Processing time

I’m really obsessed with the performances of our app, and I keep pushing my guys to improve the software as much as possible. There are ways to speed up things by having proper hardware, network configuration and proper settings. Once everything is sorted out, you should get results as fast as what we’ve been measuring here at the studio

***UPDATED Benchmarks February 27, 2019**

We now support more than one camera per Raspberry Pi, which is drastically reducing the number of cables and electronic components. Here are our latest results:


(time required to download all files, apply digital calibration and render the full mp4 at 1080p, ready to replay and share)

Number of cameras File type Dimension Hardware Duration
16JPG1080p4 Raspberry Pis3s
16RAW6k/24MP4 Raspberry Pis17s
16RAW6k/24MP8 Raspberry Pis15s
16JPG1080pusb hubs + one computer6s
42JPG1080p14 Raspberry Pis6s
16RAW6k/24MPusb hubs + one computer23s
16RAW6k/24MPusb hubs + two computers20s

*** Raspberry Pi’s architecture: Canon SL2, One Gigabit Switch (no daisy chaining), Raspberry Pi 3b+, Gaming i7 computer

*** USB hubs architecture: Canon SL2, 7 ports powered usb-hubs, Gaming i7 computer, Esper triggerbox

Trigger precision

Starting from version 1.10.0, USB triggering through Raspberry Pi' computers is about the same as using an analog trigger (using the trigger connection port). And that is true even when setting 4 cameras on a single Pi. From our experience, the only precision problem left is about the cameras themselves (mechanical shutter latency at more or less 1ms). Our latest tests have been made using Canon SL2/200d, and we’re working on various test scenarios to provide you guys with more details.


You’ll find below a few videos where we demonstrate how we use the software. I’ll update this section as new videos come up