🔍This project aims to create an anti-spoofing device using face recognition technology.
📐The key to this project is collecting and labeling your own data sets to train the model.
⏰With just 20 minutes, you can collect and annotate thousands of images for training.
📲The resulting model can be deployed on phones, tablets, and other devices.
💪The project is simple to make and sturdy, allowing for future improvements and optimizations.
What is the main goal of this project?
—The main goal is to create an anti-spoofing device using face recognition technology.
Why is it important to collect and label your own data sets?
—Collecting and labeling your own data sets allows the model to be trained on specific real-world scenarios, resulting in better accuracy and performance.
How long does it take to collect and annotate the data sets?
—It can be done in just 20 minutes, thanks to automation techniques and the ability to collect data from various sources.
Where can the resulting model be deployed?
—The model can be deployed on phones, tablets, and other devices, making it accessible for various applications and scenarios.
Is this project suitable for beginners?
—Yes, this project is designed to be simple and accessible for beginners, while still offering room for improvements and optimizations.
00:00Introduction to creating a spoofing detector using face recognition
02:30Importing the necessary packages and setting up the project
05:15Collecting and labeling data sets for training the model
07:45Training the model and optimizing the results
10:00Deploying the model on phones, tablets, and other devices
