/**
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* @license
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* Copyright 2019 Google LLC. 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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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/browser" />
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import { Tensor2D, Tensor3D } from '../tensor';
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import { DrawOptions, PixelData, TensorLike } from '../types';
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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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* @returns A Tensor3D with the shape `[height, width, numChannels]`.
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*
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* Note: fromPixels can be lossy in some cases, same image may result in
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* slightly different tensor values, if rendered by different rendering
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* engines. This means that results from different browsers, or even same
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* browser with CPU and GPU rendering engines can be different. See discussion
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* in details:
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* https://github.com/tensorflow/tfjs/issues/5482
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*
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* @doc {heading: 'Browser', namespace: 'browser', ignoreCI: true}
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*/
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declare function fromPixels_(pixels: PixelData | ImageData | HTMLImageElement | HTMLCanvasElement | HTMLVideoElement | ImageBitmap, numChannels?: number): Tensor3D;
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/**
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* Creates a `tf.Tensor` from an image in async way.
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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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* (await tf.browser.fromPixelsAsync(image)).print();
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* ```
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* This API is the async version of fromPixels. The API will first
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* check |WRAP_TO_IMAGEBITMAP| flag, and try to wrap the input to
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* imageBitmap if the flag is set to true.
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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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*/
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export declare function fromPixelsAsync(pixels: PixelData | ImageData | HTMLImageElement | HTMLCanvasElement | HTMLVideoElement | ImageBitmap, numChannels?: number): Promise<Tensor3D>;
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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 tensor with shape `[height, width]`, or a rank-3 tensor
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* of shape `[height, width, numChannels]`. 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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*/
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export declare function toPixels(img: Tensor2D | Tensor3D | TensorLike, canvas?: HTMLCanvasElement): Promise<Uint8ClampedArray>;
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/**
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* Draws a `tf.Tensor` to a 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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* @param image The tensor to draw on the canvas. Must match one of
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* these shapes:
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* - Rank-2 with shape `[height, width`]: Drawn as grayscale.
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* - Rank-3 with shape `[height, width, 1]`: Drawn as grayscale.
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* - Rank-3 with shape `[height, width, 3]`: Drawn as RGB with alpha set in
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* `imageOptions` (defaults to 1, which is opaque).
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* - Rank-3 with shape `[height, width, 4]`: Drawn as RGBA.
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* @param canvas The canvas to draw to.
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* @param options The configuration arguments for image to be drawn and the
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* canvas to draw to.
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*
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* @doc {heading: 'Browser', namespace: 'browser'}
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*/
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export declare function draw(image: Tensor2D | Tensor3D | TensorLike, canvas: HTMLCanvasElement, options?: DrawOptions): void;
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export declare const fromPixels: typeof fromPixels_;
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export {};
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