"use strict";
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/**
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* @license
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* Copyright 2019 Google Inc. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
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return new (P || (P = Promise))(function (resolve, reject) {
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function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
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function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
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function step(result) { result.done ? resolve(result.value) : new P(function (resolve) { resolve(result.value); }).then(fulfilled, rejected); }
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step((generator = generator.apply(thisArg, _arguments || [])).next());
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});
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};
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var __generator = (this && this.__generator) || function (thisArg, body) {
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var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
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return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
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function verb(n) { return function (v) { return step([n, v]); }; }
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function step(op) {
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if (f) throw new TypeError("Generator is already executing.");
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while (_) try {
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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;
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if (y = 0, t) op = [op[0] & 2, t.value];
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switch (op[0]) {
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case 0: case 1: t = op; break;
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case 4: _.label++; return { value: op[1], done: false };
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case 5: _.label++; y = op[1]; op = [0]; continue;
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case 7: op = _.ops.pop(); _.trys.pop(); continue;
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default:
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if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
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if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
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if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
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if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
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if (t[2]) _.ops.pop();
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_.trys.pop(); continue;
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}
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op = body.call(thisArg, _);
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} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
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if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
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}
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};
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Object.defineProperty(exports, "__esModule", { value: true });
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var engine_1 = require("../engine");
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var kernel_registry_1 = require("../kernel_registry");
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var tensor_1 = require("../tensor");
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var tensor_util_env_1 = require("../tensor_util_env");
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var operation_1 = require("./operation");
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var tensor_ops_1 = require("./tensor_ops");
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var fromPixels2DContext;
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/**
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* Creates a `tf.Tensor` from an image.
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*
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* ```js
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* const image = new ImageData(1, 1);
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* image.data[0] = 100;
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* image.data[1] = 150;
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* image.data[2] = 200;
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* image.data[3] = 255;
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*
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* tf.browser.fromPixels(image).print();
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* ```
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*
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* @param pixels The input image to construct the tensor from. The
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* supported image types are all 4-channel. You can also pass in an image
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* object with following attributes:
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* `{data: Uint8Array; width: number; height: number}`
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* @param numChannels The number of channels of the output tensor. A
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* numChannels value less than 4 allows you to ignore channels. Defaults to
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* 3 (ignores alpha channel of input image).
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*/
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/** @doc {heading: 'Browser', namespace: 'browser', ignoreCI: true} */
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function fromPixels_(pixels, numChannels) {
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if (numChannels === void 0) { numChannels = 3; }
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// Sanity checks.
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if (numChannels > 4) {
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throw new Error('Cannot construct Tensor with more than 4 channels from pixels.');
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}
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if (pixels == null) {
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throw new Error('pixels passed to tf.browser.fromPixels() can not be null');
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}
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var isPixelData = false;
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var isImageData = false;
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var isVideo = false;
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var isImage = false;
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var isCanvasLike = false;
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if (pixels.data instanceof Uint8Array) {
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isPixelData = true;
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}
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else if (typeof (ImageData) !== 'undefined' && pixels instanceof ImageData) {
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isImageData = true;
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}
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else if (typeof (HTMLVideoElement) !== 'undefined' &&
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pixels instanceof HTMLVideoElement) {
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isVideo = true;
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}
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else if (typeof (HTMLImageElement) !== 'undefined' &&
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pixels instanceof HTMLImageElement) {
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isImage = true;
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// tslint:disable-next-line: no-any
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}
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else if (pixels.getContext != null) {
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isCanvasLike = true;
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}
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else {
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throw new Error('pixels passed to tf.browser.fromPixels() must be either an ' +
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"HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData " +
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"in browser, or OffscreenCanvas, ImageData in webworker" +
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" or {data: Uint32Array, width: number, height: number}, " +
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("but was " + pixels.constructor.name));
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}
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if (isVideo) {
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var HAVE_CURRENT_DATA_READY_STATE = 2;
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if (isVideo &&
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pixels.readyState <
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HAVE_CURRENT_DATA_READY_STATE) {
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throw new Error('The video element has not loaded data yet. Please wait for ' +
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'`loadeddata` event on the <video> element.');
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}
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}
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// If the current backend has 'FromPixels' registered, it has a more
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// efficient way of handling pixel uploads, so we call that.
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var kernel = kernel_registry_1.getKernel('FromPixels', engine_1.ENGINE.backendName);
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if (kernel != null) {
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return engine_1.ENGINE.runKernel('FromPixels', { pixels: pixels }, { numChannels: numChannels });
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}
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var _a = isVideo ?
