils/IMAGENET_CLASSES_DARKNET.js

diff --git a/src/ImageClassifier/darknet.js b/src/ImageClassifier/darknet.js
new file mode 100644
index 000000000..f0841bdfb
--- /dev/null
+++ b/src/ImageClassifier/darknet.js
@@ -0,0 +1,143 @@
+// Copyright (c) 2018 ml5
+//
+// This software is released under the MIT License.
+// https://opensource.org/licenses/MIT
+
+/* eslint-disable */
+import * as tf from '@tensorflow/tfjs';
+import IMAGENET_CLASSES_DARKNET from '../utils/IMAGENET_CLASSES_DARKNET';
+
+const DEFAULTS = {
+    DARKNET_URL:'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknetreference/model.json',
+    DARKNET_TINY_URL:'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknettiny/model.json',
+    IMAGE_SIZE_DARKNET:256,
+    IMAGE_SIZE_DARKNET_TINY:224,
+}
+
+
+export async function load(version) {
+  if (tf == null) {
+    throw new Error(
+        `Cannot find TensorFlow.js. If you are using a <script> tag, please ` +
+        `also include @tensorflow/tfjs on the page before using this model.`);
+  }
+  if (version !== 'reference' && version !== 'tiny') {
+    throw new Error(`Please select a version : darknet-reference or darknet-tiny`);
+  }
+ 
+  const darknet = new Darknet(version);
+  await darknet.load();
+  return darknet;
+}
+
+export class Darknet {
+ 
+  constructor(version) {
+    this.version = version;
+    switch (this.version) {
+        case 'reference':
+          this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET;
+          break;
+        case 'tiny':
+          this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET_TINY;
+          break;
+
+        default:
+            break;
+    }
+    this.imgSize
+  }
+
+  async load() {
+    switch (this.version) {
+        // might add darknet_448
+        case 'reference':
+          this.model = await tf.loadModel(DEFAULTS.DARKNET_URL);
+          break;
+    
+        case 'tiny':
+          this.model = await tf.loadModel(DEFAULTS.DARKNET_TINY_URL);
+          break;
+        
+        default:
+            break;
+    }
+    
+    // Warmup the model.
+    const result = tf.tidy(() =>this.model.predict(tf.zeros([1, this.imgSize, this.imgSize, 3])));
+    await result.data();
+    result.dispose();
+
+    }
+
+  /**
+   * Classifies an image from the 1000 ImageNet classes returning a map of
+   * the most likely class names to their probability.
+   *
+   * @param img The image to classify. Can be a tensor or a DOM element image,
+   * video, or canvas.
+   * @param topk How many top values to use. Defaults to 3.
+   */
+  async classify(img, topk = 3) {
+    let logits = tf.tidy(()=>{
+        const imgData = this.preProcess(img,this.imgSize);
+        const predictions = this.model.predict(imgData)
+        return tf.softmax(predictions);
+    })
+    const classes = await getTopKClasses(logits, topk);
+    logits.dispose();
+    return classes;
+  }
+
+  preProcess(img, size) {
+    let image;
+    if (!(img instanceof tf.Tensor)) {
+        if (img instanceof HTMLImageElement || img instanceof HTMLVideoElement) {
+            image = tf.fromPixels(img);
+        } else if (typeof img === 'object' && (img.elt instanceof HTMLImageElement || img.elt instanceof HTMLVideoElement)) {
+            image = tf.fromPixels(img.elt); // Handle p5.js image and video.
+        }
+    } else {
+        image = img;
+    }
+    // Normalize the image from [0, 255] to [0, 1].
+    const normalized = image.toFloat().div(tf.scalar(255));
+    let resized = normalized;
+    if (normalized.shape[0] !== size || normalized.shape[1] !== size) {
+        const alignCorners = true;
+        resized = tf.image.resizeBilinear(normalized, [size, size], alignCorners);
+    }
+    // Reshape to a single-element batch so we can pass it to predict.
+    const batched = resized.reshape([1, size, size, 3]);
+    // Scale Stuff
+    // this.scaleX = this.imgHeight / this.inputHeight;
+    // this.scaleY = this.imgWidth / this.inputWidth;
+    return batched;
+}
+}
+
+async function getTopKClasses(logits, topK) {
+  const values = await logits.data();
+  const valuesAndIndices = [];
+  for (let i = 0; i < values.length; i++) {
+    valuesAndIndices.push({value: values[i], index: i});
+  }
+  valuesAndIndices.sort((a, b) => {
+    return b.value - a.value;
+  });
+  const topkValues = new Float32Array(topK);
+  const topkIndices = new Int32Array(topK);
+  for (let i = 0; i < topK; i++) {
+    topkValues[i] = valuesAndIndices[i].value;
+    topkIndices[i] = valuesAndIndices[i].index;
+  }
+
+  const topClassesAndProbs = [];
+  for (let i = 0; i < topkIndices.length; i++) {
+    topClassesAndProbs.push({
+      className: IMAGENET_CLASSES_DARKNET[topkIndices[i]],
+      probability: topkValues[i]
+    });
+  }
+  return topClassesAndProbs;
+}
\ No newline at end of file
diff --git a/src/ImageClassifier/index.js b/src/ImageClassifier/index.js
index 618b5e557..d91e4d78d 100644
--- a/src/ImageClassifier/index.js
+++ b/src/ImageClassifier/index.js
@@ -9,8 +9,10 @@ Image Classifier using pre-trained networks
 
 import * as tf from '@tensorflow/tfjs';
 import * as mobilenet from '@tensorflow-models/mobilenet';
+import * as darknet from './darknet';
 import callCallback from '../utils/callcallback';
 
