I am seeing a similar thing. I have changed the Nvidia Power Management Mode setting to "Prefer Maximum Performance" from 'Optimal Power' - will monitor and see if it makes any difference.
[tool] [tutorial] Free AI Person Detection for Blue Iris
- Thread starter GentlePumpkin
- Start date
I am seeing a similar thing. I have changed the Nvidia Power Management Mode setting to "Prefer Maximum Performance" from 'Optimal Power' - will monitor and see if it makes any difference.
Hi, I SSH into my cloudkey and edited my server.js though my syntax in the file is slightly different perhaps because I'm on Cloudkey Gen2+ Firmware version: v1.1.13 and this is a bit newer than yours but this is what mine looks like in server.js
Code:
DEFAULTS=[{fps:15,idrInterval:1,bitrate:3e6,minMotionAdaptiveBitRate:75e4,minClientAdaptiveBitRate:0},{fps:15,idrInterval:1,bitrate:12e5,minMotionAdaptiveBitRate:75e4,minClientAdaptiveBitRate:15e4},{fps:15,idrInterval:1,bitrate:2e5,minMotionAdaptiveBitRate:0,minClientAdaptiveBitRate:0}],I changed the "idrInterval:5" to idrInterval:1" in these three spots and restarted with
Code:
systemctl restart unifi-protectAfter doing so keyframe stays at 0.20 though a few times I seen it go higher but I think only when cameras were rebooted, after nothing changed I rebooted both the Cloudkey and the four cameras I am testing with and it still remains at 0.20 for the keyframe rate. I also rebooted the BI server and no change to the keyframe rate.
I did also notice in my server.js file I had one extra "idrInterval:5" and I also changed that to idrInterval:1" and it made no difference with everything, that code section with the extra "idrInterval" was referring to a UVC G4 Pro PTZ
Code:
DEFAULTS[o.RESOLUTION_ID.LOW]};switch(e){case"UVC G4 PTZ":case"UVC G4 Pro":t={...o.DEFAULTS[o.RESOLUTION_ID.HIGH],fps:24,idrInterval:1,bitrate:6e6,minMotionAdaptiveBitRate:2e6,minClientAdaptiveBitRate:0}}return[t,r,s]},Thanks again for the tips on what fixed this for you and it leads me down the right path, I'm not sure what is wrong with mine but my version with these changes doesn't affect the keyframe rate the same way as with your version.
I spoke too soon, I have this working with four Ubiquiti G3 cameras and they are getting the 1.0 Keyframe instead of 0.20 and now all four cameras are working, will try adding more.
For others with Ubiquiti Protect that may be having the same problem I upgraded to the following shown below and followed @mayop 's info.
Gen2+ Cloudkey Firmware 2.0.24
Protect version is 1.17.0 Beta 9
**Thanks again @mayop for you very helpful info to getting my cameras working
Hi everyone, wondering if anyone can help.
I switched to using the Jetson Nano for DeepStack detection the other day. I was super happy with the performance but have now realised that the accuracy is waaay down compared to the CPU version. People detected as 97-100% are now being detected as low as 40% or not at all.
I'm using "deepquestai/deepstack:jetpack".
Does anyone know if there is anything that can be done about this? I'm really keen to get away from the CPU version.
I switched to using the Jetson Nano for DeepStack detection the other day. I was super happy with the performance but have now realised that the accuracy is waaay down compared to the CPU version. People detected as 97-100% are now being detected as low as 40% or not at all.
I'm using "deepquestai/deepstack:jetpack".
Does anyone know if there is anything that can be done about this? I'm really keen to get away from the CPU version.
I think there’s an environment variable to set speed vs accuracy
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robpur
Getting comfortable
As johannp0218 said, try running in high mode if you have not tried that already. The option is -e MODE=High. Here's what I use.
sudo docker run --runtime nvidia --restart=unless-stopped -e MODE=High -e VISION-DETECTION=True -p 5050:5000 deepquestai/deepstack:jetpack-2020.12
I haven't had the Nano running long enough or paid enough attention to know if it's less accurate than the CPU versions I'm running.
I thought High was for speed, not accuracy. Like High would yield fast times but poor detection while low will yield slower times but more accurate results
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“DeepStack offers three modes allowing you to tradeoff speed for peformance. During startup, you can specify performance mode to be , “High” , “Medium” and “Low”
The default mode is “Medium””
Maybe I’m reading it wrong haha
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I think I am reading it wrong, after reading it again, it’s performance mode so like Robpur said High should get you better accuracy
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I believe so. But note, the drop in % confidence may not mean a drop in accuracy. (in fact, it is likely more accurate / more critical). deepstack have changed their thresholding over the recent updates, so youll have to adjust what is an acceptable threshold in your setup, regardless of the given % value.
robpur
Getting comfortable
I just averaged the last 20 results from my Nano and came up with 468ms. Size of images being submitted are 1280x720, 1920x1080 and 2048x1536. I'm running in High mode.
I've tried on medium and high modes and it's pretty much the same unfortunately.
I did tests on the same images between the CPU version and Jetpack one.
The differences are really too great to use the Nano.
I notice that you @robpur have 2012.12 at the end though, is that just your container name or a newer version?
Ideally the Jetson version would just use the same model as the CPU one but I have no idea how you would go about doing that.
Hi guys,
Here's an example to show you what I mean with the same image used against the CPU and Jetson versions, on the same mode.
You can see that the level of confidence on the person (97% vs 41%) is wildly different and other objects were not picked up at all, such as the bowl.
Jetson
CPU
robpur
Getting comfortable
It's the latest version that was recently released, fetched with
sudo docker pull deepquestai/deepstack:jetpack-2020.12
I don't know how it compares with what you are running.
Using deepstack:Jetson in High with 640x480 I get 300ms. But I'm missing lots of genuine triggers as confidence is low.
I dont understand why my AI tool randomly just keeps storing images in the queue... it's soo frustrating... i try reboot, delete all images in the folder etc.. and it always does it randomly... at the moment, i have 32 images in the 'queue' and everything shows it is up and running.
Edit: what makes it even more weird is, if I go to settings --> AI Server URL(s) --> edit and upload a test image, it works straight away... it does not go into the "queue"... ?
Edit: what makes it even more weird is, if I go to settings --> AI Server URL(s) --> edit and upload a test image, it works straight away... it does not go into the "queue"... ?
Last edited:
Good question. No, the CPU version I am comparing it with is a Windows version that I downloaded off the DeepStack website 6 months or so ago and been using with Blue Iris since. It's only an i3 NUC (ESXi VM) so the plan was to offload the intense image processing to a Jetson as the NUC is already kept pretty busy with Blue Iris and Home Assistant.