This module converts the model's output into the format expected by the coco api

This class converts the output of the model to the final panoptic result, in the format expected by the coco panoptic API

Track a series of values and provide access to smoothed values over a window or the global series average.

Vision Transformer with support for global average pooling

This is the DETR module that performs object detection

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).

Masked Autoencoder with VisionTransformer backbone

This is a more standard version of the position embedding, very similar to the one used by the Attention is all you need paper, generalized t

Calculating Average Precision

ResNet backbone with frozen BatchNorm.

Class to convert 3DETR MLP head outputs into bounding boxes

A callable which takes a dataset dict in Detectron2 Dataset format, and map it into a format used by DETR. The callable currently does t

This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no

RandomCuboid augmentation from DepthContrast [https://arxiv.org/abs/2101.02691] We slightly modify this operation to account for object detec

RandomCuboid augmentation from DepthContrast [https://arxiv.org/abs/2101.02691] We slightly modify this operation to account for object detec

This class computes the loss for DETR. The process happens in two steps: 1) we compute hungarian assignment between ground truth boxes an

Track a series of values and provide access to smoothed values over a window or the global series average.

Track a series of values and provide access to smoothed values over a window or the global series average.

Extension of the Trainer class adapted to DETR.

f''' Chamder Distance L1

f''' Chamder Distance L2

This is a 2D attention module, which only returns the attention softmax (no multiplication by value)

Very simple multi-layer perceptron (also called FFN)

Simple convolutional head, using group norm. Upsampling is done using a FPN approach

This is a thin wrapper around D2's backbone to provide padding masking

Main 3DETR model. Consists of the following learnable sub-models - pre_encoder: takes raw point cloud, subsamples it and projects into "D" di

2D Image to Patch Embedding

Absolute pos embedding, learned.

Extension of the Trainer class adapted to DETR.

f''' emd

Calculating Average Precision

Used for nn.Transformer that uses a HW x N x C rep

Used for nn.Transformer that uses a HW x N x C rep

f''' Chamder Distance L2

croped point clouds with class label from sunrbgd validation set

Implement Detr

BatchNorm2d where the batch statistics and the affine parameters are fixed. Copy-paste from torchvision.misc.ops with added eps before rqsrt