+
 const DEFAULTS = {
   mobilenet: {
     version: 1,
@@ -23,14 +25,24 @@ class ImageClassifier {
   constructor(modelName, video, options, callback) {
     this.modelName = modelName;
     this.video = video;
-    this.version = options.version || DEFAULTS[this.modelName].version;
-    this.alpha = options.alpha || DEFAULTS[this.modelName].alpha;
-    this.topk = options.topk || DEFAULTS[this.modelName].topk;
     this.model = null;
-    if (this.modelName === 'mobilenet') {
-      this.modelToUse = mobilenet;
-    } else {
-      this.modelToUse = null;
+    switch (this.modelName) {
+      case 'mobilenet':
+        this.modelToUse = mobilenet;
+        this.version = options.version || DEFAULTS.mobilenet.version;
+        this.alpha = options.alpha || DEFAULTS.mobilenet.alpha;
+        this.topk = options.topk || DEFAULTS.mobilenet.topk;
+        break;
+      case 'darknet':
+        this.version = 'reference'; // this a 28mb model
+        this.modelToUse = darknet;
+        break;
+      case 'darknet-tiny':
+        this.version = 'tiny'; // this a 4mb model
+        this.modelToUse = darknet;
+        break;
+      default:
+        this.modelToUse = null;
     }
     // Load the model
     this.ready = callCallback(this.loadModel(), callback);
diff --git a/src/utils/IMAGENET_CLASSES_DARKNET.js b/src/utils/IMAGENET_CLASSES_DARKNET.js
new file mode 100644
index 000000000..2ffbc011c
--- /dev/null
+++ b/src/utils/IMAGENET_CLASSES_DARKNET.js
@@ -0,0 +1,1008 @@
+// Copyright (c) 2018 ml5
+//
+// This software is released under the MIT License.
+// https://opensource.org/licenses/MIT
+/* eslint-disable */
+export default [
+    "kit fox",
+    "English setter",
+    "Siberian husky",
+    "Australian terrier",
+    "English springer",
+    "grey whale",
+    "lesser panda",
+    "Egyptian cat",
+    "ibex",
+    "Persian cat",
+    "cougar",
+    "gazelle",
+    "porcupine",
+    "sea lion",
+    "malamute",
+    "badger",
+    "Great Dane",
+    "Walker hound",
+    "Welsh springer spaniel",
+    "whippet",
+    "Scottish deerhound",
+    "killer whale",
+    "mink",
+    "African elephant",
+    "Weimaraner",
+    "soft-coated wheaten terrier",
+    "Dandie Dinmont",
+    "red wolf",
+    "Old English sheepdog",
+    "jaguar",
+    "otterhound",
+    "bloodhound",
+    "Airedale",
+    "hyena",
+    "meerkat",
+    "giant schnauzer",
+    "titi",
+    "three-toed sloth",
+    "sorrel",
+    "black-footed ferret",
+    "dalmatian",
+    "black-and-tan coonhound",
+    "papillon",
+    "skunk",
+    "Staffordshire bullterrier",
+    "Mexican hairless",
+    "Bouvier des Flandres",
+    "weasel",
+    "miniature poodle",
+    "Cardigan",
+    "malinois",
+    "bighorn",
+    "fox squirrel",
+    "colobus",
+    "tiger cat",
+    "Lhasa",
+    "impala",
+    "coyote",
+    "Yorkshire terrier",
+    "Newfoundland",
+    "brown bear",
+    "red fox",
+    "Norwegian elkhound",
+    "Rottweiler",
+    "hartebeest",
+    "Saluki",
+    "grey fox",
+    "schipperke",
+    "Pekinese",
+    "Brabancon griffon",
+    "West Highland white terrier",
+    "Sealyham terrier",
+    "guenon",
+    "mongoose",
+    "indri",
+    "tiger",
+    "Irish wolfhound",
+    "wild boar",
+    "EntleBucher",
+    "zebra",
+    "ram",
+    "French bulldog",
+    "orangutan",
+    "basenji",
+    "leopard",
+    "Bernese mountain dog",
+    "Maltese dog",
+    "Norfolk terrier",
+    "toy terrier",
+    "vizsla",
+    "cairn",
+    "squirrel monkey",
+    "groenendael",
+    "clumber",
+    "Siamese cat",
+    "chimpanzee",
+    "komondor",
+    "Afghan hound",
+    "Japanese spaniel",
+    "proboscis monkey",
+    "guinea pig",
+    "white wolf",
+    "ice bear",
+    "gorilla",
+    "borzoi",
+    "toy poodle",
+    "Kerry blue terrier",
+    "ox",
+    "Scotch terrier",
+    "Tibetan mastiff",
+    "spider monkey",
+    "Doberman",
+    "Boston bull",
+    "Greater Swiss Mountain dog",
+    "Appenzeller",
+    "Shih-Tzu",
+    "Irish water spaniel",
+    "Pomeranian",
+    "Bedlington terrier",
+    "warthog",
+    "Arabian camel",
+    "siamang",
+    "miniature schnauzer",
+    "collie",
+    "golden retriever",
+    "Irish terrier",
+    "affenpinscher",
+    "Border collie",
+    "hare",
+    "boxer",
+    "silky terrier",
+    "beagle",
+    "Leonberg",
+    "German short-haired pointer",
+    "patas",
+    "dhole",
+    "baboon",
+    "macaque",
+    "Chesapeake Bay retriever",
+    "bull mastiff",
+    "kuvasz",
+    "capuchin",
+    "pug",
+    "curly-coated retriever",
+    "Norwich terrier",
+    "flat-coated retriever",
+    "hog",
+    "keeshond",
+    "Eskimo dog",
+    "Brittany spaniel",
+    "standard poodle",
+    "Lakeland terrier",
+    "snow leopard",
+    "Gordon setter",
+    "dingo",
+    "standard schnauzer",
+    "hamster",
+    "Tibetan terrier",
+    "Arctic fox",
+    "wire-haired fox terrier",
+    "basset",
+    "water buffalo",
+    "American black bear",
+    "Angora",
+    "bison",
+    "howler monkey",
+    "hippopotamus",
+    "chow",
