"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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var tslib_1 = require("tslib");
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var utils_1 = require("../utils");
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var awaitMediaLoaded_1 = require("./awaitMediaLoaded");
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var isMediaElement_1 = require("./isMediaElement");
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var NetInput_1 = require("./NetInput");
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var resolveInput_1 = require("./resolveInput");
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/**
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* Validates the input to make sure, they are valid net inputs and awaits all media elements
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* to be finished loading.
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*
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* @param input The input, which can be a media element or an array of different media elements.
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* @returns A NetInput instance, which can be passed into one of the neural networks.
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*/
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function toNetInput(inputs) {
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return tslib_1.__awaiter(this, void 0, void 0, function () {
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var inputArgArray, getIdxHint, inputArray;
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return tslib_1.__generator(this, function (_a) {
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switch (_a.label) {
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case 0:
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if (inputs instanceof NetInput_1.NetInput) {
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return [2 /*return*/, inputs];
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}
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inputArgArray = Array.isArray(inputs)
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? inputs
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: [inputs];
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if (!inputArgArray.length) {
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throw new Error('toNetInput - empty array passed as input');
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}
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getIdxHint = function (idx) { return Array.isArray(inputs) ? " at input index " + idx + ":" : ''; };
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inputArray = inputArgArray.map(resolveInput_1.resolveInput);
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inputArray.forEach(function (input, i) {
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if (!isMediaElement_1.isMediaElement(input) && !utils_1.isTensor3D(input) && !utils_1.isTensor4D(input)) {
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if (typeof inputArgArray[i] === 'string') {
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throw new Error("toNetInput -" + getIdxHint(i) + " string passed, but could not resolve HTMLElement for element id " + inputArgArray[i]);
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}
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throw new Error("toNetInput -" + getIdxHint(i) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id");
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}
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if (utils_1.isTensor4D(input)) {
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// if tf.Tensor4D is passed in the input array, the batch size has to be 1
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var batchSize = input.shape[0];
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if (batchSize !== 1) {
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throw new Error("toNetInput -" + getIdxHint(i) + " tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array");
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}
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}
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});
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// wait for all media elements being loaded
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return [4 /*yield*/, Promise.all(inputArray.map(function (input) { return isMediaElement_1.isMediaElement(input) && awaitMediaLoaded_1.awaitMediaLoaded(input); }))];
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case 1:
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// wait for all media elements being loaded
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_a.sent();
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return [2 /*return*/, new NetInput_1.NetInput(inputArray, Array.isArray(inputs))];
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}
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});
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});
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}
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exports.toNetInput = toNetInput;
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//# sourceMappingURL=toNetInput.js.map
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