Yolov8-Custom-Object-Detetction

This repos explains the custom object detection training using Yolov8

The goal is to detetc a person is using mask or not and whether using it in wrong way. I am using "Face Mask Dataset" from kaggle which is already available in yolo format. https://www.kaggle.com/datasets/maalialharbi/face-mask-dataset?resource=download

This is a initial version of custom trianing with YOLOv8. Currently YOLOv8 is the newest state-of-the-art YOLO model that can be used for object detection, image classification, and instance segmentation tasks.

I am using Google Colab for trianing. If you are intrested to check custom trianing with YOLOv5, please follow this link 😀 https://github.com/Balakishan77/yolov5_custom_trained_traffic_sign_detector.

About this Dataset for Detection Tasks:

https://www.kaggle.com/datasets/maalialharbi/face-mask-dataset?resource=download This is ready to use Face Mask Dataset in YOLO format for Detection tasks. It can be used for training as well as for testing.

The images are split as follows:

Test: 136 =10% Train: 990 = 70% Valid: 294 = 20% Total = 1420 images Image Augmentation was done to increase the dataset size and make it more powerful. The images are in: JPEG, PNG format

The dataset has 3 classes: no_mask mask improper_mask

Training Custom Face Mask Detection Model:

I have used Yolov8m for custom training with Face Mask data. I did training in Google colab by reading data from Google drive. The notebook explains the below steps:

1.Setting Up Google Colab
2.YOLOV8 Installation
3.Mounting Google Drive
4.Create face_mask_detetcion.yaml (dataset config file) (YOLOV8 format)
5.Training Our Custom Face Mask Detetcion Model
6.Metrics
7.Run Inference With Custom YOLOv8 Object Detector Trained Weights

Inference results on the video using Yolov8 custome trained model:

Attached video as seperate file in repo. Below are the some of the detetcions on image.

Conclusion:

Based on the inference results, the trained model is doing a great job. We can still imrpove it by using large yolov8 models, additional data and hyperparameter changes. Model file is also available for any type of testing.

References:

1.https://github.com/ultralytics/ultralytics

2.https://docs.ultralytics.com/tasks/detection/

3.https://www.kaggle.com/datasets/maalialharbi/face-mask-dataset?resource=download