+    "giant panda",
+    "American Staffordshire terrier",
+    "Shetland sheepdog",
+    "Great Pyrenees",
+    "Chihuahua",
+    "tabby",
+    "marmoset",
+    "Labrador retriever",
+    "Saint Bernard",
+    "armadillo",
+    "Samoyed",
+    "bluetick",
+    "redbone",
+    "polecat",
+    "marmot",
+    "kelpie",
+    "gibbon",
+    "llama",
+    "miniature pinscher",
+    "wood rabbit",
+    "Italian greyhound",
+    "lion",
+    "cocker spaniel",
+    "Irish setter",
+    "dugong",
+    "Indian elephant",
+    "beaver",
+    "Sussex spaniel",
+    "Pembroke",
+    "Blenheim spaniel",
+    "Madagascar cat",
+    "Rhodesian ridgeback",
+    "lynx",
+    "African hunting dog",
+    "langur",
+    "Ibizan hound",
+    "timber wolf",
+    "cheetah",
+    "English foxhound",
+    "briard",
+    "sloth bear",
+    "Border terrier",
+    "German shepherd",
+    "otter",
+    "koala",
+    "tusker",
+    "echidna",
+    "wallaby",
+    "platypus",
+    "wombat",
+    "revolver",
+    "umbrella",
+    "schooner",
+    "soccer ball",
+    "accordion",
+    "ant",
+    "starfish",
+    "chambered nautilus",
+    "grand piano",
+    "laptop",
+    "strawberry",
+    "airliner",
+    "warplane",
+    "airship",
+    "balloon",
+    "space shuttle",
+    "fireboat",
+    "gondola",
+    "speedboat",
+    "lifeboat",
+    "canoe",
+    "yawl",
+    "catamaran",
+    "trimaran",
+    "container ship",
+    "liner",
+    "pirate",
+    "aircraft carrier",
+    "submarine",
+    "wreck",
+    "half track",
+    "tank",
+    "missile",
+    "bobsled",
+    "dogsled",
+    "bicycle-built-for-two",
+    "mountain bike",
+    "freight car",
+    "passenger car",
+    "barrow",
+    "shopping cart",
+    "motor scooter",
+    "forklift",
+    "electric locomotive",
+    "steam locomotive",
+    "amphibian",
+    "ambulance",
+    "beach wagon",
+    "cab",
+    "convertible",
+    "jeep",
+    "limousine",
+    "minivan",
+    "Model T",
+    "racer",
+    "sports car",
+    "go-kart",
+    "golfcart",
+    "moped",
+    "snowplow",
+    "fire engine",
+    "garbage truck",
+    "pickup",
+    "tow truck",
+    "trailer truck",
+    "moving van",
+    "police van",
+    "recreational vehicle",
+    "streetcar",
+    "snowmobile",
+    "tractor",
+    "mobile home",
+    "tricycle",
+    "unicycle",
+    "horse cart",
+    "jinrikisha",
+    "oxcart",
+    "bassinet",
+    "cradle",
+    "crib",
+    "four-poster",
+    "bookcase",
+    "china cabinet",
+    "medicine chest",
+    "chiffonier",
+    "table lamp",
+    "file",
+    "park bench",
+    "barber chair",
+    "throne",
+    "folding chair",
+    "rocking chair",
+    "studio couch",
+    "toilet seat",
+    "desk",
+    "pool table",
+    "dining table",
+    "entertainment center",
+    "wardrobe",
+    "Granny Smith",
+    "orange",
+    "lemon",
+    "fig",
+    "pineapple",
+    "banana",
+    "jackfruit",
+    "custard apple",
+    "pomegranate",
+    "acorn",
+    "hip",
+    "ear",
+    "rapeseed",
+    "corn",
+    "buckeye",
+    "organ",
+    "upright",
+    "chime",
+    "drum",
+    "gong",
+    "maraca",
+    "marimba",
+    "steel drum",
+    "banjo",
+    "cello",
+    "violin",
+    "harp",
+    "acoustic guitar",
+    "electric guitar",
+    "cornet",
+    "French horn",
+    "trombone",
+    "harmonica",
+    "ocarina",
+    "panpipe",
+    "bassoon",
+    "oboe",
+    "sax",
+    "flute",
+    "daisy",
+    "yellow lady's slipper",
+    "cliff",
+    "valley",
+    "alp",
+    "volcano",
+    "promontory",
+    "sandbar",
+    "coral reef",
+    "lakeside",
+    "seashore",
+    "geyser",
+    "hatchet",
+    "cleaver",
+    "letter opener",
+    "plane",
+    "power drill",
+    "lawn mower",
+    "hammer",
+    "corkscrew",
+    "can opener",
+    "plunger",
+    "screwdriver",
+    "shovel",
+    "plow",
+    "chain saw",
+    "cock",
+    "hen",
+    "ostrich",
+    "brambling",
+    "goldfinch",
+    "house finch",
+    "junco",
+    "indigo bunting",
+    "robin",
+    "bulbul",
+    "jay",
+    "magpie",
+    "chickadee",
+    "water ouzel",
+    "kite",
+    "bald eagle",
+    "vulture",
+    "great grey owl",
+    "black grouse",
+    "ptarmigan",
+    "ruffed grouse",
+    "prairie chicken",
+    "peacock",
+    "quail",
+    "partridge",
+    "African grey",
+    "macaw",
+    "sulphur-crested cockatoo",
+    "lorikeet",
+    "coucal",
+    "bee eater",
+    "hornbill",
+    "hummingbird",
+    "jacamar",
+    "toucan",
+    "drake",
+    "red-breasted merganser",
+    "goose",
+    "black swan",
+    "white stork",
+    "black stork",
+    "spoonbill",
+    "flamingo",
+    "American egret",
+    "little blue heron",
+    "bittern",
+    "crane",
+    "limpkin",
+    "American coot",
+    "bustard",
+    "ruddy turnstone",
+    "red-backed sandpiper",
+    "redshank",
+    "dowitcher",
+    "oystercatcher",
+    "European gallinule",
+    "pelican",
+    "king penguin",
+    "albatross",
+    "great white shark",
+    "tiger shark",
+    "hammerhead",
+    "electric ray",
