Deep Inertial Prediction (DIPr)

Related tags

Deep Learningdipr
Overview

Deep Inertial Prediction

For more information and context related to this repo, please refer to our website.

Getting Started (non Docker)

Note: you will need to have pytorch installed (tested with 1.8 and higher)

python3 -m venv <venv_path>
source <venv_path>/bin/activate

git clone https://github.com/arcturus-industries/dipr.git && cd dipr
pip3 install -e .
python3 dipr/evaluate.py --challenge_folder <data_path>

Getting Started (with Docker)

You will need docker and realpath commands to be installed

git clone https://github.com/arcturus-industries/dipr.git && cd dipr
# on x86_64 systems
./build-and-run.sh <data_path>
# on arm64 systems (like mac M1)
./build-and-run-aarch64.sh <data_path>

M1 Mac note: You can use either the X86_64 container or the arm64 container. If you use the x86_64 container, you may see "Could not initialize NNPACK! Reason: Unsupported hardware." This is only a warning. It will however take a long time to run (about 30 minutes or longer after the docker build finishes)

Package Content

  • dataset.py - sample API to read the challenge hdf5 dataset format
  • cnn_backend.py - a file with CNN inference backends (currenly only TorchScript is supported). If you plan to work on a DL inference framework other than TorchScript, implement it there
  • noise_utils.py - a file with noise calibration and parameters, you may adjust them to generate your own noise levels
  • imu_fallback.py - a sample implmentation of ImuFallback with CNN velocity measurements
  • utils.py - auxiliary tools
  • evaluate.py - sample test script that runs ImuFallback on available datasets and outputs Mean Absolute Velocity metric

Running sample evaluation script

python3 evaluate.py --challenge_folder <data_path>

or for the docker versions

# on x86_64 systems
./build-and-run.sh <data_path>
# on arm64 systems (like mac M1)
./build-and-run-aarch64.sh <data_path>

It will output something like:

python3.9 evaluate.py -df shared
Dataset OpenVR_2021-09-02_17-40-34-synthetic, segments durations [7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0 ] sec
Processing datasets: 100%|██████████| 1/1 [05:04<00:00, 304.92s/files]
all_vel_mae_cnn 2.12cm/s
all_vel_mae_fallback 9.73cm/s
all_pose_mae_fallback 15.51cm

Which mean it found OpenVR_2021-09-02_17-40-34-synthetic test dataset, and executed ImuFallback on 13 segments of duration 7 seconds, and estimated over them averaged Mean Absolute Velocity Error as 9.73cm/s

It also outputs image with tracking plots to <challenge_folder_root>/_results/<datasetname>.png. There are plots for IMU only tracking, ImuFallback + CNN traking and ground truth

Challenge folder Content

train_synthetic - a folder with train datasets, available after sign-up https://dipr.ai/sign-up

test_synthetic - a folder where evaluation script looks for test datasets (we share only one example dataset)

_results - a folder where evaluation script stores some results

pretrained - an example CNN model we ship

Known Issues

Installing dependencies natively on Apple Silicon may fail with the following:

> pip3 install -e .
...
    error: Command "clang -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -iwithsysroot/System/Library/Frameworks/System.framework/PrivateHeaders -iwithsysroot/Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.8/Headers -arch arm64 -arch x86_64 -Werror=implicit-function-declaration -ftrapping-math -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -DNO_ATLAS_INFO=3 -DHAVE_CBLAS -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/core/src/common -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/core/src/umath -Inumpy/core/include -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/core/include/numpy -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/distutils/include -Inumpy/core/src/common -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/src/npysort -Inumpy/core/src/_simd -I<venv_path>/include -I/Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.8/include/python3.8 -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/core/src/common -Ibuild/src.macosx-10.14-x86_64-3.8/numpy/core/src/npymath -c numpy/core/src/multiarray/dragon4.c -o build/temp.macosx-10.14-x86_64-3.8/numpy/core/src/multiarray/dragon4.o -MMD -MF build/temp.macosx-10.14-x86_64-3.8/numpy/core/src/multiarray/dragon4.o.d -msse3 -I/System/Library/Frameworks/vecLib.framework/Headers" failed with exit status 1
    ----------------------------------------
    ERROR: Failed building wheel for numpy

Workaround: use the Docker instructions

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

Owner
Arcturus Industries
Arcturus Industries
Convex optimization for fun and profit.

