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Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

How to download and setup Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

Open terminal and run command
git clone https://github.com/alen-smajic/Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning.git
git clone is used to create a copy or clone of Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning repositories. You pass git clone a repository URL.
it supports a few different network protocols and corresponding URL formats.

Also you may download zip file with Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning https://github.com/alen-smajic/Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning/archive/master.zip

Or simply clone Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning with SSH
[email protected]:alen-smajic/Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning.git

If you have some problems with Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

You may open issue on Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning support forum (system) here: https://github.com/alen-smajic/Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning/issues