+    "stingray",
+    "barracouta",
+    "coho",
+    "tench",
+    "goldfish",
+    "eel",
+    "rock beauty",
+    "anemone fish",
+    "lionfish",
+    "puffer",
+    "sturgeon",
+    "gar",
+    "loggerhead",
+    "leatherback turtle",
+    "mud turtle",
+    "terrapin",
+    "box turtle",
+    "banded gecko",
+    "common iguana",
+    "American chameleon",
+    "whiptail",
+    "agama",
+    "frilled lizard",
+    "alligator lizard",
+    "Gila monster",
+    "green lizard",
+    "African chameleon",
+    "Komodo dragon",
+    "triceratops",
+    "African crocodile",
+    "American alligator",
+    "thunder snake",
+    "ringneck snake",
+    "hognose snake",
+    "green snake",
+    "king snake",
+    "garter snake",
+    "water snake",
+    "vine snake",
+    "night snake",
+    "boa constrictor",
+    "rock python",
+    "Indian cobra",
+    "green mamba",
+    "sea snake",
+    "horned viper",
+    "diamondback",
+    "sidewinder",
+    "European fire salamander",
+    "common newt",
+    "eft",
+    "spotted salamander",
+    "axolotl",
+    "bullfrog",
+    "tree frog",
+    "tailed frog",
+    "whistle",
+    "wing",
+    "paintbrush",
+    "hand blower",
+    "oxygen mask",
+    "snorkel",
+    "loudspeaker",
+    "microphone",
+    "screen",
+    "mouse",
+    "electric fan",
+    "oil filter",
+    "strainer",
+    "space heater",
+    "stove",
+    "guillotine",
+    "barometer",
+    "rule",
+    "odometer",
+    "scale",
+    "analog clock",
+    "digital clock",
+    "wall clock",
+    "hourglass",
+    "sundial",
+    "parking meter",
+    "stopwatch",
+    "digital watch",
+    "stethoscope",
+    "syringe",
+    "magnetic compass",
+    "binoculars",
+    "projector",
+    "sunglasses",
+    "loupe",
+    "radio telescope",
+    "bow",
+    "cannon",
+    "assault rifle",
+    "rifle",
+    "projectile",
+    "computer keyboard",
+    "typewriter keyboard",
+    "crane",
+    "lighter",
+    "abacus",
+    "cash machine",
+    "slide rule",
+    "desktop computer",
+    "hand-held computer",
+    "notebook",
+    "web site",
+    "harvester",
+    "thresher",
+    "printer",
+    "slot",
+    "vending machine",
+    "sewing machine",
+    "joystick",
+    "switch",
+    "hook",
+    "car wheel",
+    "paddlewheel",
+    "pinwheel",
+    "potter's wheel",
+    "gas pump",
+    "carousel",
+    "swing",
+    "reel",
+    "radiator",
+    "puck",
+    "hard disc",
+    "sunglass",
+    "pick",
+    "car mirror",
+    "solar dish",
+    "remote control",
+    "disk brake",
+    "buckle",
+    "hair slide",
+    "knot",
+    "combination lock",
+    "padlock",
+    "nail",
+    "safety pin",
+    "screw",
+    "muzzle",
+    "seat belt",
+    "ski",
+    "candle",
+    "jack-o'-lantern",
+    "spotlight",
+    "torch",
+    "neck brace",
+    "pier",
+    "tripod",
+    "maypole",
+    "mousetrap",
+    "spider web",
+    "trilobite",
+    "harvestman",
+    "scorpion",
+    "black and gold garden spider",
+    "barn spider",
+    "garden spider",
+    "black widow",
+    "tarantula",
+    "wolf spider",
+    "tick",
+    "centipede",
+    "isopod",
+    "Dungeness crab",
+    "rock crab",
+    "fiddler crab",
+    "king crab",
+    "American lobster",
+    "spiny lobster",
+    "crayfish",
+    "hermit crab",
+    "tiger beetle",
+    "ladybug",
+    "ground beetle",
+    "long-horned beetle",
+    "leaf beetle",
+    "dung beetle",
+    "rhinoceros beetle",
+    "weevil",
+    "fly",
+    "bee",
+    "grasshopper",
+    "cricket",
+    "walking stick",
+    "cockroach",
+    "mantis",
+    "cicada",
+    "leafhopper",
+    "lacewing",
+    "dragonfly",
+    "damselfly",
+    "admiral",
+    "ringlet",
+    "monarch",
+    "cabbage butterfly",
+    "sulphur butterfly",
+    "lycaenid",
+    "jellyfish",
+    "sea anemone",
+    "brain coral",
+    "flatworm",
+    "nematode",
+    "conch",
+    "snail",
+    "slug",
+    "sea slug",
+    "chiton",
+    "sea urchin",
+    "sea cucumber",
+    "iron",
+    "espresso maker",
+    "microwave",
+    "Dutch oven",
+    "rotisserie",
+    "toaster",
+    "waffle iron",
+    "vacuum",
+    "dishwasher",
+    "refrigerator",
+    "washer",
+    "Crock Pot",
+    "frying pan",
+    "wok",
+    "caldron",
+    "coffeepot",
+    "teapot",
+    "spatula",
+    "altar",
+    "triumphal arch",
+    "patio",
+    "steel arch bridge",
+    "suspension bridge",
+    "viaduct",
+    "barn",
+    "greenhouse",
+    "palace",
+    "monastery",
+    "library",
+    "apiary",
+    "boathouse",
+    "church",
+    "mosque",
+    "stupa",
+    "planetarium",
+    "restaurant",
+    "cinema",
+    "home theater",
+    "lumbermill",
+    "coil",
+    "obelisk",
+    "totem pole",
+    "castle",
+    "prison",
+    "grocery store",
+    "bakery",
+    "barbershop",
+    "bookshop",
+    "butcher shop",
+    "confectionery",
+    "shoe shop",
+    "tobacco shop",
+    "toyshop",
+    "fountain",
+    "cliff dwelling",
+    "yurt",
+    "dock",
+    "brass",
+    "megalith",
+    "bannister",
+    "breakwater",
