"use strict"; var __awaiter = this && this.__awaiter || function (thisArg, _arguments, P, generator) { return new (P || (P = Promise))(function (resolve, reject) { function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } } function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } } function step(result) { result.done ? resolve(result.value) : new P(function (resolve) { resolve(result.value); }).then(fulfilled, rejected); } step((generator = generator.apply(thisArg, _arguments || [])).next()); }); }; var __generator = this && this.__generator || function (thisArg, body) { var _ = { label: 0, sent: function sent() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g; return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function () { return this; }), g; function verb(n) { return function (v) { return step([n, v]); }; } function step(op) { if (f) throw new TypeError("Generator is already executing."); while (_) { try { if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t; if (y = 0, t) op = [op[0] & 2, t.value]; switch (op[0]) { case 0: case 1: t = op; break; case 4: _.label++; return { value: op[1], done: false }; case 5: _.label++; y = op[1]; op = [0]; continue; case 7: op = _.ops.pop(); _.trys.pop(); continue; default: if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; } if (op[0] === 3 && (!t || op[1] > t[0] && op[1] < t[3])) { _.label = op[1]; break; } if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; } if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; } if (t[2]) _.ops.pop(); _.trys.pop(); continue; } op = body.call(thisArg, _); } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; } } if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true }; } }; Object.defineProperty(exports, "__esModule", { value: true }); var tf = require("@tensorflow/tfjs"); var nsfw_classes_1 = require("./nsfw_classes"); var BASE_PATH = 'https://s3.amazonaws.com/ir_public/nsfwjs/'; var IMAGE_SIZE = 299; function load(base) { if (base === void 0) { base = BASE_PATH; } return __awaiter(this, void 0, void 0, function () { var nsfwnet; return __generator(this, function (_a) { switch (_a.label) { case 0: 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."); } nsfwnet = new Index(base); return [4, nsfwnet.load()]; case 1: _a.sent(); return [2, nsfwnet]; } }); }); } exports.load = load; var Index = function () { function NSFWJS(base) { this.intermediateModels = {}; this.path = base + "model.json"; this.normalizationOffset = tf.scalar(255); } NSFWJS.prototype.load = function () { return __awaiter(this, void 0, void 0, function () { var _a, result; var _this = this; return __generator(this, function (_b) { switch (_b.label) { case 0: _a = this; return [4, tf.loadLayersModel(this.path)]; case 1: _a.model = _b.sent(); this.endpoints = this.model.layers.map(function (l) { return l.name; }); result = tf.tidy(function () { return _this.model.predict(tf.zeros([1, IMAGE_SIZE, IMAGE_SIZE, 3])); }); return [4, result.data()]; case 2: _b.sent(); result.dispose(); return [2]; } }); }); }; NSFWJS.prototype.infer = function (img, endpoint) { var _this = this; if (endpoint != null && this.endpoints.indexOf(endpoint) === -1) { throw new Error("Unknown endpoint " + endpoint + ". Available endpoints: " + (this.endpoints + ".")); } return tf.tidy(function () { if (!(img instanceof tf.Tensor)) { img = tf.browser.fromPixels(img); } var normalized = img.toFloat().div(_this.normalizationOffset); var resized = normalized; if (img.shape[0] !== IMAGE_SIZE || img.shape[1] !== IMAGE_SIZE) { var alignCorners = true; resized = tf.image.resizeBilinear(normalized, [IMAGE_SIZE, IMAGE_SIZE], alignCorners); } var batched = resized.reshape([1, IMAGE_SIZE, IMAGE_SIZE, 3]); var model; if (endpoint == null) { model = _this.model; } else { if (_this.intermediateModels[endpoint] == null) { var layer = _this.model.layers.find(function (l) { return l.name === endpoint; }); _this.intermediateModels[endpoint] = tf.model({ inputs: _this.model.inputs, outputs: layer.output }); } model = _this.intermediateModels[endpoint]; } return model.predict(batched); }); }; NSFWJS.prototype.classify = function (img, topk) { if (topk === void 0) { topk = 5; } return __awaiter(this, void 0, void 0, function () { var logits, classes; return __generator(this, function (_a) { switch (_a.label) { case 0: logits = this.infer(img); return [4, getTopKClasses(logits, topk)]; case 1: classes = _a.sent(); logits.dispose(); return [2, classes]; } }); }); }; return NSFWJS; }(); exports.NSFWJS = Index; function getTopKClasses(logits, topK) { return __awaiter(this, void 0, void 0, function () { var values, valuesAndIndices, i, topkValues, topkIndices, i, topClassesAndProbs, i; return __generator(this, function (_a) { switch (_a.label) { case 0: return [4, logits.data()]; case 1: values = _a.sent(); valuesAndIndices = []; for (i = 0; i < values.length; i++) { valuesAndIndices.push({ value: values[i], index: i }); } valuesAndIndices.sort(function (a, b) { return b.value - a.value; }); topkValues = new Float32Array(topK); topkIndices = new Int32Array(topK); for (i = 0; i < topK; i++) { topkValues[i] = valuesAndIndices[i].value; topkIndices[i] = valuesAndIndices[i].index; } topClassesAndProbs = []; for (i = 0; i < topkIndices.length; i++) { topClassesAndProbs.push({ className: nsfw_classes_1.NSFW_CLASSES[topkIndices[i]], probability: topkValues[i] }); } return [2, topClassesAndProbs]; } }); }); }