Yolov3-Implementation-Using-OpenCV

Implementing Yolov3 algorithm using OpenCV to detect different objects

Input	Output

Steps of implementation

1-Firstly run download_models.sh. This will download following three files:-

• coco.names (contains the names of all the detection objects)
• yolov3.weights (pretrained weights for the model)
• yolov3.cfg (configuration file of yolov3 algorithm)

2-Then run yolov3_run.py. The output will be stored in the format of video_name_yolo_out_py.avi for videos and image_name_yolo_out_py.jpg for images.

3-For running through command lines:-

• python3 yolov3_run.py --video=video_name.mp4
• python3 yolov3_run.py --image=image_name.jpg

File Structure

.
└── Yolov3-Implementation-Using-OpenCV
    ├── bash
    │   └── tree_structure.sh
    ├── download_models.sh
    ├── images
    │   ├── input-1.jpeg
    │   ├── input-2.jpeg
    │   ├── input-3.jpeg
    │   ├── output-1.jpg
    │   ├── output-2.jpg
    │   └── output-3.jpg
    ├── README.md
    └── yolov3_run.py

Downloading Models

coco.names (https://github.com/pjreddie/darknet/blob/master/data/coco.names?raw=true-O./coco.names)

yolov3.weights (https://pjreddie.com/media/files/yolov3.weights)

yolov3.cfg https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg?raw=true-O./yolov3.cfg)