+    "dam",
+    "chainlink fence",
+    "picket fence",
+    "worm fence",
+    "stone wall",
+    "grille",
+    "sliding door",
+    "turnstile",
+    "mountain tent",
+    "scoreboard",
+    "honeycomb",
+    "plate rack",
+    "pedestal",
+    "beacon",
+    "mashed potato",
+    "bell pepper",
+    "head cabbage",
+    "broccoli",
+    "cauliflower",
+    "zucchini",
+    "spaghetti squash",
+    "acorn squash",
+    "butternut squash",
+    "cucumber",
+    "artichoke",
+    "cardoon",
+    "mushroom",
+    "shower curtain",
+    "jean",
+    "carton",
+    "handkerchief",
+    "sandal",
+    "ashcan",
+    "safe",
+    "plate",
+    "necklace",
+    "croquet ball",
+    "fur coat",
+    "thimble",
+    "pajama",
+    "running shoe",
+    "cocktail shaker",
+    "chest",
+    "manhole cover",
+    "modem",
+    "tub",
+    "tray",
+    "balance beam",
+    "bagel",
+    "prayer rug",
+    "kimono",
+    "hot pot",
+    "whiskey jug",
+    "knee pad",
+    "book jacket",
+    "spindle",
+    "ski mask",
+    "beer bottle",
+    "crash helmet",
+    "bottlecap",
+    "tile roof",
+    "mask",
+    "maillot",
+    "Petri dish",
+    "football helmet",
+    "bathing cap",
+    "teddy",
+    "holster",
+    "pop bottle",
+    "photocopier",
+    "vestment",
+    "crossword puzzle",
+    "golf ball",
+    "trifle",
+    "suit",
+    "water tower",
+    "feather boa",
+    "cloak",
+    "red wine",
+    "drumstick",
+    "shield",
+    "Christmas stocking",
+    "hoopskirt",
+    "menu",
+    "stage",
+    "bonnet",
+    "meat loaf",
+    "baseball",
+    "face powder",
+    "scabbard",
+    "sunscreen",
+    "beer glass",
+    "hen-of-the-woods",
+    "guacamole",
+    "lampshade",
+    "wool",
+    "hay",
+    "bow tie",
+    "mailbag",
+    "water jug",
+    "bucket",
+    "dishrag",
+    "soup bowl",
+    "eggnog",
+    "mortar",
+    "trench coat",
+    "paddle",
+    "chain",
+    "swab",
+    "mixing bowl",
+    "potpie",
+    "wine bottle",
+    "shoji",
+    "bulletproof vest",
+    "drilling platform",
+    "binder",
+    "cardigan",
+    "sweatshirt",
+    "pot",
+    "birdhouse",
+    "hamper",
+    "ping-pong ball",
+    "pencil box",
+    "pay-phone",
+    "consomme",
+    "apron",
+    "punching bag",
+    "backpack",
+    "groom",
+    "bearskin",
+    "pencil sharpener",
+    "broom",
+    "mosquito net",
+    "abaya",
+    "mortarboard",
+    "poncho",
+    "crutch",
+    "Polaroid camera",
+    "space bar",
+    "cup",
+    "racket",
+    "traffic light",
+    "quill",
+    "radio",
+    "dough",
+    "cuirass",
+    "military uniform",
+    "lipstick",
+    "shower cap",
+    "monitor",
+    "oscilloscope",
+    "mitten",
+    "brassiere",
+    "French loaf",
+    "vase",
+    "milk can",
+    "rugby ball",
+    "paper towel",
+    "earthstar",
+    "envelope",
+    "miniskirt",
+    "cowboy hat",
+    "trolleybus",
+    "perfume",
+    "bathtub",
+    "hotdog",
+    "coral fungus",
+    "bullet train",
+    "pillow",
+    "toilet tissue",
+    "cassette",
+    "carpenter's kit",
+    "ladle",
+    "stinkhorn",
+    "lotion",
+    "hair spray",
+    "academic gown",
+    "dome",
+    "crate",
+    "wig",
+    "burrito",
+    "pill bottle",
+    "chain mail",
+    "theater curtain",
+    "window shade",
+    "barrel",
+    "washbasin",
+    "ballpoint",
+    "basketball",
+    "bath towel",
+    "cowboy boot",
+    "gown",
+    "window screen",
+    "agaric",
+    "cellular telephone",
+    "nipple",
+    "barbell",
+    "mailbox",
+    "lab coat",
+    "fire screen",
+    "minibus",
+    "packet",
+    "maze",
+    "pole",
+    "horizontal bar",
+    "sombrero",
+    "pickelhaube",
+    "rain barrel",
+    "wallet",
+    "cassette player",
+    "comic book",
+    "piggy bank",
+    "street sign",
+    "bell cote",
+    "fountain pen",
+    "Windsor tie",
+    "volleyball",
+    "overskirt",
+    "sarong",
+    "purse",
+    "bolo tie",
+    "bib",
+    "parachute",
+    "sleeping bag",
+    "television",
+    "swimming trunks",
+    "measuring cup",
+    "espresso",
+    "pizza",
+    "breastplate",
+    "shopping basket",
+    "wooden spoon",
+    "saltshaker",
+    "chocolate sauce",
+    "ballplayer",
+    "goblet",
+    "gyromitra",
+    "stretcher",
+    "water bottle",
+    "dial telephone",
+    "soap dispenser",
+    "jersey",
+    "school bus",
+    "jigsaw puzzle",
+    "plastic bag",
+    "reflex camera",
+    "diaper",
+    "Band Aid",
+    "ice lolly",
+    "velvet",
+    "tennis ball",
+    "gasmask",
+    "doormat",
+    "Loafer",
+    "ice cream",
+    "pretzel",
+    "quilt",
+    "maillot",
+    "tape player",
+    "clog",
+    "iPod",
+    "bolete",
+    "scuba diver",
+    "pitcher",
+    "matchstick",
+    "bikini",
+    "sock",
+    "CD player",
+    "lens cap",
+    "thatch",
+    "vault",
+    "beaker",
+    "bubble",
+    "cheeseburger",
+    "parallel bars",
+    "flagpole",
+    "coffee mug",
+    "rubber eraser",
+    "stole",
+    "carbonara",
+    "dumbbell",
+    
+]
\ No newline at end of file

