This is an AI tool that detects masks super fast:
- No installation or registration.
- No need to buy expensive devices.
- You don’t even need a continuous internet connection.
- Most importantly, it is completely FREE!
Well, let’s be serious. This is an AI model running in the browser that can recognize whether people are wearing masks and automatically remind them.
Think of those mask detection machines at the entrance of luxury stores; they can remind customers to wear masks. However, most small businesses and local shops cannot pay thousands of dollars to install them. Now, you only need a tablet or laptop, and you can have it! After loading, this model runs completely locally on your device, and no data will be uploaded to the server.
How to use it?
Now, you can use it on Android, iOS, Windows, macOS, and Linux systems. For the best experience and fastest speed, please use the Chrome browser on non-iOS systems.
- Download and launch the latest version of the Chrome browser
- Enter chrome://flags in the address bar
- Enable all WebAssembly features
- Re-launch Chrome, open the web page, and allow access to the camera.
Hint: The FPS depends on your device CPU.
Why is it so fast?
This model is modified from Yolo-Fastest and is only 1.3M in size. It might be the fastest and lightest open-source improved version of a YOLO general object detection model. The YOLO series models we are familiar with, which are known for detection speed, are much larger than it, usually tens of megabytes in size. Even the smallest one, YOLOv5s, is 7.5M. Therefore, this model puts very little pressure on the device.
| Model | Yolo-Fastest | YOLOv3-tiny | YOLOv3-SPP | YOLOv5s | YOLOv5m | YOLOv5l | YOLOv5x |
|---|---|---|---|---|---|---|---|
| Size | 1.3M | 8.9M | 63.0M | 7.5M | 21.8M | 47.8M | 89.0M |
The deployment of this model is achieved through the NCNN framework and WebAssembly. NCNN is a high-performance neural network inference computing framework optimized for mobile platforms. It has excellent performance on low-computing-power devices. WebAssembly compiles the C++ program into a binary format so that it can run at high speed in the browser.
Because of this, even without a GPU, even if it runs in a browser, it can complete the detection with a high FPS, which exceeds most common mask detection tools.
What about privacy issues?
Since this model runs entirely in the browser, it does not upload and does not need to upload any data, such as video content, to the server. All detection processes are completed locally. After loading, the user can even cut off the Internet connection.
All video content will only be processed in real time and will not be stored in any form.
Therefore, there is no need to worry about privacy leaks or other related issues. This also means that the user does not need to set up Wi-Fi for the place where the device is placed or worry about extra data charges caused by detection. At the same time, the tool will not occupy the storage space of the device.
What’s more?
Because only Safari supports WebAssembly under the iOS system, and it does not support parallel computing acceleration methods such as SIMD, the speed will be slower than other platforms.
All in all, it is a free alternative to expensive mask detection machines. You can buy a tablet for $60 and a floor stand for $20 to get similar functions. After this pandemic, these devices can also be used for other purposes.
In such a hard time, I hope this AI can help small businesses that are struggling to persist, so that they can obtain protection similar to luxury shops at a small cost. As long as this tool can protect one more person from COVID-19, it will be enough.
Of course, this project is not mature yet. If you have any suggestions or are willing to contribute to this project, please contact me.
Thank you very much!
Release information
2025.11.20 - 3.0.0: New UI design and restructured repo.
2021.01.06 - 2.0.4: Add feedback function.
2020.12.13 - 2.0.0: Deployed a new model. It can recognize faces that are not wearing a mask properly (not completely covering nose and mouth). Improved the recognition of faces covered by a mobile phone.
2020.12.01 - 1.1.0: Added support for iOS system. Now it can automatically recognize whether the browser supports advanced computing functions and apply them.
2020.11.30 - 1.0.3: Added Spanish and Chinese versions.
2020.11.28 - 1.0.2: The domain name was changed to facemask-detection.com, which is convenient for users to remember.
2020.11.26 - 1.0.1: The website is officially established.
