Euro-Coin-Detection-Yolov5

Overview :

The purpose of this project is to create a Deep Learning model to detect the coin. My model is based on YOLO's object detection algorithm, and I'm using the dataset from Roboflow website.

📁 Dataset Used : From Roboflow Website

The dataset consist of one class: Coin Detect

Workflow:

Data Preparation:

• Total 1017 images for training and 80 images for validation present in 1class.
• Create a bounding boxes with the help of label-img And makesense.ai website according to YoloV5.
• Prepare folder structure that can be accept by YoloV5.

Steps to use Yolov5:

• Cloning the YoloV5 file from official repository.
• Changing the directory of yolov5
• Installing the dependencies
• Download all versions pre-trained weights.

Steps Before Training Custom Dataset:

• Go to yolov5/data/.
• Open data.yaml
• Edit the following inside it:

1. Training and Validation file path
2. Number of classes and Class names.

Training YOLOV5 Model

• Set images size 640 with batch of 8.
• Train model around 300 epochs .
• Visualise the training metrics with the help of tensorboard.

• Testing Images Using Test Data

• 
•