From 26769e906ae8b1065d89bd830396ab68a00d885b Mon Sep 17 00:00:00 2001
From: Mohamed Amine Ben Ammar <hiddentn@outlook.com>
Date: Thu, 16 Aug 2018 13:53:42 +0100
Subject: [PATCH 2/5] fixed linting stuff

---
 src/ImageClassifier/darknet.js | 189 ++++++++++++++++-----------------
 1 file changed, 93 insertions(+), 96 deletions(-)

diff --git a/src/ImageClassifier/darknet.js b/src/ImageClassifier/darknet.js
index f0841bdfb..364638151 100644
--- a/src/ImageClassifier/darknet.js
+++ b/src/ImageClassifier/darknet.js
@@ -3,72 +3,106 @@
 // This software is released under the MIT License.
 // https://opensource.org/licenses/MIT
 
-/* eslint-disable */
 import * as tf from '@tensorflow/tfjs';
 import IMAGENET_CLASSES_DARKNET from '../utils/IMAGENET_CLASSES_DARKNET';
 
 const DEFAULTS = {
-    DARKNET_URL:'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknetreference/model.json',
-    DARKNET_TINY_URL:'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknettiny/model.json',
-    IMAGE_SIZE_DARKNET:256,
-    IMAGE_SIZE_DARKNET_TINY:224,
-}
+  DARKNET_URL: 'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknetreference/model.json',
+  DARKNET_TINY_URL: 'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknettiny/model.json',
+  IMAGE_SIZE_DARKNET: 256,
+  IMAGE_SIZE_DARKNET_TINY: 224,
+};
 
 
-export async function load(version) {
-  if (tf == null) {
-    throw new Error(
-        `Cannot find TensorFlow.js. If you are using a <script> tag, please ` +
-        `also include @tensorflow/tfjs on the page before using this model.`);
+async function getTopKClasses(logits, topK) {
+  const values = await logits.data();
+  const valuesAndIndices = [];
+  for (let i = 0; i < values.length; i += 1) {
+    valuesAndIndices.push({
+      value: values[i],
+      index: i,
+    });
   }
-  if (version !== 'reference' && version !== 'tiny') {
-    throw new Error(`Please select a version : darknet-reference or darknet-tiny`);
+  valuesAndIndices.sort((a, b) => b.value - a.value);
+
+  const topkValues = new Float32Array(topK);
+  const topkIndices = new Int32Array(topK);
+  for (let i = 0; i < topK; i += 1) {
+    topkValues[i] = valuesAndIndices[i].value;
+    topkIndices[i] = valuesAndIndices[i].index;
   }
- 
-  const darknet = new Darknet(version);
-  await darknet.load();
-  return darknet;
+
+  const topClassesAndProbs = [];
+  for (let i = 0; i < topkIndices.length; i += 1) {
+    topClassesAndProbs.push({
+      className: IMAGENET_CLASSES_DARKNET[topkIndices[i]],
+      probability: topkValues[i],
+    });
+  }
+  return topClassesAndProbs;
 }
 
+function preProcess(img, size) {
+  let image;
+  if (!(img instanceof tf.Tensor)) {
+    if (img instanceof HTMLImageElement || img instanceof HTMLVideoElement) {
+      image = tf.fromPixels(img);
+    } else if (typeof img === 'object' && (img.elt instanceof HTMLImageElement || img.elt instanceof HTMLVideoElement)) {
+      image = tf.fromPixels(img.elt); // Handle p5.js image and video.
+    }
+  } else {
+    image = img;
+  }
+  // Normalize the image from [0, 255] to [0, 1].
+  const normalized = image.toFloat().div(tf.scalar(255));
+  let resized = normalized;
+  if (normalized.shape[0] !== size || normalized.shape[1] !== size) {
+    const alignCorners = true;
+    resized = tf.image.resizeBilinear(normalized, [size, size], alignCorners);
+  }
+  // Reshape to a single-element batch so we can pass it to predict.
+  const batched = resized.reshape([1, size, size, 3]);
+  // Scale Stuff
+  // this.scaleX = this.imgHeight / this.inputHeight;
+  // this.scaleY = this.imgWidth / this.inputWidth;
+  return batched;
+}
 export class Darknet {
- 
   constructor(version) {
     this.version = version;
     switch (this.version) {
-        case 'reference':
-          this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET;
-          break;
-        case 'tiny':
-          this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET_TINY;
-          break;
-
-        default:
-            break;
+      case 'reference':
+        this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET;
+        break;
+      case 'tiny':
+        this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET_TINY;
+        break;
+
+      default:
+        break;
     }
-    this.imgSize
   }
 
