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Course submission material for Lidar point cloud based 3D Detection using Yolo, followed by Sensor Fusion and Camera Based Tracking using Extended Kalman Filters for Udacity Self Driving Nanodegree

License: Other

Python 99.93% Shell 0.07%
object-detection autonomous-driving yolo detection iou-calculation waymo-open-dataset mahalanobis-distance kalman-filter sensor-fusion

nd013-c2-sensor-fusion's Introduction

  • 👋 Hi, I’m @AmolGalande
  • 👀 I’m interested in Autonomous Driving Cars
  • 🌱 I’m currently learning Object Detection in Images using Machine Learning
  • 💞️ I’m looking to collaborate on ...
  • 📫 How to reach me linkedin.com/in/amol-galande

nd013-c2-sensor-fusion's People

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amolloma avatar mvirgo avatar sudkul avatar uanjali avatar

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nd013-c2-sensor-fusion's Issues

track list in loop over dataset.py

Hello there, I am currently working on the data association part using GNN. I am trying to use this code for 2d tracking where pedestrians are in the scene. I have only bounding box coordinates. I am trying to use this code for tracking part where the kalman filter is used. I have a problem at line 245 in loop_over_dataset.py. Please help me how to use the GNN in kalman filter with bounding box coordinates for a pedestrian and not with lidar and camera.

I hope you help. Thanks in advance!

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