NgpdZddlZddlmZmZddlmZdZdZdZ d Z d Z Gd d e Z d e defdZdS)a1Base box coder. Box coders convert between coordinate frames, namely image-centric (with (0,0) on the top left of image) and anchor-centric (with (0,0) being defined by a specific anchor). Users of a BoxCoder can call two methods: encode: which encodes a box with respect to a given anchor (or rather, a tensor of boxes wrt a corresponding tensor of anchors) and decode: which inverts this encoding with a decode operation. In both cases, the arguments are assumed to be in 1-1 correspondence already; it is not the job of a BoxCoder to perform matching. N)ListOptional)BoxList faster_rcnnkeypoint mean_stddevsquaregHz>cbeZdZdZdefdeeedefdZdZ de de fd Z de fd Z dS) FasterRcnnBoxCoderzFaster RCNN box coder.N scale_factorsepscj||_|"t|dksJ|D] }|dksJ ||_dS)a0Constructor for FasterRcnnBoxCoder. Args: scale_factors: List of 4 positive scalars to scale ty, tx, th and tw. If set to None, does not perform scaling. For Faster RCNN, the open-source implementation recommends using [10.0, 10.0, 5.0, 5.0]. Nr)_scale_factorslenr)selfr rscalars ]/var/www/html/ai-engine/env/lib/python3.11/site-packages/effdet/object_detection/box_coder.py__init__zFasterRcnnBoxCoder.__init__>sT,  $}%%****' " "zzzzzcdS)Nr)rs r code_sizezFasterRcnnBoxCoder.code_sizeNsqrboxesanchorsc|\}}}}|\}}} } ||jz }||jz }| |jz } | |jz } ||z |z } ||z |z } tj| |z } tj| |z }|j@| |jdz} | |jdz} ||jdz}| |jdz} tj| | || gS)a Encode a box collection with respect to anchor collection. Args: boxes: BoxList holding N boxes to be encoded. anchors: BoxList of anchors. Returns: a tensor representing N anchor-encoded boxes of the format [ty, tx, th, tw]. Nrr) get_center_coordinates_and_sizesrtorchlogrstackt)rrr ycenter_a xcenter_ahawaycenterxcenterhwtxtytwths rencodezFasterRcnnBoxCoder.encodeQs(/'O'O'Q'Q$ 9b"!&!G!G!I!I!Q dh dh TX  TX  !R ' !R ' Yq2v   Yq2v     * $%a( (B $%a( (B $%a( (B $%a( (B{BB+,,..000rcB|\}}}}|\}}} } |j@||jdz}||jdz}| |jdz} | |jdz} t j| |z} t j| |z} ||z|z} ||z|z}| | dz z }|| dz z }| | dz z}|| dz z}t t j||||gS)zDecode relative codes to boxes. Args: rel_codes: a tensor representing N anchor-encoded boxes. anchors: BoxList of anchors. Returns: boxes: BoxList holding N bounding boxes. Nrrrrg@)r r$unbindrr!exprr#)r rel_codesrr%r&r'r(r.r-r0r/r,r+r)r*yminxminymaxxmaxs rdecodezFasterRcnnBoxCoder.decodeps5(/'O'O'Q'Q$ 9b""--//BB   * $%a( (B $%a( (B $%a( (B $%a( (B IbMMB  IbMMB r'I%r'I%RRRRu{D$d#;<<>>@@AAAr) __name__ __module__ __qualname____doc__EPSrrfloatrrrr1r:rrrr r ;s  >BQT  htE{&;      1G1g1111>BBBBBBBrr box_coderrcPt|jdksJ|jdkr3td|jdddt jfd|D}|S)aTDecode a batch of encoded boxes. This op takes a batch of encoded bounding boxes and transforms them to a batch of bounding boxes specified by their corners in the order of [y_min, x_min, y_max, x_max]. Args: encoded_boxes: a float32 tensor of shape [batch_size, num_anchors, code_size] representing the location of the objects. box_coder: a BoxCoder object. anchors: a BoxList of anchors used to encode `encoded_boxes`. Returns: decoded_boxes: a float32 tensor of shape [batch_size, num_anchors, coder_size] representing the corners of the objects in the order of [y_min, x_min, y_max, x_max]. Raises: ValueError: if batch sizes of the inputs are inconsistent, or if the number of anchors inferred from encoded_boxes and anchors are inconsistent. rrzjThe number of anchors inferred from encoded_boxes and anchors are inconsistent: shape[1] of encoded_boxes z+ should be equal to the number of anchors: .cFg|]}|jSr)r:r).0rrrAs r z batch_decode..s9!!!38 ((.!!!r)rshape num_boxes ValueErrorr!r#r3) encoded_boxesrAr decoded_boxess `` r batch_decoderLs* }" # #q ( ( ( (1!2!2!4!444j(-a000'2C2C2E2E2E2EGHH H K!!!!!r!typingrrbox_listr FASTER_RCNNKEYPOINT MEAN_STDDEVSQUAREr?objectr rLrrrrTs   !!!!!!!!     OBOBOBOBOBOBOBOBd+=r