   async load() {
     switch (this.version) {
-        // might add darknet_448
-        case 'reference':
-          this.model = await tf.loadModel(DEFAULTS.DARKNET_URL);
-          break;
-    
-        case 'tiny':
-          this.model = await tf.loadModel(DEFAULTS.DARKNET_TINY_URL);
-          break;
-        
-        default:
-            break;
+      // might add darknet_448
+      case 'reference':
+        this.model = await tf.loadModel(DEFAULTS.DARKNET_URL);
+        break;
+
+      case 'tiny':
+        this.model = await tf.loadModel(DEFAULTS.DARKNET_TINY_URL);
+        break;
+
+      default:
+        break;
     }
-    
+
     // Warmup the model.
-    const result = tf.tidy(() =>this.model.predict(tf.zeros([1, this.imgSize, this.imgSize, 3])));
+    const result = tf.tidy(() => this.model.predict(tf.zeros([1, this.imgSize, this.imgSize, 3])));
     await result.data();
     result.dispose();
-
-    }
+  }
 
   /**
    * Classifies an image from the 1000 ImageNet classes returning a map of
@@ -79,65 +113,28 @@ export class Darknet {
    * @param topk How many top values to use. Defaults to 3.
    */
   async classify(img, topk = 3) {
-    let logits = tf.tidy(()=>{
-        const imgData = this.preProcess(img,this.imgSize);
-        const predictions = this.model.predict(imgData)
-        return tf.softmax(predictions);
-    })
+    const logits = tf.tidy(() => {
+      const imgData = preProcess(img, this.imgSize);
+      const predictions = this.model.predict(imgData);
+      return tf.softmax(predictions);
+    });
     const classes = await getTopKClasses(logits, topk);
     logits.dispose();
     return classes;
   }
-
-  preProcess(img, size) {
-    let image;
-    if (!(img instanceof tf.Tensor)) {
-        if (img instanceof HTMLImageElement || img instanceof HTMLVideoElement) {
-            image = tf.fromPixels(img);
-        } else if (typeof img === 'object' && (img.elt instanceof HTMLImageElement || img.elt instanceof HTMLVideoElement)) {
-            image = tf.fromPixels(img.elt); // Handle p5.js image and video.
-        }
-    } else {
-        image = img;
-    }
-    // Normalize the image from [0, 255] to [0, 1].
-    const normalized = image.toFloat().div(tf.scalar(255));
-    let resized = normalized;
-    if (normalized.shape[0] !== size || normalized.shape[1] !== size) {
-        const alignCorners = true;
-        resized = tf.image.resizeBilinear(normalized, [size, size], alignCorners);
-    }
-    // Reshape to a single-element batch so we can pass it to predict.
-    const batched = resized.reshape([1, size, size, 3]);
-    // Scale Stuff
-    // this.scaleX = this.imgHeight / this.inputHeight;
-    // this.scaleY = this.imgWidth / this.inputWidth;
-    return batched;
-}
 }
 
-async function getTopKClasses(logits, topK) {
-  const values = await logits.data();
-  const valuesAndIndices = [];
-  for (let i = 0; i < values.length; i++) {
-    valuesAndIndices.push({value: values[i], index: i});
+
+export async function load(version) {
+  if (tf == null) {
+    throw new Error('Cannot find TensorFlow.js. If you are using a <script> tag, please ' +
+      'also include @tensorflow/tfjs on the page before using this model.');
   }
-  valuesAndIndices.sort((a, b) => {
-    return b.value - a.value;
-  });
-  const topkValues = new Float32Array(topK);
-  const topkIndices = new Int32Array(topK);
-  for (let i = 0; i < topK; i++) {
-    topkValues[i] = valuesAndIndices[i].value;
-    topkIndices[i] = valuesAndIndices[i].index;
+  if (version !== 'reference' && version !== 'tiny') {
+    throw new Error('Please select a version : darknet-reference or darknet-tiny');
   }
 
-  const topClassesAndProbs = [];
-  for (let i = 0; i < topkIndices.length; i++) {
-    topClassesAndProbs.push({
-      className: IMAGENET_CLASSES_DARKNET[topkIndices[i]],
-      probability: topkValues[i]
-    });
-  }
-  return topClassesAndProbs;
-}
\ No newline at end of file
+  const darknet = new Darknet(version);
+  await darknet.load();
+  return darknet;
+}

From 46527fa8fbe58c763d3ffff658a91dce7c10f6b6 Mon Sep 17 00:00:00 2001
From: Mohamed Amine Ben Ammar <hiddentn@outlook.com>
Date: Thu, 16 Aug 2018 20:48:43 +0100
Subject: [PATCH 3/5] edits..

