JeVois-Pro ultra-compact deep learning camera gets 26 TOPS Hailo-8 AI accelerator

JeVois-Pro tiny AI camera was introduced last year with an Amlogic A311D processor with a built-in 5 TOPS NPU, and support for an Intel Myriad X or Google Edge TPU M.2 card all that in a compact 50x50x45 mm box.

The company has now managed to get hold of some M.2 A+E 2230 Hailo-8 modules delivering up to 26 TOPS of AI performance and is selling for JeVois-Pro ultra-compact deep learning camera with the Hailo-8 accelerator for $599 delivering up to 31 TOPS once we include the built-in 5 TOPS NPU.

 

Jevois Pro Hailo 8 AI accelerator

I won’t go through the full specifications again, but in a nutshell, that’s a camera designed for robotics projects, powered by an Amlogic A311D hexa-core Cortex-A73/A53 processor with 4GB RAM, a microSD card socket for the OS and data, and a 2MP Sony IMX290 Starvis sensor.

Since the system is quite compact and the AI accelerator fairly powerful, I asked the company about potential thermal issues, and they enable the fan by default when Hailo-8 is detected:

So far, thermal is good, the Hailo board reports typically around 50C once we turn on our fan at full speed. We set this as default when a hailo board is detected, because we don’t yet have a simple way to let our fan driver know what the hailo temp is (maybe Hailo can add temps in some /sys/class/ entry in the future). Even though our fan is on the opposite side of the case, it still generates enough airflow to cool the hailo board by 10~15C when it is on vs off. If things get worse in the future, we already have a connector for a second fan on our main board, so we would ship a modified case front with a small 25mm fan blowing right onto the neural accelerator (in addition to the 40mm fan in the back).

The system can run pretty big networks such as a full YOLOv7 640×640 at 11.5 fps, or the smaller YOLOv5m 640×640 at 40fps, resnet-50 at 228fps, and is quite more capable than when fitted with a Google Coral TPU Edge that is only capable of running small Mobilenets networks and the likes. We can check the capabilities of the camera with the Hailo-8 module in the video below.

 

JeVois also released some benchmarks using the CPU, Amlogic NPU, Coral Edge TPU, and Hailo-8 accelerator. But note that those results do NOT represent the peak performance of these accelerators, and only results with the Jevois-Pro unit due to its limitation. These include a PCIe x1 interface (Hailo support PCIe x4), the processor is slower than on some other test systems, and the USB 3.0 capable Myriad X chip is only connected over a USB 2.0 interface. That’s why you may see higher or lower numbers for Hailo-8, Myriad X, or Coral Edge AI accelerator on other systems.

 

JeVois-Pro Hailo-8 performance FPS
Jevois-Pro with Hailo-8 results – Vertical scale: Mean FPS

Classify tests use 224×224 RGB images, and Detect (YOLO) tests 640×640 RGB images. Sadly a direct comparison between various accelerators is not possible as most benchmarks are different, and/or with different inputs.

Share this:

Support CNX Software! Donate via PayPal or cryptocurrencies, become a Patron on Patreon, or buy review samples

ROCK Pi 4C Plus
Subscribe
Notify of
guest
The comment form collects your name, email and content to allow us keep track of the comments placed on the website. Please read and accept our website Terms and Privacy Policy to post a comment.
0 Comments
Advertisement