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Search results for jupyter notebook lidar

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41 search results found

Pseudo_lidar ⭐ 555

(CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Dataset Api ⭐ 455

The ApolloScape Open Dataset for Autonomous Driving and its Application.

Kitti Dataset ⭐ 184

Visualising LIDAR data from KITTI dataset.

Pandaset Devkit ⭐ 170

Rellis 3d ⭐ 133

RELLIS-3D: A Multi-modal Dataset for Off-Road Robotics

Whiteboxgui ⭐ 115

An interactive GUI for WhiteboxTools in a Jupyter-based environment

Weakly Supervised 3d Object Detection ⭐ 85

Weakly Supervised 3D Object Detection from Point Clouds (VS3D), ACM MM 2020

Gedi_tutorials ⭐ 78

GEDI L3 and L4 Tutorials

Tensorflow implementation of Multi-View 3D Object Detection Network (in progress)

Fusion Ekf Python ⭐ 63

An extended Kalman Filter implementation in Python for fusing lidar and radar sensor measurements

Pointcloudsegmentation ⭐ 59

The research project based on Semantic KITTTI dataset, 3d Point Cloud Segmentation , Obstacle Detection

Visualizing Lidar Data ⭐ 45

Visualizing lidar data using Uber Autonomous Visualization System (AVS) and Jupyter Notebook Application

Lidar_generation ⭐ 41

Code for "Deep Generative Models for LiDAR Data"

Awesome Vehicle Datasets ⭐ 32

Deep Lidar Inertial Odometry

Denselidarnet ⭐ 29

LDLS (Label Diffusion LiDAR Segmentation) algorithm for instance segmentation of LiDAR point clouds.

a benchmark dataset for training and evaluating global cloud classification models.

F4g Oceania Pdal ⭐ 21

A workshop on PDAL for FOSS4G SotM Oceania 2018

Rl Obstacle Avoidance ⭐ 19

LIDAR based Obstacle Avoidance with Reinforcement Learning

A lidar-based Teach-and-Repeat framework designed to enable outdoor autonomous navigation in harsh weather.

Multi-person 3D panoramic localization tracking

Python For Remote Sensing ⭐ 15

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

pyGEDI is a Python Package for NASA's Global Ecosystem Dynamics Investigation (GEDI) mission, data extraction, analysis, processing and visualization.

Carla Kitti ⭐ 14

CARLA-KITTI generates synthetic data from the CARLA simulator for KITTI 2D/3D Object Detection task.

Lane Marking Detection ⭐ 14

This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.

Extended Kalman Filter ⭐ 11

3d_scanner ⭐ 10

blender python script to receive and process data from an arduino/lidar/mpu6050 based 3D_scanner

Didi_challenge_2017_python ⭐ 10

Goal of project was to detect vehicles and pedestrians using Lidar points in real time.

Atltvhead Gesture Recognition Bracer ⭐ 10

Atltvhead Gesture Recognition Bracer - A TensorflowLite gesture detector for the atltvhead project and for exploration into Data Science

Ros2 Ouster Tools ⭐ 9

Tools and utilities (not a driver) for working with Ouster LiDARs in ROS2.

Gpu Analytics Perf Tests ⭐ 9

A GPU-vs-CPU performance benchmark: (OmniSci [MapD] Core DB / cuDF GPU DataFrame) vs (Pandas DataFrame / Postgres / PDAL)

Forestlas ⭐ 7

code for generating metrics of forest vertical structure from airborne LiDAR data

3d Object Detection For Autonomous Vehicles ⭐ 6

Project on 3D Object Detection using Lyft's level5 dataset. Obtained mAP of 0.045 on the private leader board on kaggle and ranked in the top 20% among all teams participated in the competition.

Lidar_ground_plane_and_obstacles_detections ⭐ 6

Python and C++ examples that show shows how to process 3-D Lidar data by segmenting the ground plane and finding obstacles.

Adaptive Filtering Wizard

Kalman_filter_for_localization_using_python ⭐ 5

Kalman filters are really good at taking noisy sensor data and smoothing out the data to make more accurate predictions. For autonomous vehicles, Kalman filters can be used in object tracking. A Kalman filter does this by weighing the uncertainty in your belief about the location versus the uncertainty in the lidar or radar measurement. If your belief is very uncertain, the Kalman filter gives more weight to the sensor. If the sensor measurement has more uncertainty, your belief about the locati

Aws Open Data Satellite Lidar Tutorial ⭐ 5

This is the repository for OpenData tutorial content by MLSL.

Advancedobjectdetection ⭐ 5

Point Attention ⭐ 5

A python implementation of the Atmospheric Lidar Data Augmentation (ALiDAn) framework and a learning pipeline utilizing both ALiDAn's and raw data.

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