The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22

Last update: Nov 25, 2022

Related tags

Deep Learning SiamTPNTracker

Overview

SiamTPN

Introduction

This is the official implementation of the SiamTPN (WACV2022). The tracker intergrates pyramid feature network and transformer into Siamese network, achieving state-of-the-art performance (better than DiMP) while runing 30 FPS on a single CPU. The tracker optimized with ONXX and openvino could run at 45 FPS on cpu end, leading promising performance when deploying on drones for tracking.

[Paper] [Raw Results] [Drone Tracking Videos] [Models]

Training

prepare data

change the path in lib/train/admin/local.py to your data location

# Distributed training withh 4 nodes 
python -m torch.distributed.launch --nproc_per_node 4 tools/run_training.py --config shufflenet_l345_192

# single gpu training for test purpose
python tools/run_training.py --config shufflenet_l345_192

Test and evaluate SiamTPN

prepare data

change the path in lib/test/evaluation/local.py to your data location

running on cpu

# Download the pretrain model and put it under ./results/checkpoints/train/SiamTPN/ folder

python tools/test.py siamtpn shufflenet_l345_192 --dataset_name got10k_val --debug 1 --cpu 1 --epoch 100 --sequence GOT-10k_Val_000001

running on cpu with onnx optimized

The debug mode will show tracking results, more details refer to tools/test.py

Currently, onnx only support cpu version

First, you need to install onxx and onxxruningtime:

pip install onxx
# for onxx runining time, download the openvino version from release [page](https://github.com/intel/onnxruntime/releases/tag/v3.1) and install with
pip install onnxruntime_openvino-1.9.0-cp37-cp37m-linux_x86_64.whl

# please refer the [page](https://github.com/intel/onnxruntime/releases/tag/v3.1) for openvino installation details.

# Download the converted onnx model and put it under ./results/onnx/ folder
# or conver your own model with 
python tools/onnx_search.py
python tools/onnx_template.py

python tools/test.py siamtpn_onnx shufflenet_l345_192 --dataset_name got10k_val --debug 1 --cpu 1 --epoch 100 --sequence GOT-10k_Val_000001

Citation

Acknowledge

Our code is implemented based on the following libraries:

The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22

Related tags

Overview

SiamTPN

Introduction

Training

prepare data

Test and evaluate SiamTPN

prepare data

running on cpu

running on cpu with onnx optimized

Citation

Acknowledge

Owner

Robotics and Intelligent Systems Control @ NYUAD

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

NHS AI Lab Skunkworks project: Long Stayer Risk Stratification

Official code release for "GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis"

Watch faces morph into each other with StyleGAN 2, StyleGAN, and DCGAN!

PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

RoIAlign & crop_and_resize for PyTorch

optimization routines for hyperparameter tuning

A quantum game modeling of pandemic (QHack 2022)

A PyTorch Implementation of "Neural Arithmetic Logic Units"

Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

A task Provided by A respective Artenal Ai and Ml based Company to complete it

CSPML (crystal structure prediction with machine learning-based element substitution)

Flexible-CLmser: Regularized Feedback Connections for Biomedical Image Segmentation

An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022

Metadata-Extractor - Metadata Extractor Script can be used to read in exif metadata

Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Totally Versatile Miscellanea for Pytorch

Tensorflow port of a full NetVLAD network

Dynamic wallpaper generator.