CFMM Optimal Routing This repository contains the code needed to generate the figures used in the paper Optimal Routing for Constant Function Market M

Guillermo Angeris 183 Dec 29, 2022
Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation

Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation Official PyTorch implementation for the paper Look

Rishabh Jangir 20 Nov 24, 2022
Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training".

Mixup-Data-Dependency Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training". Running Alternating Line Exp

Muthu Chidambaram 0 Nov 11, 2021
Multi-task yolov5 with detection and segmentation based on yolov5

YOLOv5DS Multi-task yolov5 with detection and segmentation based on yolov5(branch v6.0) decoupled head anchor free segmentation head README中文 Ablation

150 Dec 30, 2022
Anonymize BLM Protest Images

Anonymize BLM Protest Images This repository automates @BLMPrivacyBot, a Twitter bot that shows the anonymized images to help keep protesters safe. Us

Stanford Machine Learning Group 40 Oct 13, 2022
Video-based open-world segmentation

UVO_Challenge Team Alpes_runner Solutions This is an official repo for our UVO Challenge solutions for Image/Video-based open-world segmentation. Our

Yuming Du 84 Dec 22, 2022
Wider-Yolo Kütüphanesi ile Yüz Tespit Uygulamanı Yap

WIDER-YOLO : Yüz Tespit Uygulaması Yap Wider-Yolo Kütüphanesinin Kullanımı 1. Wider Face Veri Setini İndir Train Dataset Val Dataset Test Dataset Not:

Kadir Nar 6 Aug 22, 2022
A coin flip game in which you can put the amount of money below or equal to 1000 and then choose heads or tail

COIN_FLIPPY ##This is a simple example package. You can use Github-flavored Markdown to write your content. Coinflippy A coin flip game in which you c

2 Dec 26, 2021
basic tutorial on pytorch

Quick Tutorial on PyTorch PyTorch Basics Linear Regression Logistic Regression Artificial Neural Networks Convolutional Neural Networks Recurrent Neur

7 Sep 15, 2022
Official code base for the poster "On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation" published in NeurIPS 2021 Workshop (SVRHM)

Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio

Binxu 8 Aug 17, 2022
Python Auto-ML Package for Tabular Datasets

Tabular-AutoML AutoML Package for tabular datasets Tabular dataset tuning is now hassle free! Run one liner command and get best tuning and processed

Sagnik Roy 18 Nov 20, 2022
multimodal transformer

This repo holds the code to perform experiments with the multimodal autoregressive probabilistic model Transflower. Overview of the repo It is structu

Guillermo Valle 68 Dec 13, 2022
Deep Sea Treasure Environment for Multi-Objective Optimization Research

DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip

imec IDLab 6 Nov 14, 2022
ATAC: Adversarially Trained Actor Critic

ATAC: Adversarially Trained Actor Critic Adversarially Trained Actor Critic for Offline Reinforcement Learning by Ching-An Cheng*, Tengyang Xie*, Nan

Microsoft 41 Dec 08, 2022
Code for BMVC2021 paper "Boundary Guided Context Aggregation for Semantic Segmentation"

Boundary-Guided-Context-Aggregation Boundary Guided Context Aggregation for Semantic Segmentation Haoxiang Ma, Hongyu Yang, Di Huang In BMVC'2021 Pape

Haoxiang Ma 31 Jan 08, 2023
The Generic Manipulation Driver Package - Implements a ROS Interface over the robotics toolbox for Python

Armer Driver Armer aims to provide an interface layer between the hardware drivers of a robotic arm giving the user control in several ways: Joint vel

QUT Centre for Robotics (QCR) 13 Nov 26, 2022
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)

CM-NAS Official Pytorch code of paper CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification in ICCV2021. Vis

JDAI-CV 40 Nov 25, 2022
Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing"

ProxyFL Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing" Authors: Shivam Kalra*, Junfeng Wen*, Jess

Layer6 Labs 14 Dec 06, 2022
Face-Recognition-based-Attendance-System - An implementation of Attendance System in python.

Face-Recognition-based-Attendance-System A real time implementation of Attendance System in python. Pre-requisites To understand the implentation of F

Muhammad Zain Ul Haque 1 Dec 31, 2021
Spatiotemporal resampling methods for mlr3

mlr3spatiotempcv Package website: release | dev Spatiotemporal resampling methods for mlr3. This package extends the mlr3 package framework with spati

45 Nov 21, 2022