During the pandemic, minding if people were using masks indoors or outdoors started to be the typical scenario. And even though making this identification by a human eye seems to be a trivial task, it ended up being an interesting challenge for the current development of Artificial Intelligence systems. Unlike facial recognition systems, this solution would not need to identify the exact person with features such as eye, nose, mouth, ears. Still, it can determine the correct use of a mask in whatever scenario or facial characteristic is present.
“If we can compute the number [of people who are complying with the mask mandates], people can make policies and monitor on whether or not they need to do another campaign to push mask usage,” says Alan Descoins, the Chief Technology Officer of Tryolabs.
In March 2021, MaskCam was demonstrated and introduced by the joint efforts and leading technology from BDTI, Jabil, NVIDIA, and AI and Machine learning solutions company Tryolabs develop AI and Machine learning solutions capable of detecting people passing through a security-like camera and identifying if they were using a face mask or not. Now we are also glad to apply this great open-source project MaskCaM with Seeed’s Jetson Platform edge devices.
As part of a multi-partner team with engineering consulting firm BDTI, AI solution and GPU provider NVIDIA, and electronics manufacturer Jabil, this AI and Machine learning solutions company, Tryolabs developed a system capable of detecting people passing through a security-like camera and identifying if they were using a face mask or not. Now we are also glad to apply this great open-source project MaskCam with Seeed’s Jetson Platform edge devices.
MaskCam: an Open Source Smart Camera to Detect Face Masks
The Face Mask Solution powered by Tryolabs is a prototype reference design for an NVIDIA Jetson module-based smart camera system that measures crowd face mask usage in real-time, with all AI computation performed at the edge. We have deployed MashCam our A206 Jetson Carrier board. Combining the USB camera, the smart camera detects and tracks people in its field of view and determines whether they are wearing a mask via an object detection, tracking, and voting algorithm. It uploads statistics to the cloud, where a web GUI can be used to monitor face mask compliance in the field of view. Please check the below demo video.
Tryolabs is with the mission of being the leading platform for AI transformation. Tryolabs team creates high-impact solutions by applying computer vision, natural language processing, predictive analytics, and more techniques in the AI field. We are partnering with Tryolabs to solve complex problems together, tailored to individual business cases, leveraging Seeed’s decade’s hardware expertise and Tryolabs’s unique AI solution. On their website, you can find solutions for:
The on-device software stack is mostly written in Python and able to run under JetPack 4.6. Edge AI processing is handled by NVIDIA’s DeepStream video analytics framework, YOLOv4-tiny, and Tryolabs’ Norfair tracker. Tryolabs analytics offers report statistics to and receives commands from the cloud using MQTT and a web-based GUI. The software is containerized and for evaluation can be easily installed on an NVIDIA Jetson SoMs using docker with just a couple of commands. The device can also run under remote management such as mender.io, balenaOS, which makes it easy to manage and deploy multiple devices.
Finding a piece of hardware that can satisfy the requirements of the AI application is not easy. It required a compact size and cost-effective computer that can run object detection models in real-time.
NVIDIA Jetson Powered Solution
Face Mask solution is built around the NVIDIA Jetson SOM (system-on-module), which somehow manages to fit a CPU, GPU, RAM, and flash memory into a bit smaller than a credit card. Here we will recommend the Seeed A206 Jetson Carrier board, with a camera and a must-have heatsink to use with Jetson Nano SoM.
You can also choose Jetson SUB Mini PC-Blue with Jetson Xavier NX module, an Aluminium case with cooling fan, 128GB SSD, WiFi, Antennas, and pre-installed JetPack System.
Mask Cam supports the following Jetson platform hardware
- NVIDIA® Jetson Nano™ Developer Kit
- NVIDIA® Jetson Xavier™ NX Developer Kit
- Jetson SUB Mini PC
- A203 Carrier Board
- A203 (Version 2) Carrier Board
- A205 Carrier Board
- A206 Carrier Board
Seeed Nvidia Jetson SoMs powered Edge Devices
Seeed’s newest A206 carrier board has nearly the same design and function as NVIDIA® Jetson Xavier™ NX carrier board, fully compatible with Jetson Nano/Xavier NX/TX2 NX module. It provides several connectors with industry-standard pinouts to support additional functionality beyond what is integrated on the main platform board.
The board provides HDMI 2.0, Gigabit Ethernet, USB 3.0, M.2 key E wifi / BT, M.2 key M, CSI camera, RS232, CAN, PIO, I2C, I2S fans, and other rich peripheral interfaces, which are compatible with multiple NVIDIA SoMs and offer a wide variety of options and flexibility.
Raspberry Pi High-Quality Camera can be a good candidate, which is built around the IMX477 image sensor, which supports 4032×3040 resolution at 30 FPS and 1920×1080 resolution at 60 FPS. Compare with Raspberry Pi Camera Module V2 also based on Sony IMX219, new cameras for Jetson Nano and Jetson Xavier NX starts at a cheaper price at $18.90. The 8MP Infrared Night Vision Camera with 77° FOV with double IR LED modules only starts from $20.90. IMX219 cameras for Jetson Nano and Jetson Xavier NX also include different degrees of Field of View (FOV) functions to help the camera image capturing avoid edge vignettinPlease refer to Seeed blog on How To Choose Cameras For NVIDIA Jetson Nano and Xavier NX.
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