49 lines
1.8 KiB
TypeScript
49 lines
1.8 KiB
TypeScript
/**
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* Copyright 2023 The MediaPipe Authors.
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*
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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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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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/** The output result of ImageSegmenter. */
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export class ImageSegmenterResult {
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constructor(
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/**
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* Multiple masks represented as `Float32Array` or `WebGLTexture`-backed
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* `MPImage`s where, for each mask, each pixel represents the prediction
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* confidence, usually in the [0, 1] range.
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*/
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readonly confidenceMasks?: MPMask[],
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/**
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* A category mask represented as a `Uint8ClampedArray` or
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* `WebGLTexture`-backed `MPImage` where each pixel represents the class
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* which the pixel in the original image was predicted to belong to.
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*/
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readonly categoryMask?: MPMask,
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/**
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* The quality scores of the result masks, in the range of [0, 1].
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* Defaults to `1` if the model doesn't output quality scores. Each
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* element corresponds to the score of the category in the model outputs.
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*/
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readonly qualityScores?: number[]) {}
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/** Frees the resources held by the category and confidence masks. */
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close(): void {
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this.confidenceMasks?.forEach(m => {
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m.close();
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});
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this.categoryMask?.close();
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}
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}
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