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aliran tensor:: operasi:: NonMaxSuppressionDengan Tumpang Tindih
#include <image_ops.h> Dengan rakus memilih subset kotak pembatas dalam urutan skor yang menurun.
Ringkasan
memangkas kotak-kotak yang memiliki tumpang tindih tinggi dengan kotak-kotak yang dipilih sebelumnya. Kotak pembatas dengan skor kurang dari score_threshold akan dihapus. Nilai tumpang tindih N-kali-n diberikan dalam bentuk matriks persegi, yang memungkinkan untuk menentukan kriteria tumpang tindih khusus (misalnya perpotongan dengan kesatuan, perpotongan dengan luas, dll.).
Output dari operasi ini adalah sekumpulan bilangan bulat yang diindeks ke dalam kumpulan input kotak pembatas yang mewakili kotak yang dipilih. Koordinat kotak pembatas yang sesuai dengan indeks yang dipilih kemudian dapat diperoleh dengan menggunakan tf.gather operation . Misalnya:
indeks_yang dipilih = tf.image.non_max_suppression_with_overlaps( tumpang tindih, skor, ukuran_output_maks, ambang_tumpang tindih, ambang_skor) kotak_yang dipilih = tf.gather(kotak, indeks_yang dipilih)
Argumen:
- ruang lingkup: Objek Lingkup
- tumpang tindih: Tensor float 2-D dengan bentuk
[num_boxes, num_boxes] yang mewakili nilai tumpang tindih kotak n-kali-n. - skor: Tensor float 1-D berbentuk
[num_boxes] yang mewakili satu skor yang sesuai dengan setiap kotak (setiap baris kotak). - max_output_size: Tensor bilangan bulat skalar yang mewakili jumlah maksimum kotak yang akan dipilih dengan penekanan non-maks.
- overlap_threshold: Tensor float 0-D yang mewakili ambang batas untuk menentukan apakah kotak juga tumpang tindih.
- score_threshold: Tensor float 0-D yang mewakili ambang batas untuk memutuskan kapan harus menghapus kotak berdasarkan skor.
Pengembalian:
-
Output : Tensor bilangan bulat 1-D berbentuk [M] yang mewakili indeks yang dipilih dari kotak tensor, dengan M <= max_output_size .
Atribut publik
Fungsi publik
simpul
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Keluaran
operator::tensorflow::Output() const
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::NonMaxSuppressionWithOverlaps Class Reference\n\ntensorflow::ops::NonMaxSuppressionWithOverlaps\n==============================================\n\n`#include \u003cimage_ops.h\u003e`\n\nGreedily selects a subset of bounding boxes in descending order of score,.\n\nSummary\n-------\n\npruning away boxes that have high overlaps with previously selected boxes. Bounding boxes with score less than `score_threshold` are removed. N-by-n overlap values are supplied as square matrix, which allows for defining a custom overlap criterium (eg. intersection over union, intersection over area, etc.).\n\nThe output of this operation is a set of integers indexing into the input collection of bounding boxes representing the selected boxes. The bounding box coordinates corresponding to the selected indices can then be obtained using the `tf.gather operation`. For example:\n\nselected_indices = tf.image.non_max_suppression_with_overlaps( overlaps, scores, max_output_size, overlap_threshold, score_threshold) selected_boxes = tf.gather(boxes, selected_indices)\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- overlaps: A 2-D float tensor of shape `[num_boxes, num_boxes]` representing the n-by-n box overlap values.\n- scores: A 1-D float tensor of shape `[num_boxes]` representing a single score corresponding to each box (each row of boxes).\n- max_output_size: A scalar integer tensor representing the maximum number of boxes to be selected by non max suppression.\n- overlap_threshold: A 0-D float tensor representing the threshold for deciding whether boxes overlap too.\n- score_threshold: A 0-D float tensor representing the threshold for deciding when to remove boxes based on score.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): A 1-D integer tensor of shape `[M]` representing the selected indices from the boxes tensor, where `M \u003c= max_output_size`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [NonMaxSuppressionWithOverlaps](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1af965488437d8cbc7c79e1c36eca2abb3)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` overlaps, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` scores, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_output_size, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` overlap_threshold, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` score_threshold)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1a2f05b95bdafce0c5fc4a8269b35709e3) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [selected_indices](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1ab9ac497f027b7104d8ba5463a5a487ca) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1a77c8843216c117ea9cc2597027f4a20e)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1a46f0366220ce965998602e5248c93070)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_non_max_suppression_with_overlaps_1a636de2d3e1a950d52efadd9bff02eb59)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### selected_indices\n\n```scdoc\n::tensorflow::Output selected_indices\n``` \n\nPublic functions\n----------------\n\n### NonMaxSuppressionWithOverlaps\n\n```gdscript\n NonMaxSuppressionWithOverlaps(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input overlaps,\n ::tensorflow::Input scores,\n ::tensorflow::Input max_output_size,\n ::tensorflow::Input overlap_threshold,\n ::tensorflow::Input score_threshold\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
