https://github.com/abhinav-26/face-mask-detection-system

In this Repository I have uploaded Mask Detection System using Python3 and concepts of Transfer Learning.
https://github.com/abhinav-26/face-mask-detection-system

face-mask-detection hacktoberfest hacktoberfest2020 inception mask-detection python3 transfer-learning

Last synced: 3 months ago
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In this Repository I have uploaded Mask Detection System using Python3 and concepts of Transfer Learning.

• Host: GitHub
• URL: https://github.com/abhinav-26/face-mask-detection-system
• Owner: Abhinav-26
• License: gpl-3.0
• Created: 2020-07-16T09:16:46.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-10-31T15:32:09.000Z (almost 5 years ago)
• Last Synced: 2024-10-14T07:44:47.802Z (12 months ago)
• Topics: face-mask-detection, hacktoberfest, hacktoberfest2020, inception, mask-detection, python3, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 59.6 KB
• Stars: 3
• Watchers: 1
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
# Face-Mask-Detection-System

In this Repository I have uploaded Mask Detection System using Python3 and concepts of Transfer Learning and fine tuning. For creating this face-mask detector I used the pre-trained model inception_v3 which is provided by Google.


Transfer Learning is a study in which we use the pre-trained created models to solve our problems. There are many different models which has already eing created by different individuals or organisations such as vgg16, AlexNet, ResNet50, inceptioin_v3, etc. These models use imagenet weights for classification/detection of images. These models are highly efficient in object detection as it has been trained with huge data. To ease our tasks and work more efficiently we use these models and perform fine tuning in it as per our requirement and perform the tasks.


I myself have used inception_v3 model which is created by google. It has very high accuracy for object detection and was trained with very huge data. In this Project I got an accuracy of around 99%.

To see the demonstration of the project Click Here


# How to Run Application

1. Setup DeepLearning Environment


2. Install Packages Used 


3. Train Your Model


4. A new weight will be saved, download it


5. python3 MaskDetection.py for real-time detection