| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { ENGINE } from '../../engine';
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| 18 | import { NonMaxSuppressionV5 } from '../../kernel_names';
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| 19 | import { convertToTensor } from '../../tensor_util_env';
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| 20 | import { nonMaxSuppSanityCheck } from '../nonmax_util';
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| 21 | import { op } from '../operation';
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| 22 | /**
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| 23 | * Performs non maximum suppression of bounding boxes based on
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| 24 | * iou (intersection over union).
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| 25 | *
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| 26 | * This op also supports a Soft-NMS mode (c.f.
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| 27 | * Bodla et al, https://arxiv.org/abs/1704.04503) where boxes reduce the score
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| 28 | * of other overlapping boxes, therefore favoring different regions of the image
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| 29 | * with high scores. To enable this Soft-NMS mode, set the `softNmsSigma`
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| 30 | * parameter to be larger than 0.
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| 31 | *
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| 32 | * @param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
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| 33 | * `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
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| 34 | * the bounding box.
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| 35 | * @param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
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| 36 | * @param maxOutputSize The maximum number of boxes to be selected.
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| 37 | * @param iouThreshold A float representing the threshold for deciding whether
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| 38 | * boxes overlap too much with respect to IOU. Must be between [0, 1].
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| 39 | * Defaults to 0.5 (50% box overlap).
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| 40 | * @param scoreThreshold A threshold for deciding when to remove boxes based
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| 41 | * on score. Defaults to -inf, which means any score is accepted.
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| 42 | * @param softNmsSigma A float representing the sigma parameter for Soft NMS.
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| 43 | * When sigma is 0, it falls back to nonMaxSuppression.
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| 44 | * @return A map with the following properties:
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| 45 | * - selectedIndices: A 1D tensor with the selected box indices.
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| 46 | * - selectedScores: A 1D tensor with the corresponding scores for each
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| 47 | * selected box.
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| 48 | *
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| 49 | * @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'}
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| 50 | */
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| 51 | function nonMaxSuppressionWithScore_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, softNmsSigma = 0.0) {
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| 52 | const $boxes = convertToTensor(boxes, 'boxes', 'nonMaxSuppression');
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| 53 | const $scores = convertToTensor(scores, 'scores', 'nonMaxSuppression');
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| 54 | const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);
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| 55 | maxOutputSize = params.maxOutputSize;
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| 56 | iouThreshold = params.iouThreshold;
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| 57 | scoreThreshold = params.scoreThreshold;
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| 58 | softNmsSigma = params.softNmsSigma;
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| 59 | const inputs = { boxes: $boxes, scores: $scores };
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| 60 | const attrs = { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };
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| 61 | // tslint:disable-next-line: no-unnecessary-type-assertion
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| 62 | const result = ENGINE.runKernel(NonMaxSuppressionV5, inputs, attrs);
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| 63 | return { selectedIndices: result[0], selectedScores: result[1] };
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| 64 | }
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| 65 | export const nonMaxSuppressionWithScore = op({ nonMaxSuppressionWithScore_ });
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| 66 | //# 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