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adafruit_circuitpython_bno055

CircuitPython driver for BNO055 absolute orientation sensor

allan_variance_ros

ROS compatible tool to generate Allan Deviation plots

bash-git-prompt

An informative and fancy bash prompt for Git users

byd_dataset_ws

catkin_simple

catkin, simpler

deepstream_lpr_app

Sample app code for LPR deployment on DeepStream

depth-anything

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

dino

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

drt-vio-init

The official repository of our CVPR2023 paper "A Rotation-Translation-Decoupled Solution for Robust and Efficient Visual-Inertial Initialization".

dso

Direct Sparse Odometry

fast-livo

A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).

file_player_sthereo_dataset

gmflow

[CVPR'22 Oral] GMFlow: Learning Optical Flow via Global Matching

hkustgz-mphil-proposal

infiray-sdk

thermal camera infiray SDK

kalibr

The Kalibr visual-inertial calibration toolbox

kalibr_allan

IMU Allan standard deviation charts for use with Kalibr and inertial kalman filters.

livox_camera_calib

This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.

livox_camera_lidar_calibration

Calibrate the extrinsic parameters between Livox LiDAR and camera

livox_ros_driver2

Livox device driver under Ros(Compatible with ros and ros2), support Lidar HAP and Mid-360.

mamba

multi-spectral-dataset

open_vins

An open source platform for visual-inertial navigation research.

opencv

Open Source Computer Vision Library

opencv_contrib

Repository for OpenCV's extra modules

opengv

OpenGV is a collection of computer vision methods for solving geometric vision problems. It is hosted and maintained by the Mobile Perception Lab of ShanghaiTech.

picai_labels

Annotations for the PI-CAI Challenge: Public Training and Development Dataset

products

超核电子产品资料

prostatemr_3d-cad-cspca

Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.

pytorch-superpoint

Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629