Get guided anchors and loc masks for a single level. Args: square (tensor): Squares of a single level. shape_pred (te

Get the mask scores. mask_score = bbox_score * mask_iou

Get sampled approxs and inside flags according to feature map sizes. Args: featmap_sizes (list[tuple]): Multi-level feature map s

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression https://arxiv.org/abs/1902.09630 code refer to:

IoU loss. Computing the IoU loss between a set of predicted bboxes and target bboxes. The loss is calculated as negative log of IoU. Arg

Benchmark between async and synchronous inference interfaces. Sample runs for 20 demo images on K80 GPU, model - mask_rcnn_r50_fpn_1x:

Map rois to corresponding feature levels by scales. - scale < finest_scale * 2: level 0 - finest_scale * 2 <= scale < finest_scale *

Merge augmented proposals (multiscale, flip, etc.) Args: aug_proposals (list[Tensor]): proposals from different testing schem

Merge augmented detection bboxes and scores. Args: aug_bboxes (list[Tensor]): shape (n, 4*#class) aug_scores (list[Te

Test model with multiple gpus. This method tests model with multiple gpus and collects the results under two different modes: gpu and cpu mod

Parse information from a line in a requirements text file

Patch the forward method of a module. Args: func (callable): The original forward method. src_type (torch.dtype): Type of input a

Print mAP and results of each class. A table will be printed to show the gts/dets/recall/AP of each class and the mAP. Args: mea

Print recalls in a table. Args: recalls(ndarray): calculated from `bbox_recalls` proposal_nums(ndarray or list): top N proposals