Internship-SelfDrivingCar

Self driving car level 2 (longitudinal and lateral) from depth camera, GNSS, IMU, and wheel odometry

baseline_line_finding_yolov5

conda create -n fsd_env python=3.8
conda activate fsd_env
cd baseline_lane_finding_yolov5/
pip install -r requirements.txt
python track.py --source close_calls.mp4 --show-vid # from video
python track.py --source close_calls.mp4 --show-vid # from webcam

yolop_lane_finding

conda create --name fsd --clone fsd_env
conda activate fsd
cd yolop/
pip install -r requirements.txt
python tools/demo.py --source videos/jalan_tol.mp4 --device 0 # from video, --device 0 is cuda
python tools/demo.py --source 0 --device 0 # from webcam and using cuda

yolov9_custom_object_detection

conda create -n yolov9_env python=3.9
conda activate yolov9_env
cd yolov9_custom_object_detection/
pip install -r requirements.txt
python detect_dual.py --source 'videos/jalan_tol.mp4' --img 640 --device 0 --weights 'runs/train/yolov9-m-finetuning/weights/best.pt' --name yolov9_m_640