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.