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tensor akışı:: işlem:: Alanı Yeniden Boyutlandır
#include <image_ops.h> Alan enterpolasyonunu kullanarak images size göre yeniden boyutlandırın.
Özet
Giriş görüntüleri farklı türde olabilir ancak çıktı görüntüleri her zaman değişkendir.
Sınırlı sayısal kesinlik nedeniyle, çıktı görüntüsünün piksel değerleri aralığı, giriş görüntüsünün aralığından biraz farklı olabilir. Bir çıkış aralığını garanti etmek için (örneğin, [0.0, 1.0] , çıkışa tf.clip_by_value uygulayın.
Her çıkış pikseli, önce pikselin kapladığı alanı giriş tensörüne dönüştürerek ve ardından kapladığı alanla kesişen piksellerin ortalaması alınarak hesaplanır. Bir giriş pikselinin ortalamaya katkısı, kapladığı alanla kesişen alanın oranıyla ağırlıklandırılır. Bu, OpenCV'nin INTER_AREA'sı ile aynıdır.
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- görüntüler: şekilli 4-D
[batch, height, width, channels] . - size: = 2 öğeden oluşan 1 boyutlu bir int32 Tensörü :
new_height, new_width . Görüntüler için yeni boyut.
İsteğe bağlı özellikler (bkz. Attrs ):
- align_corners: True ise, giriş ve çıkış tensörlerinin 4 köşe pikselinin merkezleri, köşe piksellerindeki değerler korunarak hizalanır. Varsayılan olarak false olur.
İade:
-
Output : Şekilli 4-D [batch, new_height, new_width, channels] .
Genel özellikler
Kamu işlevleri
düğüm
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatör::tensorflow::Çıktı
operator::tensorflow::Output() const
Genel statik işlevler
Köşeleri Hizala
Attrs AlignCorners(
bool x
)
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Son güncelleme tarihi: 2025-07-27 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-27 UTC."],[],[],null,["# tensorflow::ops::ResizeArea Class Reference\n\ntensorflow::ops::ResizeArea\n===========================\n\n`#include \u003cimage_ops.h\u003e`\n\nResize `images` to `size` using area interpolation.\n\nSummary\n-------\n\n[Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input) images can be of different types but output images are always float.\n\nThe range of pixel values for the output image might be slightly different from the range for the input image because of limited numerical precision. To guarantee an output range, for example `[0.0, 1.0]`, apply `tf.clip_by_value` to the output.\n\nEach output pixel is computed by first transforming the pixel's footprint into the input tensor and then averaging the pixels that intersect the footprint. An input pixel's contribution to the average is weighted by the fraction of its area that intersects the footprint. This is the same as OpenCV's INTER_AREA.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- images: 4-D with shape `[batch, height, width, channels]`.\n- size: = A 1-D int32 [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) of 2 elements: `new_height, new_width`. The new size for the images.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resize-area/attrs#structtensorflow_1_1ops_1_1_resize_area_1_1_attrs)):\n\n- align_corners: If true, the centers of the 4 corner pixels of the input and output tensors are aligned, preserving the values at the corner pixels. Defaults to false.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 4-D with shape `[batch, new_height, new_width, channels]`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResizeArea](#classtensorflow_1_1ops_1_1_resize_area_1a48c3b130fbd05acaed9512549485f012)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` images, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` size)` ||\n| [ResizeArea](#classtensorflow_1_1ops_1_1_resize_area_1ac1b5d48c5c77399d5198780d905281d7)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` images, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` size, const `[ResizeArea::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resize-area/attrs#structtensorflow_1_1ops_1_1_resize_area_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resize_area_1a5cb2a40837fb9d975e2ca454469e5cac) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [resized_images](#classtensorflow_1_1ops_1_1_resize_area_1a64b25c97b7028b2b4c93978f2e957ad4) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_resize_area_1abdc62a6906daefaa326cda016f8fbb0c)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_resize_area_1a6e7fba9df05a54b4e0de2d079fa03403)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_resize_area_1a15a700424a492dfe07a1777ddc6146bd)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------|\n| [AlignCorners](#classtensorflow_1_1ops_1_1_resize_area_1ae8ffc21c407e98bddb149275984ed3cf)`(bool x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resize-area/attrs#structtensorflow_1_1ops_1_1_resize_area_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResizeArea::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resize-area/attrs) | Optional attribute setters for [ResizeArea](/versions/r2.1/api_docs/cc/class/tensorflow/ops/resize-area#classtensorflow_1_1ops_1_1_resize_area). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### resized_images\n\n```scdoc\n::tensorflow::Output resized_images\n``` \n\nPublic functions\n----------------\n\n### ResizeArea\n\n```gdscript\n ResizeArea(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input images,\n ::tensorflow::Input size\n)\n``` \n\n### ResizeArea\n\n```gdscript\n ResizeArea(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input images,\n ::tensorflow::Input size,\n const ResizeArea::Attrs & attrs\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``` \n\nPublic static functions\n-----------------------\n\n### AlignCorners\n\n```text\nAttrs AlignCorners(\n bool x\n)\n```"]]
