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

Last update: Jan 08, 2023

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

A PyTorch version of You Only Look at One-level Feature object detector

Diverse Object-Scene Compositions For Zero-Shot Action Recognition

KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

Code for "3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop"

FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX.

Personal implementation of paper "Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval"

The self-supervised goal reaching benchmark introduced in Discovering and Achieving Goals via World Models

A Python Package for Convex Regression and Frontier Estimation

The code written during my Bachelor Thesis "Classification of Human Whole-Body Motion using Hidden Markov Models".

v objective diffusion inference code for PyTorch.

ScaleNet: A Shallow Architecture for Scale Estimation

This repository contains the code for designing risk bounded motion plans for car-like robot using Carla Simulator.

Implementation of CVPR'2022:Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors

Lightweight library to build and train neural networks in Theano

Jupyter notebooks for using & learning Keras

Sign Language Translation with Transformers (COLING'2020, ECCV'20 SLRTP Workshop)

Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification

Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator