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tensor akışı:: işlem:: CropAndResizeGradBoxes
#include <image_ops.h> Crop_and_resize işleminin giriş kutusu tensörüne göre gradyanını hesaplar.
Özet
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- dereceler: 4 boyutlu bir şekil tensörü
[num_boxes, crop_height, crop_width, depth] . - resim: 4 boyutlu bir şekil tensörü
[batch, image_height, image_width, depth] . Hem image_height hem de image_width pozitif olması gerekir. - 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.
İsteğe bağlı özellikler (bkz. Attrs ):
- yöntem: Enterpolasyon yöntemini belirten bir dize. Şimdilik yalnızca 'bilinear' desteklenmektedir.
İade:
-
Output : [num_boxes, 4] şeklinde bir 2 boyutlu tensör.
Genel statik işlevler |
|---|
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: 2025-07-25 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-25 UTC."],[],[],null,["# tensorflow::ops::CropAndResizeGradBoxes Class Reference\n\ntensorflow::ops::CropAndResizeGradBoxes\n=======================================\n\n`#include \u003cimage_ops.h\u003e`\n\nComputes the gradient of the crop_and_resize op wrt the input boxes tensor.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/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- image: A 4-D tensor of shape `[batch, image_height, image_width, depth]`. Both `image_height` and `image_width` need to be positive.\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\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-boxes/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_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/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): A 2-D tensor of shape `[num_boxes, 4]`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [CropAndResizeGradBoxes](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1a7396286fdb983072f2291a1b8e42dd72)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grads, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` image, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` boxes, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` box_ind)` ||\n| [CropAndResizeGradBoxes](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1acb0082fa9451e89cacb7f33ec41ea71f)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grads, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` image, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` boxes, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` box_ind, const `[CropAndResizeGradBoxes::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-boxes/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1adaf9854fc96b856511f2dc5d98f970d9) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1aa787d871d3d2a6d4db396a999df47866) | `::`[tensorflow::Output](/versions/r2.0/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_boxes_1adc2ba9c9ad9db25b155a2c4d257cf17b)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1a31b45934d809d1528e55f1b32e7c4a42)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1aaffb6597bcce6544556871610729fbf6)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Method](#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1a40631e53f11d856a516a8a73adce1646)`(StringPiece x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-boxes/attrs#structtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::CropAndResizeGradBoxes::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/crop-and-resize-grad-boxes/attrs) | Optional attribute setters for [CropAndResizeGradBoxes](/versions/r2.0/api_docs/cc/class/tensorflow/ops/crop-and-resize-grad-boxes#classtensorflow_1_1ops_1_1_crop_and_resize_grad_boxes). |\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### CropAndResizeGradBoxes\n\n```gdscript\n CropAndResizeGradBoxes(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input grads,\n ::tensorflow::Input image,\n ::tensorflow::Input boxes,\n ::tensorflow::Input box_ind\n)\n``` \n\n### CropAndResizeGradBoxes\n\n```gdscript\n CropAndResizeGradBoxes(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input grads,\n ::tensorflow::Input image,\n ::tensorflow::Input boxes,\n ::tensorflow::Input box_ind,\n const CropAndResizeGradBoxes::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```"]]
