kanshi VS tensorrt_demos

Without digging into you problem, i just let you know one options/tool as an addition: https://github.com/emersion/kanshi

This works, but after a reload of the config the configuration is gone. Then I found this discussion and changed the line to:

Kanshi is not exactly what you're looking for but i stumbled across this when I was writing the dynamic display configuration page.

You should use different scale factors on each monitor. You can do it in your sway configuration, or use something like kanshi that automatically applies different settings based on what is connected.

If this fixes your problem you'll want to apply this fix: Disable Laptop screen upon closing screen. or you can use something like Automatic display profile switcher when you connect your external display to switch it to while also disabling your laptop screen.

I also heard of kanshi for monitor configuration, but I believe there's an open bug where sway reload breaks kanshi config... which kind of defeats the purpose.

kanshi should be able to do it.

Assuming your connected monitors may change - you plug another one in and then you want to move workspaces the new output: kanshi can help you with that. You can tell kanshi to execute commands when it matches a profile.

For this you can use kanshi.

tensorrt_demo github repository

https://github.com/NVIDIA-AI-IOT/torch2trt <- pretty straightforward https://github.com/jkjung-avt/tensorrt_demos <- this helped me a lot

> I'll also add a caveat that toolage for Jetson boards is extremely incomplete.

A hundred times this. I was about to write another rant here but I already did that[0] a while ago, so I'll save my breath this time. :)

Another fun fact regarding toolage: Today I discovered that many USB cameras work poorly on Jetsons (at least when using OpenCV), probably due to different drivers and/or the fact that OpenCV doesn't support ARM64 as well as it does x86_64. :(

> They supply you with a bunch of sorely outdated models for TensorRT like Inceptionv3 and SSD-MobileNetv2 and VGG-16.

They supply you with such models? That's news to me. AFAIK converting something like SSD-MobileNetv2 from TensorFlow to TensorRT still requires substantial manual work and magic, as this code[1] attests to. There are countless (countless!) posts on the Nvidia forums by people complaining that they're not able to convert their models.

[0]: https://news.ycombinator.com/item?id=26004235

[1]: https://github.com/jkjung-avt/tensorrt_demos/blob/master/ssd... (In fact, this is the only piece of code I've found on the entire internet that managed to successfully convert my SSD-MobileNetV2.)

It was some work getting compiled on nano but I used this guy's work to get started. https://jkjung-avt.github.io/tensorrt-yolov4/ and https://github.com/jkjung-avt/tensorrt_demos