---
 src/ImageClassifier/darknet.js | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/ImageClassifier/darknet.js b/src/ImageClassifier/darknet.js
index 364638151..66cab1d9f 100644
--- a/src/ImageClassifier/darknet.js
+++ b/src/ImageClassifier/darknet.js
@@ -7,8 +7,8 @@ import * as tf from '@tensorflow/tfjs';
 import IMAGENET_CLASSES_DARKNET from '../utils/IMAGENET_CLASSES_DARKNET';
 
 const DEFAULTS = {
-  DARKNET_URL: 'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknetreference/model.json',
-  DARKNET_TINY_URL: 'https://rawgit.com/TheHidden1/ml5-data-and-models/darknetclassifier/models/darknetclassifier/darknettiny/model.json',
+  DARKNET_URL: 'https://rawgit.com/ml5js/ml5-data-and-models/master/models/darknetclassifier/darknetreference/model.json',
+  DARKNET_TINY_URL: 'https://rawgit.com/ml5js/ml5-data-and-models/master/models/darknetclassifier/darknettiny/model.json',
   IMAGE_SIZE_DARKNET: 256,
   IMAGE_SIZE_DARKNET_TINY: 224,
 };

From 978ff993590338834ce279b3d202cb5580c50c87 Mon Sep 17 00:00:00 2001
From: Mohamed Amine Ben Ammar <hiddentn@outlook.com>
Date: Thu, 16 Aug 2018 20:52:17 +0100
Subject: [PATCH 4/5] edits2.0

---
 src/ImageClassifier/darknet.js | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/src/ImageClassifier/darknet.js b/src/ImageClassifier/darknet.js
index 66cab1d9f..fff4557de 100644
--- a/src/ImageClassifier/darknet.js
+++ b/src/ImageClassifier/darknet.js
@@ -126,10 +126,6 @@ export class Darknet {
 
 
 export async function load(version) {
-  if (tf == null) {
-    throw new Error('Cannot find TensorFlow.js. If you are using a <script> tag, please ' +
-      'also include @tensorflow/tfjs on the page before using this model.');
-  }
   if (version !== 'reference' && version !== 'tiny') {
     throw new Error('Please select a version : darknet-reference or darknet-tiny');
   }

From 4cf7f6aa0ff51c1f38ff5d832dc926775e9d75cc Mon Sep 17 00:00:00 2001
From: Cristobal Valenzuela <cvalenzuela@nyu.edu>
Date: Mon, 17 Sep 2018 17:31:29 -0400
Subject: [PATCH 5/5] clean comments

---
 src/ImageClassifier/darknet.js | 22 ++--------------------
 src/ImageClassifier/index.js   |  1 -
 2 files changed, 2 insertions(+), 21 deletions(-)

diff --git a/src/ImageClassifier/darknet.js b/src/ImageClassifier/darknet.js
index fff4557de..0da6d4bd8 100644
--- a/src/ImageClassifier/darknet.js
+++ b/src/ImageClassifier/darknet.js
@@ -13,7 +13,6 @@ const DEFAULTS = {
   IMAGE_SIZE_DARKNET_TINY: 224,
 };
 
-
 async function getTopKClasses(logits, topK) {
   const values = await logits.data();
   const valuesAndIndices = [];
@@ -53,20 +52,16 @@ function preProcess(img, size) {
   } else {
     image = img;
   }
-  // Normalize the image from [0, 255] to [0, 1].
   const normalized = image.toFloat().div(tf.scalar(255));
   let resized = normalized;
   if (normalized.shape[0] !== size || normalized.shape[1] !== size) {
     const alignCorners = true;
     resized = tf.image.resizeBilinear(normalized, [size, size], alignCorners);
   }
-  // Reshape to a single-element batch so we can pass it to predict.
   const batched = resized.reshape([1, size, size, 3]);
-  // Scale Stuff
-  // this.scaleX = this.imgHeight / this.inputHeight;
-  // this.scaleY = this.imgWidth / this.inputWidth;
   return batched;
 }
+
 export class Darknet {
   constructor(version) {
     this.version = version;
@@ -77,7 +72,6 @@ export class Darknet {
       case 'tiny':
         this.imgSize = DEFAULTS.IMAGE_SIZE_DARKNET_TINY;
         break;
-
       default:
         break;
     }
@@ -85,15 +79,12 @@ export class Darknet {
 
   async load() {
     switch (this.version) {
-      // might add darknet_448
       case 'reference':
         this.model = await tf.loadModel(DEFAULTS.DARKNET_URL);
         break;
-
       case 'tiny':
         this.model = await tf.loadModel(DEFAULTS.DARKNET_TINY_URL);
         break;
-
       default:
         break;
     }
@@ -104,14 +95,6 @@ export class Darknet {
     result.dispose();
   }
 
-  /**
-   * Classifies an image from the 1000 ImageNet classes returning a map of
-   * the most likely class names to their probability.
-   *
-   * @param img The image to classify. Can be a tensor or a DOM element image,
-   * video, or canvas.
-   * @param topk How many top values to use. Defaults to 3.
-   */
   async classify(img, topk = 3) {
     const logits = tf.tidy(() => {
       const imgData = preProcess(img, this.imgSize);
@@ -124,10 +107,9 @@ export class Darknet {
   }
 }
 
-
 export async function load(version) {
   if (version !== 'reference' && version !== 'tiny') {
-    throw new Error('Please select a version : darknet-reference or darknet-tiny');
+    throw new Error('Please select a version: darknet-reference or darknet-tiny');
   }
 
   const darknet = new Darknet(version);
diff --git a/src/ImageClassifier/index.js b/src/ImageClassifier/index.js
index 5d0d2e7a4..7e59b0b9f 100644
--- a/src/ImageClassifier/index.js
+++ b/src/ImageClassifier/index.js
@@ -12,7 +12,6 @@ import * as mobilenet from '@tensorflow-models/mobilenet';
 import * as darknet from './darknet';
 import callCallback from '../utils/callcallback';
 
-
 const DEFAULTS = {
   mobilenet: {
     version: 1,