/**
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* @license
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* Copyright 2021 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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* https://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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import { tensor1d } from '../tensor1d';
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import { op } from '../operation';
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import { cast } from '../cast';
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import { split } from '../split';
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import { bincount } from '../bincount';
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import { lessEqual } from '../less_equal';
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import { greater } from '../greater';
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import { sum } from '../sum';
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import { add } from '../add';
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import { mul } from '../mul';
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import { div } from '../div';
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import { sub } from '../sub';
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import { round } from '../round';
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import { where } from '../where';
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import { fill } from '../fill';
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import { slice } from '../slice';
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import { range } from '../range';
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import { tensor } from '../tensor';
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import * as util from '../../util';
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import { convertToTensor } from '../../tensor_util_env';
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/**
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* Performs image binarization with corresponding threshold
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* (depends on the method)value, which creates a binary image from a grayscale.
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* @param image 3d tensor of shape [imageHeight,imageWidth, depth],
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* where imageHeight and imageWidth must be positive.The image color
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* range should be [0, 255].
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* @param method Optional string from `'binary' | 'otsu'`
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* which specifies the method for thresholding. Defaults to 'binary'.
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* @param inverted Optional boolean whichspecifies
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* if colours should be inverted. Defaults to false.
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* @param threshValue Optional number which defines threshold value from 0 to 1.
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* Defaults to 0.5.
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* @return A 3d tensor of shape [imageHeight,imageWidth, depth], which
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* contains binarized image.
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*/
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function threshold_(image, method = 'binary', inverted = false, threshValue = 0.5) {
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const $image = convertToTensor(image, 'image', 'threshold');
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/* 0.2989, 0.5870, 0.1140 are represent luma coefficients in CCIR601.
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Reference for converting between RGB and grayscale: https://en.wikipedia.org/wiki/Luma_%28video%29 */
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const RED_INTENCITY_COEF = 0.2989;
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const GREEN_INTENCITY_COEF = 0.5870;
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const BLUE_INTENCITY_COEF = 0.1140;
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const totalPixelsInImage = $image.shape[0] * $image.shape[1];
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let $threshold = mul(tensor1d([threshValue]), 255);
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let r, g, b, grayscale;
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util.assert($image.rank === 3, () => 'Error in threshold: image must be rank 3,' +
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`but got rank ${$image.rank}.`);
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util.assert($image.shape[2] === 3 || $image.shape[2] === 1, () => 'Error in threshold: ' +
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'image color channel must be equal to 3 or 1' +
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`but got ${$image.shape[2]}.`);
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util.assert($image.dtype === 'int32' || $image.dtype === 'float32', () => 'Error in dtype: image dtype must be int32 or float32,' +
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`but got dtype ${$image.dtype}.`);
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util.assert(method === 'otsu' || method === 'binary', () => `Method must be binary or otsu, but was ${method}`);
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if ($image.shape[2] === 3) {
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[r, g, b] = split($image, [1, 1, 1], -1);
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const $r = mul(r, RED_INTENCITY_COEF);
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const $g = mul(g, GREEN_INTENCITY_COEF);
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const $b = mul(b, BLUE_INTENCITY_COEF);
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grayscale = add(add($r, $g), $b);
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}
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else {
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grayscale = image;
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}
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if (method === 'otsu') {
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const $histogram = bincount(cast(round(grayscale), 'int32'), tensor([]), 256);
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$threshold = otsu($histogram, totalPixelsInImage);
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}
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const invCondition = inverted ?
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lessEqual(grayscale, $threshold) : greater(grayscale, $threshold);
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const result = cast(mul(invCondition, 255), 'int32');
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return result;
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}
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function otsu(histogram, total) {
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let bestThresh = tensor1d([-1]);
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let bestInBetVar = tensor1d([0]);
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let cInBetVar = tensor1d([0]);
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let classFirst, classSecond, meanFirst, meanSec, weightForeground, weightBack;
