balajisrinivas/Object-Detection-on-images-using-YOLO

Object Detection on images using YOLO

YOLO (You Only Look Once) is a very powerful and a fast algorithm in object detection. A strong understanding of the algorithm is essential before we start to code.

Some important papers to start with -

There are three papers you need to go through (Maybe difficult to understand initially, but worth reading it)

• You Only Look Once: Unified, Real-Time Object Detection
• YOLO9000: Better, Faster, Stronger
• YOLOv3: An Incremental Improvement

We are going to use YOLO v3 for our coding purpose in this repository.

Before going to code, we need to download some important YOLO files. It's the folder that's present in this repository as yolo-coco

The three files that needs to be downloaded are -

• coco.names
• yolov3.cfg
• yolov3.weights

Download these files and save it inside a folder. Name the folder anything you wish, but I have named it as yolo-coco just because of the fact that we are going to use the coco dataset objects.

Create a folder images and have some pictures inside it to test the object detection.

The yolo.py has the script to detect the objects in the images.

Make sure you have numpy and opencv installed. If not install them using pip

pip install numpy
pip install opencv-python

I am using the numpy version 1.17.4 and opencv version 3.4.2

You can now run the file by giving this command on your command promt

python yolo.py --image images/ipl.jpeg

You can use any image you want after the --image argument. Make sure you give the right path.

Press q to quit the window of the image showing object detection

Feel free to star ⭐ this repo if you find this useful and visit my YouTube channel if you have time.

Thanks!