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Obstacle and Lane Detection using YOLO and Lane-Net

Steps to execute:

  1. Extract the "ObstacleAndLaneDetection" project file from the submission.

  2. Download the weights of the pre-trained models from https://drive.google.com/drive/folders/1IX1seops2R8XgnBWfePeDMNAPhz2Yf9f?usp=sharing

  3. Extract and save the "models" folder in the LaneDetectionLaneNet folder.

  4. Extract and save the "yolo-coco" folder in the ObstacleDetectionYOLO folder.

  5. Execute the Test_Detections_On_Video.py file with the following arguments.

    python Test_Detections_On_Video.py --input ./test_video/lane_traffic.avi --output ./OUT/output_video.avi

  6. Check the results in the specified output directory or in the OUT directory.

Please check Project report pdf for more details.