Implementation of ICCV21 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers

Related tags

Deep Learningpnp-detr
Overview

Implementation of ICCV 2021 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers arxiv

This repository is based on detr

Recently, DETR pioneered the solution of vision tasks with transformers, it directly translates the image feature map into the object detection result. Though effective, translating the full feature map can be costly due to redundant computation on some area like the background. In this work, we encapsulate the idea of reducing spatial redundancy into a novel poll and pool (PnP) sampling module, with which we build an end-to-end PnP-DETR architecture that adaptively allocates its computation spatially to be more efficient. Concretely, the PnP module abstracts the image feature map into fine foreground object feature vectors and a small number of coarse background contextual feature vectors. The transformer models information interaction within the fine-coarse feature space and translates the features into the detection result. Moreover, the PnP-augmented model can instantly achieve various desired trade-offs between performance and computation with a single model by varying the sampled feature length, without requiring to train multiple models as existing methods. Thus it offers greater flexibility for deployment in diverse scenarios with varying computation constraint. We further validate the generalizability of the PnP module on panoptic segmentation and the recent transformer-based image recognition model ViT and show consistent efficiency gain. We believe our method makes a step for efficient visual analysis with transformers, wherein spatial redundancy is commonly observed.

PnP-DETR

Usage

First, clone the repository locally:

git clone https://github.com/twangnh/pnp-detr

Then, install PyTorch 1.5+ and torchvision 0.6+:

conda install -c pytorch pytorch torchvision

Install pycocotools (for evaluation on COCO) and scipy (for training):

conda install cython scipy
pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'

That's it, should be good to train and evaluate detection models.

(optional) to work with panoptic install panopticapi:

pip install git+https://github.com/cocodataset/panopticapi.git

Data preparation

Download and extract COCO 2017 train and val images with annotations from http://cocodataset.org. We expect the directory structure to be the following:

path/to/coco/
  annotations/  # annotation json files
  train2017/    # train images
  val2017/      # val images

Training

To train baseline DETR on a single node with 8 gpus for 300 epochs run:

python -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --coco_path /path/to/coco 

Following DETR, We train PnP-DETR with AdamW setting learning rate in the transformer to 1e-4 and 1e-5 in the backbone. Horizontal flips, scales an crops are used for augmentation. Images are rescaled to have min size 800 and max size 1333. The transformer is trained with dropout of 0.1, and the whole model is trained with grad clip of 0.1.

Evaluation

To evaluate DETR R50 on COCO val5k with a single GPU run:

python main.py --batch_size 2 --no_aux_loss --eval --resume xxx --coco_path /path/to/coco

Multinode training

Distributed training is available via Slurm and submitit:

pip install submitit

Train baseline DETR-6-6 model on 4 nodes for 300 epochs:

python run_with_submitit.py --timeout 3000 --coco_path /path/to/coco

License

DETR is released under the Apache 2.0 license. Please see the LICENSE file for more information.

Owner
twang
make things work
twang
Learning to Prompt for Continual Learning

Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr

Google Research 207 Jan 06, 2023
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced

Dominik Bauer 5 Jan 02, 2023
PyTorch implementation of Pay Attention to MLPs

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Jake Tae 34 Dec 13, 2022
使用深度学习框架提取视频硬字幕;docker容器免安装深度学习库,使用本地api接口使得界面和后端识别分离;

extract-video-subtittle 使用深度学习框架提取视频硬字幕; 本地识别无需联网; CPU识别速度可观; 容器提供API接口; 运行环境 本项目运行环境非常好搭建,我做好了docker容器免安装各种深度学习包; 提供windows界面操作; 容器为CPU版本; 视频演示 https

歌者 16 Aug 06, 2022
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.

signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled

Will Glad 1 Mar 11, 2022
Provide partial dates and retain the date precision through processing

Prefix date parser This is a helper class to parse dates with varied degrees of precision. For example, a data source might state a date as 2001, 2001

Friedrich Lindenberg 13 Dec 14, 2022
An open source library for face detection in images. The face detection speed can reach 1000FPS.

libfacedetection This is an open source library for CNN-based face detection in images. The CNN model has been converted to static variables in C sour

Shiqi Yu 11.4k Dec 27, 2022
Vision-and-Language Navigation in Continuous Environments using Habitat

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Jacob Krantz 132 Jan 02, 2023
Measures input lag without dedicated hardware, performing motion detection on recorded or live video

What is InputLagTimer? This tool can measure input lag by analyzing a video where both the game controller and the game screen can be seen on a webcam

Bruno Gonzalez 4 Aug 18, 2022
Repository of continual learning papers

Continual learning paper repository This repository contains an incomplete (but dynamically updated) list of papers exploring continual learning in ma

29 Jan 05, 2023
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag

Matthew Macy 606 Dec 21, 2022
Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm

Multi-band Spectro Radiomertric Image Analysis with K-means Cluster Algorithm Overview Multi-band Spectro Radiomertric images are images comprising of

Chibueze Henry 6 Mar 16, 2022
CryptoFrog - My First Strategy for freqtrade

cryptofrog-strategies CryptoFrog - My First Strategy for freqtrade NB: (2021-04-20) You'll need the latest freqtrade develop branch otherwise you migh

Robert Davey 137 Jan 01, 2023
fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.

fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.

Ali Abdalla 34 Jan 05, 2023
Multiview 3D object detection on MultiviewC dataset through moft3d.

Multiview Orthographic Feature Transformation for 3D Object Detection Multiview 3D object detection on MultiviewC dataset through moft3d. Introduction

Jiahao Ma 20 Dec 21, 2022
SNIPS: Solving Noisy Inverse Problems Stochastically

SNIPS: Solving Noisy Inverse Problems Stochastically This repo contains the official implementation for the paper SNIPS: Solving Noisy Inverse Problem

Bahjat Kawar 35 Nov 09, 2022
This is the official PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning".

Artistic Style Transfer with Internal-external Learning and Contrastive Learning This is the official PyTorch implementation of our paper: "Artistic S

51 Dec 20, 2022
Official PyTorch implementation of BlobGAN: Spatially Disentangled Scene Representations

BlobGAN: Spatially Disentangled Scene Representations Official PyTorch Implementation Paper | Project Page | Video | Interactive Demo BlobGAN.mp4 This

148 Dec 29, 2022
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.

ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We

haguettaz 12 Dec 10, 2022
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size

pogg 1.5k Jan 05, 2023