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[
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pixels.videoWidth,
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pixels.videoHeight
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] :
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[pixels.width, pixels.height], width = _a[0], height = _a[1];
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var vals;
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if (isCanvasLike) {
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vals =
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// tslint:disable-next-line:no-any
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pixels.getContext('2d').getImageData(0, 0, width, height).data;
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}
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else if (isImageData || isPixelData) {
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vals = pixels.data;
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}
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else if (isImage || isVideo) {
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if (fromPixels2DContext == null) {
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fromPixels2DContext = document.createElement('canvas').getContext('2d');
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}
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fromPixels2DContext.canvas.width = width;
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fromPixels2DContext.canvas.height = height;
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fromPixels2DContext.drawImage(pixels, 0, 0, width, height);
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vals = fromPixels2DContext.getImageData(0, 0, width, height).data;
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}
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var values;
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if (numChannels === 4) {
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values = new Int32Array(vals);
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}
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else {
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var numPixels = width * height;
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values = new Int32Array(numPixels * numChannels);
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for (var i = 0; i < numPixels; i++) {
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for (var channel = 0; channel < numChannels; ++channel) {
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values[i * numChannels + channel] = vals[i * 4 + channel];
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}
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}
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}
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var outShape = [height, width, numChannels];
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return tensor_ops_1.tensor3d(values, outShape, 'int32');
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}
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/**
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* Draws a `tf.Tensor` of pixel values to a byte array or optionally a
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* canvas.
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*
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* When the dtype of the input is 'float32', we assume values in the range
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* [0-1]. Otherwise, when input is 'int32', we assume values in the range
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* [0-255].
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*
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* Returns a promise that resolves when the canvas has been drawn to.
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*
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* @param img A rank-2 or rank-3 tensor. If rank-2, draws grayscale. If
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* rank-3, must have depth of 1, 3 or 4. When depth of 1, draws
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* grayscale. When depth of 3, we draw with the first three components of
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* the depth dimension corresponding to r, g, b and alpha = 1. When depth of
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* 4, all four components of the depth dimension correspond to r, g, b, a.
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* @param canvas The canvas to draw to.
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*/
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/** @doc {heading: 'Browser', namespace: 'browser'} */
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function toPixels(img, canvas) {
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return __awaiter(this, void 0, void 0, function () {
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var $img, _a, height, width, depth, data, minTensor, maxTensor, vals, minVals, maxVals, min, max, multiplier, bytes, i, r, g, b, a, j, ctx, imageData;
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return __generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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$img = tensor_util_env_1.convertToTensor(img, 'img', 'toPixels');
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if (!(img instanceof tensor_1.Tensor)) {
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// Assume int32 if user passed a native array.
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$img = $img.toInt();
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}
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if ($img.rank !== 2 && $img.rank !== 3) {
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throw new Error("toPixels only supports rank 2 or 3 tensors, got rank " + $img.rank + ".");
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}
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_a = $img.shape.slice(0, 2), height = _a[0], width = _a[1];
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depth = $img.rank === 2 ? 1 : $img.shape[2];
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if (depth > 4 || depth === 2) {
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throw new Error("toPixels only supports depth of size " +
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("1, 3 or 4 but got " + depth));
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}
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return [4 /*yield*/, $img.data()];
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case 1:
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data = _b.sent();
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minTensor = $img.min();
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maxTensor = $img.max();
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return [4 /*yield*/, Promise.all([minTensor.data(), maxTensor.data()])];
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case 2:
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vals = _b.sent();
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minVals = vals[0];
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maxVals = vals[1];
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min = minVals[0];
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max = maxVals[0];
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minTensor.dispose();
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maxTensor.dispose();
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if ($img.dtype === 'float32') {
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if (min < 0 || max > 1) {
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throw new Error("Tensor values for a float32 Tensor must be in the " +
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("range [0 - 1] but got range [" + min + " - " + max + "]."));
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}
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}
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else if ($img.dtype === 'int32') {
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if (min < 0 || max > 255) {
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throw new Error("Tensor values for a int32 Tensor must be in the " +
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("range [0 - 255] but got range [" + min + " - " + max + "]."));
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}
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}
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else {
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throw new Error("Unsupported type for toPixels: " + $img.dtype + "." +
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" Please use float32 or int32 tensors.");
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}
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multiplier = $img.dtype === 'float32' ? 255 : 1;
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bytes = new Uint8ClampedArray(width * height * 4);
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for (i = 0; i < height * width; ++i) {
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r = void 0, g = void 0, b = void 0, a = void 0;
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if (depth === 1) {
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r = data[i] * multiplier;
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g = data[i] * multiplier;
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b = data[i] * multiplier;
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a = 255;
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}
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else if (depth === 3) {
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r = data[i * 3] * multiplier;
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g = data[i * 3 + 1] * multiplier;
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b = data[i * 3 + 2] * multiplier;
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a = 255;
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}
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else if (depth === 4) {
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r = data[i * 4] * multiplier;
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g = data[i * 4 + 1] * multiplier;
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b = data[i * 4 + 2] * multiplier;
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a = data[i * 4 + 3] * multiplier;
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}
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j = i * 4;
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bytes[j + 0] = Math.round(r);
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bytes[j + 1] = Math.round(g);
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bytes[j + 2] = Math.round(b);
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bytes[j + 3] = Math.round(a);
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}
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if (canvas != null) {
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canvas.width = width;
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canvas.height = height;
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ctx = canvas.getContext('2d');
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imageData = new ImageData(bytes, width, height);
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ctx.putImageData(imageData, 0, 0);
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}
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if ($img !== img) {
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$img.dispose();
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}
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return [2 /*return*/, bytes];
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}
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});
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});
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}
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exports.toPixels = toPixels;
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exports.fromPixels = operation_1.op({ fromPixels_: fromPixels_ });
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//# sourceMappingURL=browser.js.map
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