FACE MASK DETECTION 😷

OVERVIEW :

The purpose of this project is to create a Deep Learning model that identifies whether or not someone is wearing a mask. My model is based on YOLO's object detection algorithm, and I'm using the dataset from Roboflow website.

📁 DATASET USED :

https://public.roboflow.ai/object-detection/mask-wearing

The dataset consists of two classes:

• with_mask
• without_mask

WORKFLOW:

Data Preparation:

• Total 105 images for training and 29 images for validation present in 2 classes.
• 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 600 epochs .
• Visualise the training metrics with the help of tensorboard.

TESTING IMAGES USING TEST DATA:

TESTING VIDEO DEMO :

Face mask detection is an object detection task that detects whether people are wearing masks or not in videos. This repo includes a demo for building a face mask detector using YOLOv5 model.

Face.mask.detection.video1.mp4

Just follow☝️ me and Star⭐ my repository

Motivated and supported by the works of,

[Mr.Mukesh DPawar].