[enhancement] Face-Mask-Detection folder

[KamakshiOjha]

Is your feature request related to a problem? Please describe. The current face mask detection model, while functional, lacks sufficient sample data for diverse and comprehensive evaluation. This may lead to less accurate predictions in real-world scenarios. Additionally, there is a need for visual representation of the model's performance metrics and prediction results for better interpretability.

Describe the solution you'd like I would like to improve the face mask detection project by:

1. Adding more sample images to the dataset to improve the robustness and accuracy of the model.
2. Implementing visualizations such as accuracy/loss graphs to provide clear insights into the model's performance.
3. Integrating a feature to dynamically predict and display results on new images with corresponding graphs.

Describe alternatives you've considered

1. Experiment with different CNN architectures or hybrid models to compare performance and select the best one.
2. Use a pre-trained model on a large dataset and fine-tune it on the face mask detection dataset to potentially achieve better performance.

Approach to be followed (optional)

1. Data Collection and Preprocessing:

   • Gather additional face mask and non-mask images from various sources.
   • Preprocess the images (resize, normalize, etc.) to ensure consistency with the current dataset.

2. Model Training:

   • Train the CNN model on the expanded dataset.

3. Performance Evaluation:

   • Plot accuracy and loss graphs over epochs to monitor the training process.

4. Dynamic Prediction Interface:

   • Create an interface to upload and predict new images.
   • Display prediction results along with probability scores.
   • Show graphs and metrics related to the prediction for better understanding.

Additional context The project aims to detect whether a person in an image is wearing a face mask or not using a CNN model. The enhanced features will not only improve model accuracy but also provide clear, interpretable visual feedback.

[KamakshiOjha]

Please assign me this enhancement under GSSOC

[github-actions[bot]]

Hello @KamakshiOjha, Thank you for generating an issue to this project! Please wait while we get back to you.

[KamakshiOjha]

Please assign me this enhancement under GSSOC

[KamakshiOjha]

Please Assign me this issue under SSOC or GSSOC

[KamakshiOjha]

Please Assign me this issue under GSSOC

[Gaurav-576]

Is this issue still up for grabs??