/Vehicles_YOLOv5_DeepSORT

Vehicle detection by YOLOv5 and tracking by DeepSORT and counting

Primary LanguagePython

Vehicle detection by YOLOv5 and tracking by DeepSORT and counting

Introduction

The detections algorithm generated by YOLOv5 The tracking algorithm generated by Deep Sort Counting vehicles in area using pointPolygonTest

Setting before run tracker:

  1. Create new folder:
  2. Run Virtual Environment:
  3. Git clone: git clone https://github.com/hiimjulyy0307/yolov5_deepsort_counting_vehicles.git
  4. Install package: pip install -r requirements.txt

if u have nvidia gpu install this:

  1. CUDA Deep Neural Network (cuDNN)
  2. Setting cuDNN global folder
  3. Install pytorch versions PyTorch Im using cudnn 11.6 so pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116

Setting file track!

Make sure that you Run Virtual Environment before you run :D

  1. File Track.py detect + tracking and not counting

  2. File Track2.py detect + tracking and counting vehicles using YOLOv5l.pt (you can changes version of YOLOv5 n s m l x)

  3. File Track3.py detect + tracking and counting vehicles using Custom training model (vietnamese version - base on yolov5s.pt)

  4. Can changes variable about yolo_model, deep_sort_model, source, ... from line 320 and up.

    parser.add_argument('--yolo_model', nargs='+', type=str, default='yolov5l.pt', help='model.pt path(s)')
    parser.add_argument('--deep_sort_model', type=str, default='osnet_x0_25')
    parser.add_argument('--source', type=str, default='videos\hihi.mp4', help='source')  # file/folder, 0 for webcam
    parser.add_argument('--output', type=str, default='inference/output', help='output folder')  # output folder
    parser.add_argument('--imgsz', '--img', '--img-size', nargs='+', type=int, default=[640], help='inference size h,w')
    parser.add_argument('--conf-thres', type=float, default=0.5, help='object confidence threshold')
    parser.add_argument('--iou-thres', type=float, default=0.5, help='IOU threshold for NMS')
    parser.add_argument('--fourcc', type=str, default='mp4v', help='output video codec (verify ffmpeg support)')
    parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') 
    parser.add_argument('--show-vid', action='store_false', help='display tracking video results')
    parser.add_argument('--save-vid', action='store_true', help='save video tracking results')
    parser.add_argument('--save-txt', action='store_true', help='save MOT compliant results to *.txt')

Run

$ python track.py 
         track2.py
         track3.py

Thanks