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tensor akışı:: işlem:: CropAndResizeGradImage
#include <image_ops.h> Crop_and_resize işleminin giriş görüntüsü tensörüne göre gradyanını hesaplar.
Özet
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- dereceler: 4 boyutlu bir şekil tensörü
[num_boxes, crop_height, crop_width, depth] . - kutular:
[num_boxes, 4] şeklindeki 2 boyutlu tensör. Tensörün i satırı box_ind[i] görüntüsündeki bir kutunun koordinatlarını belirtir ve normalleştirilmiş koordinatlar [y1, x1, y2, x2] ile belirtilir. y normalleştirilmiş bir koordinat değeri y * (image_height - 1) adresindeki görüntü koordinatına eşlenir, böylece normalleştirilmiş görüntü yüksekliğinin [0, 1] aralığı, görüntü yüksekliği koordinatlarında '[0, image_height - 1]'e eşlenir. y1 > y2'ye izin veririz; bu durumda örneklenen kırpma, orijinal görüntünün yukarı-aşağı çevrilmiş versiyonu olur. Genişlik boyutu da benzer şekilde ele alınır. [0, 1] aralığının dışındaki normalleştirilmiş koordinatlara izin verilir; bu durumda giriş görüntüsü değerlerini tahmin etmek için extrapolation_value kullanırız. - box_ind:
[0, batch) içindeki int32 değerlerine sahip [num_boxes] şeklindeki 1 boyutlu tensör. box_ind[i] değeri, i kutunun başvurduğu görüntüyü belirtir. - image_size: Orijinal görüntü boyutunu içeren
[batch, image_height, image_width, depth] değerine sahip 1 boyutlu tensör. Hem image_height hem de image_width pozitif olması gerekir.
İsteğe bağlı özellikler (bkz. Attrs ):
- yöntem: Enterpolasyon yöntemini belirten bir dize. Şimdilik yalnızca 'çift doğrusal' desteklenmektedir.
İade:
-
Output : Şekil [batch, image_height, image_width, depth] şeklinde 4 boyutlu tensör.
Yapıcılar ve Yıkıcılar |
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CropAndResizeGradImage (const :: tensorflow::Scope & scope, :: tensorflow::Input grads, :: tensorflow::Input boxes, :: tensorflow::Input box_ind, :: tensorflow::Input image_size, DataType T)
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CropAndResizeGradImage (const :: tensorflow::Scope & scope, :: tensorflow::Input grads, :: tensorflow::Input boxes, :: tensorflow::Input box_ind, :: tensorflow::Input image_size, DataType T, const CropAndResizeGradImage::Attrs & attrs)
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Genel statik işlevler |
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Method (StringPiece x) | |
Genel özellikler
Kamu işlevleri
düğüm
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatör::tensorflow::Çıktı
operator::tensorflow::Output() const
Genel statik işlevler
Yöntem
Attrs Method(
StringPiece x
)
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Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::CropAndResizeGradImage Class Reference\n\ntensorflow::ops::CropAndResizeGradImage\n=======================================\n\n`#include \u003cimage_ops.h\u003e`\n\nComputes the gradient of the crop_and_resize op wrt the input image tensor.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- grads: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.\n- boxes: A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensor specifies the coordinates of a box in the `box_ind[i]` image and is specified in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of `y` is mapped to the image coordinate at `y * (image_height - 1)`, so as the `[0, 1]` interval of normalized image height is mapped to \\`\\[0, image_height - 1\\] in image height coordinates. We do allow y1 \\\u003e y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the `[0, 1]` range are allowed, in which case we use `extrapolation_value` to extrapolate the input image values.\n- box_ind: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`. The value of `box_ind[i]` specifies the image that the `i`-th box refers to.\n- image_size: A 1-D tensor with value `[batch, image_height, image_width, depth]` containing the original image size. Both `image_height` and `image_width` need to be positive.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-image/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1_1_attrs)):\n\n- method: A string specifying the interpolation method. Only 'bilinear' is supported for now.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): A 4-D tensor of shape `[batch, image_height, image_width, depth]`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [CropAndResizeGradImage](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1a542871b76c83a2a8ae095c5ade81ab0e)`(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)` grads, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` boxes, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` box_ind, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` image_size, DataType T)` ||\n| [CropAndResizeGradImage](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1a5314c519439a0018be03ae0599c320d3)`(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)` grads, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` boxes, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` box_ind, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` image_size, DataType T, const `[CropAndResizeGradImage::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-image/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1ad757af122f700a9ab5acbd38629f83fb) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1adc227b21eb0d9d4ca672f34f67b7943d) | `::`[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_crop_and_resize_grad_image_1a614b37524e5b31e34837f59518d54830)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1a561ea8804d44d30b5d50d84b6619a89c)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1a189d45da47ace193a132f998417286d2)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Method](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1a10a7af8fef715e541d4c1c1472871fa5)`(StringPiece x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-image/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_image_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::CropAndResizeGradImage::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-image/attrs) | Optional attribute setters for [CropAndResizeGradImage](/versions/r1.15/api_docs/cc/class/tensorflow/ops/crop-and-resize-grad-image#classtensorflow_1_1ops_1_1_crop_and_resize_grad_image). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### CropAndResizeGradImage\n\n```gdscript\n CropAndResizeGradImage(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input grads,\n ::tensorflow::Input boxes,\n ::tensorflow::Input box_ind,\n ::tensorflow::Input image_size,\n DataType T\n)\n``` \n\n### CropAndResizeGradImage\n\n```gdscript\n CropAndResizeGradImage(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input grads,\n ::tensorflow::Input boxes,\n ::tensorflow::Input box_ind,\n ::tensorflow::Input image_size,\n DataType T,\n const CropAndResizeGradImage::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### Method\n\n```text\nAttrs Method(\n StringPiece x\n)\n```"]]
