^jdZddlZddlmcmZddlmZdejdejfdZ dejdejfdZ dejd ejde ejejffd Z dejd ejdejfd Z d ejdejfd ZdejdejdejfdZej j#eZdejdejdejfdZej j#eZy)z1Utilities for bounding box manipulation and GIoU.N)box_areaxreturnc|jd\}}}}|d|jdzz |d|jdzz |d|jdzz|d|jdzzg}tj|dS)Ng?gmindim)unbindclamptorchstack)rx_cy_cwhbs c/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/rfdetr/utilities/box_ops.pybox_cxcywh_to_xyxyrsXXb\NCa sQWWW%% % sQWWW%% % sQWWW%% % sQWWW%% %  A ;;qb !!c|jd\}}}}||zdz ||zdz ||z ||z g}tj|dS)Nrr )r rr)rx0y0x1y1rs rbox_xyxy_to_cxcywhr#sNXXb\NBB r'QbA R27>!Q .DAq Q[[^ #F NN1  ! !" %a (E    4 < nmrN)sigmoidr?reinsumsum)rJrK numerator denominatorlosss rbatch_dice_lossrTqs}^^ F ^^A FELLfg>>I**R.D)GKKOD!G,DDKi!m a@@D Krc:|jd}tj|tj|d}tj|tj |d}tj d||tj d|d|z z}||z S)aCompute sigmoid cross-entropy loss for mask predictions. Args: inputs: A float tensor of arbitrary shape. The predictions for each example. targets: A float tensor with the same shape as inputs. Stores the binary classification label for each element in inputs (0 for the negative class and 1 for the positive class). Returns: Loss tensor. r"none) reductionrM)r:F binary_cross_entropy_with_logitsr ones_like zeros_likerO)rJrKhwposnegrSs rbatch_sigmoid_ce_lossr_s aB , ,VU__V5LX^ _C , ,VU5E5Ef5MY_ `C << S' 2U\\+sUVY`U`5b bD "9r)__doc__rtorch.nn.functionalnn functionalrXtorchvision.ops.boxesrTensorrrtupler,r/rIrTjitscriptbatch_dice_loss_jitr_batch_sigmoid_ce_loss_jitrrrls<"8 *"%,,"5<<""%,,"5<<"ELL%,,5u||A[;\0' 'ell'u||'(8%,,85<<86 ELL 5<< ELL  ii&&7%,,%,,*"II,,-BCr