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for (let index = 0; index < histogram.size - 1; index++) {
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classFirst = slice(histogram, 0, index + 1);
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classSecond = slice(histogram, index + 1);
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weightForeground = div(sum(classFirst), total);
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weightBack = div(sum(classSecond), total);
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const meanFirstDivA = sum(mul(classFirst, range(0, classFirst.size)));
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meanFirst = div(meanFirstDivA, sum(classFirst));
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const meanSecFill = fill(classSecond.shape, classFirst.size);
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const meanSecAdd = add(range(0, classSecond.size), meanSecFill);
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const meanSecMul = mul(classSecond, (meanSecAdd));
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meanSec = div(sum(meanSecMul), sum(classSecond));
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const cInBetVarSubA = sub(meanFirst, meanSec);
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const cInBetVarSubB = sub(meanFirst, meanSec);
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const cInBetVarMul = mul(weightForeground, weightBack);
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cInBetVar = mul(mul(cInBetVarMul, cInBetVarSubA), cInBetVarSubB);
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const condition = greater(cInBetVar, bestInBetVar);
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bestInBetVar = where(condition, cInBetVar, bestInBetVar);
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bestThresh = where(condition, tensor1d([index]), bestThresh);
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}
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return bestThresh;
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}
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export const threshold = /* @__PURE__ */ op({ threshold_ });
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All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * https://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport { Tensor1D, Tensor3D } from '../../tensor';\nimport { tensor1d } from '../tensor1d';\nimport { TensorLike } from '../../types';\nimport { op } from '../operation';\nimport { cast } from '../cast';\nimport { split } from '../split';\nimport { bincount } from '../bincount';\nimport { lessEqual } from '../less_equal';\nimport { greater } from '../greater';\nimport { sum } from '../sum';\nimport { add } from '../add';\nimport { mul } from '../mul';\nimport { div } from '../div';\nimport { sub } from '../sub';\nimport { round } from '../round';\nimport { where } from '../where';\nimport { fill } from '../fill';\nimport {slice} from '../slice';\nimport { range } from '../range';\nimport { tensor } from '../tensor';\nimport * as util from '../../util';\nimport { convertToTensor } from '../../tensor_util_env';\n\n/**\n * Performs image binarization with corresponding threshold\n * (depends on the method)value, which creates a binary image from a grayscale.\n * @param image 3d tensor of shape [imageHeight,imageWidth, depth],\n * where imageHeight and imageWidth must be positive.The image color\n * range should be [0, 255].\n * @param method Optional string from `'binary' | 'otsu'`\n * which specifies the method for thresholding. Defaults to 'binary'.\n * @param inverted Optional boolean whichspecifies\n * if colours should be inverted. Defaults to false.\n * @param threshValue Optional number which defines threshold value from 0 to 1.\n * Defaults to 0.5.\n * @return A 3d tensor of shape [imageHeight,imageWidth, depth], which\n * contains binarized image.\n */\n\nfunction threshold_(\n    image: Tensor3D | TensorLike,\n    method = 'binary',\n    inverted = false,\n    threshValue = 0.5\n): Tensor3D {\n    const $image = convertToTensor(image, 'image', 'threshold');\n\n    /* 0.2989, 0.5870, 0.1140 are represent luma coefficients in CCIR601.\n\tReference for converting between RGB and grayscale: https://en.wikipedia.org/wiki/Luma_%28video%29  */\n\n    const RED_INTENCITY_COEF = 0.2989;\n    const GREEN_INTENCITY_COEF = 0.5870;\n    const BLUE_INTENCITY_COEF = 0.1140;\n    const totalPixelsInImage = $image.shape[0] * $image.shape[1];\n\n    let $threshold = mul(tensor1d([threshValue]), 255);\n    let r, g, b, grayscale;\n\n    util.assert(\n        $image.rank === 3,\n        () => 'Error in threshold: image must be rank 3,' +\n            `but got rank ${$image.rank}.`);\n\n    util.assert(\n        $image.shape[2] === 3 || $image.shape[2]=== 1,\n        () => 'Error in threshold: ' +\n            'image color channel must be equal to 3 or 1' +\n            `but got ${$image.shape[2]}.`);\n\n    util.assert(\n      $image.dtype === 'int32' || $image.dtype === 'float32',\n      () => 'Error in dtype: image dtype must be int32 or float32,' +\n          `but got dtype ${$image.dtype}.`);\n\n    util.assert(\n      method === 'otsu' || method === 'binary',\n      () => `Method must be binary or otsu, but was ${method}`);\n\n    if ($image.shape[2] === 3) {\n        [r, g, b] = split($image, [1, 1, 1], -1);\n        const $r = mul(r,RED_INTENCITY_COEF);\n        const $g = mul(g,GREEN_INTENCITY_COEF);\n        const $b = mul(b,BLUE_INTENCITY_COEF);\n        grayscale = add(add($r, $g), $b);\n    } else {\n        grayscale = image;\n    }\n\n    if (method === 'otsu') {\n        const $histogram = bincount(cast(round(grayscale), 'int32') as Tensor1D,\n            tensor([]),\n            256);\n        $threshold = otsu($histogram, totalPixelsInImage);\n    }\n\n    const invCondition = inverted ?\n        lessEqual(grayscale, $threshold) : greater(grayscale, $threshold);\n\n    const result = cast(mul(invCondition,255), 'int32');\n\n    return result as Tensor3D;\n}\n\nfunction otsu(histogram: Tensor1D, total: number):Tensor1D {\n\n    let bestThresh = tensor1d([-1]);\n    let bestInBetVar = tensor1d([0]);\n    let cInBetVar = tensor1d([0]);\n    let classFirst, classSecond, meanFirst,\n        meanSec, weightForeground, weightBack;\n\n    for (let index = 0; index < histogram.size-1; index++) {\n\n        classFirst = slice(histogram, 0, index + 1);\n\n        classSecond = slice(histogram,index + 1);\n\n        weightForeground = div(sum(classFirst),total);\n\n        weightBack = div(sum(classSecond),total);\n\n        const meanFirstDivA = sum(mul(classFirst, range(0, classFirst.size)));\n\n        meanFirst = div(meanFirstDivA, sum(classFirst) );\n\n        const meanSecFill = fill(classSecond.shape, classFirst.size);\n        const meanSecAdd = add(range(0,classSecond.size),meanSecFill);\n        const meanSecMul = mul(classSecond, (meanSecAdd));\n        meanSec = div(sum(meanSecMul), sum(classSecond));\n\n        const cInBetVarSubA = sub(meanFirst, meanSec);\n        const cInBetVarSubB = sub(meanFirst, meanSec);\n        const cInBetVarMul = mul(weightForeground, weightBack);\n        cInBetVar = mul(mul(cInBetVarMul,cInBetVarSubA), cInBetVarSubB);\n\n        const condition = greater(cInBetVar, bestInBetVar);\n\n        bestInBetVar = where(condition, cInBetVar, bestInBetVar);\n\n        bestThresh = where(condition, tensor1d([index]), bestThresh);\n\n    }\n    return bestThresh;\n}\n\nexport const threshold = /* @__PURE__ */ op({ threshold_ });\n"]}
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