Cooltiger
Getting the hang of it
My BI on 5.8.8.2 also reverted to Auto and not delayed start.I am on 5.8.8.2 and custom model list is working fine.
My BI on 5.8.7.11 also had reset to Auto not delayed start.
My BI on 5.8.8.2 also reverted to Auto and not delayed start.I am on 5.8.8.2 and custom model list is working fine.
I have very good accuracy with the standard models under Yolo 5, so the issue appears to me to be possibly with the Yolo 8 engine. I've only had 1 false positive in 18 months with Yolo 5 caused by a sun shadow, and most of my human triggers are from the waist up only as there's a wall separating them from the camera. Yolo 8 should in theory give much better accuracy as usually each Yolo model claims improvements. However, as it's new it maybe it just needs some more tweeking by the Yolo developers.Yes, the difference in accuracy is due to using default model yolo8v with Coral vs using Ipcam Custom models with non coral system. Getting ip-cam custom models support with Coral would probably fix this.
Absolutely, how active the cams are would certainly affect things, I was just curious if anyone was running a larger system and what experience they are having.@mad-maks Use CP.AI Explorer (Benchmark tab) to get an idea of how many requests/sec it can handle. See screenshot below.
Think about # of requests (or operations) instead of # of cameras.
If you have 100 cameras but few events, or 50 cameras but twice the # events, the load you put on CP.Ai is the same, right?
View attachment 189017
environment:
- Modules:FaceProcessing:LaunchSettings:AutoStart=false
environment:
- Modules:ObjectDetectionNet:LaunchSettings:AutoStart=false
Thanks @wittaj !You need to add:
alpr:0
To the custom models box to turn off alpr.
But keep in mind that a recent change to BI now has it run thru all models.
From this post in the BI update thread:
So I was using the following settings for my LPR camera:
I sent this to Ken and this was his response:
Yes with these settings, all custom models will be run. If you want only specific models, you need to specify the model name. If you use a non existent mode name, none of them will be executed.
There may have been a fix made to this code to cause this "new behavior" but it's actually now correct.
Thanks
Ken
So from version 5.8.8.3 on you have to enter a non existent model name in the custom model field if you only want to use the ALPR model. I changed mine to "nothing,object:0" and just updated to 5.8.8.8 and everything seems to be working as expected.
Could you share your System Info tab from the CodeProject.AI Server dashboard, and any error logs you see (if any)? Also curious to see the results if you run the nvidia-smi command and then the nvcc --version command.OS: Ubuntu, CPAI v2.5.6 (codeproject/ai-server:cuda12_2), docker
I tried to get Yolov5.NET v1.9.3 to work using GPU and cannot.
I have CPAI setup in a docker container in Ubuntu, I have the nvidia drivers installed, nvidia-runtime, etc.
I enabled Yolov5.NET but it says CPU (even after the first detection) and the inference time is what I would expect from CPU around 200ms.
Yes I had no issues with windows.
I don't believe that BI has any reason to make calls to the Background Remover module.Question on Background Remover module. Does it proactively remove the background for all snapshots sent to CPAI from Bi or do I manually have to remove the background from a snapshot and save that as a different file?
I have the same question for ipcam-combined.Hey @MikeLud1 Any idea when a YOLOv8 ipcam-animal custom model might be available?
I've been wanting to give Object Detection (YOLOv8) a try, but am currently using the ipcam-animal custom model on a few of my cameras.