Mask Detection using Convolutional Neural Network

This repository contains code for a mask detection system using a Convolutional Neural Network (CNN). The system is designed to classify images into three categories: incorrect mask, mask, and no mask.

Dataset
Data Preprocessing
Model Architecture
Model Training
Testing

Dataset

The dataset consists of images belonging to three classes: incorrect mask, mask, and no mask. The images are loaded and preprocessed using OpenCV and TensorFlow.

import tensorflow as tf
import cv2
import numpy as np
import cvlib as cv
import glob

def dataset(path):
    # Function to load and preprocess the dataset
    # ...
     return x_train, y_train

# Example usage:
 train_dir = r'datasets/maska/train/'
 test_dir = r'datasets/maska/test/'
 x_train, y_train = dataset(train_dir)
 x_test, y_test = dataset(test_dir)

Data Preprocessing

Images are resized to 128x128 pixels and loaded into NumPy arrays for training and testing. import numpy as np

Data preprocessing

x_train = np.array(x_train)
y_train = np.array(y_train)
print(x_train.shape, y_train.shape)

x_test = np.array(x_test)
y_test = np.array(y_test)
print(x_test.shape)

Model Architecture

The model is a sequential CNN with convolutional, max-pooling, batch normalization, and dense layers. from tensorflow import keras

model = keras.Sequential([
   # Model layers...
])

# Model compilation
optim = keras.optimizers.Adam(learning_rate=0.001)
model.compile(optimizer=optim, loss='categorical_crossentropy', metrics=['accuracy'])

Model Training

The model is trained on the preprocessed dataset using TensorFlow. GPU acceleration is utilized if available.

with tf.device("/GPU:0"):
    model.fit(x_train, y_train, epochs=10)
    model.evaluate(x_test, y_test)
    model.summary()

Testing

The trained model is saved and then loaded for real-time testing using a webcam.

# Example usage for real-time testing
model.save('mask_detection_model.h5', save_format='h5')

# Load the saved model
model = keras.models.load_model('mask_detection_model.h5')

# Real-time testing using webcam
# ...

Mukhriddin19980901/Mask_detection