/UAV

Primary LanguagePython

UAV-traffic-analysis

This project aims to count every vehicle (bus, car, truck) detected in the input video using YOLOv5 object-detection algorithm. It also calculates speed, acceleration of every vehicle

DEMO

Demo GIF

Steps to run

  1. Clone this repository

    git clone https://github.com/Garvit-32/UAV.git

  2. Install all the dependencies

    pip install -r requirements.txt

  3. Collect 6-8 coordinates points (latitude, longitude) from google maps and (x, y) from the image and put it in Code/localization/localization_from_points.py from there you get the pixel delta (delta x, delta y) which is used to calculate distance, speed and acceleration of vehicle later.

    Localization

    In the given script, 8 points of this image are given, likewise you have to collect and put.

  4. Exceute main script to start tracking

    python Code/main.py -p <path to video> -o <latitude and longitude coordinate of the center of the frame > -pd < pixel delta calculated from localization script>

    Example

    python Code/main.py -p Input/DJI_0004_gt.mp4 -o "37.47646052, 126.89894" -pd "-2.00e-06, -2.00e-06"

  5. Evaluate Tracking (GroudTruth are required)

    python Code/tracking_eval/tracking_eval.py -p <Path to folder containing groundtruth> -v <video name>

    Example

    python Code/tracking_eval/tracking_eval.py -p Input/yolo_id -v DJI_0004_gt

    Tracking result for the given video are:

    MOTA 0.7994
    MOTP 0.7660
    Ground Truths 3884
    False Positives 757
    Misses 10
    Mismatches 12
    Correspondences 3874

References

  1. https://github.com/ultralytics/yolov5
  2. https://github.com/Videmo/pymot