https://github.com/mohamedsebaie/face_mask_detector_webapp-by_streamlit_heroku-

This Project has been implemented by using OpenCV to detect faces in the input images and a pre-trained Keras CNN model (MobileNetV2) as mask/no-mask binary classifier applied to the faces Images. The Deep Learning model currently used has been trained using images data set from Kaggle. The trained model has been shared in this repo.
https://github.com/mohamedsebaie/face_mask_detector_webapp-by_streamlit_heroku-

caffee cnn-keras colab-notebook convolutional-neural-networks datagenerator deep-learning face-detection heroku-deployment image-classification imagenet keras mask-detection mobilenetv2 opencv pre-trained-model python streamlit transfer-learning webapp

Last synced: 2 months ago
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This Project has been implemented by using OpenCV to detect faces in the input images and a pre-trained Keras CNN model (MobileNetV2) as mask/no-mask binary classifier applied to the faces Images. The Deep Learning model currently used has been trained using images data set from Kaggle. The trained model has been shared in this repo.

• Host: GitHub
• URL: https://github.com/mohamedsebaie/face_mask_detector_webapp-by_streamlit_heroku-
• Owner: MohamedSebaie
• Created: 2021-03-14T23:10:08.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2021-09-23T11:10:11.000Z (about 4 years ago)
• Last Synced: 2025-03-14T22:11:24.029Z (7 months ago)
• Topics: caffee, cnn-keras, colab-notebook, convolutional-neural-networks, datagenerator, deep-learning, face-detection, heroku-deployment, image-classification, imagenet, keras, mask-detection, mobilenetv2, opencv, pre-trained-model, python, streamlit, transfer-learning, webapp
• Language: Jupyter Notebook
• Homepage:
• Size: 72.7 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Deployment_PROJECT (Face Mask Detector) Using Streamlit and Heroku by Applying Pre- Trained CNN Model `(MobileNetV2)`

## by `Mohamed Sebaie Sebaie`



### This is a simple `Streamlit` frontend for face mask detection in images using a pre-trained Keras CNN model `MobileNetV2` and OpenCV then deploy on `heroku`.

### The `Web Application` I Created, is in `This Link`.

#### The Data used for training can be found through  `This Link` on Kaggle Website. 

#### All work here is done on `CoLab` 

## General Info

>- This Project has been implemented by using OpenCV to detect faces in the input images and a a pre-trained Keras CNN model (MobileNetV2)   as mask/no-mask binary classifier applied to the faces Images. The Deep Learning model currently used has been trained using this image data set from kaggle `here` . The trained model has been shared in this repo. The face detector algorithm comes from `here`: the Caffee model files are in CAFFEE folder directory.

## Web APP Explanation

### Once an image has been uploaded, the classification happens automatically. 

##  About The Data:

#### The dataset used for Training consists of one zip file `Face Mask Dataset` that is download in `Colab` and unzipped then Create a pre-trained Keras CNN model (MobileNetV2) and Training then evaluate, save and test the model. The NoteBooks are in face_mask_detector_notebooks.

## Finally, After creating the ` Model` and save as `h5` file, Deploy the model with `Streamlit` frontend and upload it to`Heroku Platform`..

## The `Web Application` I Created, is in `This Link`.

## Good Reference for Deployment a Streamlit Frontend to Heroku here.