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tensoreflusso:: ops:: ResizeArea
#include <image_ops.h>
size
images
utilizzando l'interpolazione dell'area.
Riepilogo
Le immagini di input possono essere di diversi tipi ma le immagini di output sono sempre float.
L'intervallo dei valori dei pixel per l'immagine di output potrebbe essere leggermente diverso dall'intervallo dell'immagine di input a causa della precisione numerica limitata. Per garantire un intervallo di output, ad esempio [0.0, 1.0]
, applicare tf.clip_by_value
all'output.
Ogni pixel di output viene calcolato trasformando prima l'impronta del pixel nel tensore di input e quindi calcolando la media dei pixel che intersecano l'impronta. Il contributo di un pixel di input alla media è ponderato in base alla frazione della sua area che interseca l'impronta. Questo è lo stesso di INTER_AREA di OpenCV.
Argomenti:
- scope: un oggetto Scope
- immagini: 4-D con forma
[batch, height, width, channels]
. - size: = A 1-D int32 Tensore di 2 elementi:
new_height, new_width
. La nuova dimensione per le immagini.
Attributi facoltativi (vedi Attrs
):
- align_corners: se vero, i centri dei 4 pixel d'angolo dei tensori di input e output sono allineati, preservando i valori nei pixel d'angolo. Il valore predefinito è falso.
Resi:
-
Output
: 4-D con forma [batch, new_height, new_width, channels]
.
Attributi pubblici
Funzioni pubbliche
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatore::tensorflow::Output
operator::tensorflow::Output() const
Funzioni pubbliche statiche
Allinea angoli
Attrs AlignCorners(
bool x
)
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-27 UTC.
[null,null,["Ultimo aggiornamento 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/r2.3/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/r2.3/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/r2.3/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/r2.3/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/r2.3/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/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` images, ::`[tensorflow::Input](/versions/r2.3/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/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` images, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` size, const `[ResizeArea::Attrs](/versions/r2.3/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/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [resized_images](#classtensorflow_1_1ops_1_1_resize_area_1a64b25c97b7028b2b4c93978f2e957ad4) | `::`[tensorflow::Output](/versions/r2.3/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/r2.3/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/r2.3/api_docs/cc/struct/tensorflow/ops/resize-area/attrs) | Optional attribute setters for [ResizeArea](/versions/r2.3/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```"]]