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I am seeing the YOLOv5 .NET module displaying CPU (DirectML) despite the module info screen showing that GPU is enabled. Did I read somewhere that there is something wrong in the code that displays CPU instead of GPU on the status screen? I don't remember where I heard this.
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Thanks very much for your report. Could you please share your System Info tab from your CodeProject.AI Server dashboard?
Thanks,
Sean Ewington
CodeProject
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Server version: 2.6.2
System: Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs: Intel(R) Core(TM) i5-7500 CPU @ 3.40GHz (Intel)
1 CPU x 4 cores. 4 logical processors (x64)
GPU (Primary): Intel(R) HD Graphics 630 (1,024 MiB) (Intel Corporation)
Driver: 31.0.101.2111
System RAM: 16 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.5
.NET SDK: Not found
Default Python: Not found
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
Intel(R) HD Graphics 630:
Driver Version 31.0.101.2111
Video Processor Intel(R) HD Graphics Family
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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Thanks very much for that. And are you able to confirm that the GPU is actually being used for that module, but on the CodeProject.AI Server dashboard, CPU is displayed?
Thanks,
Sean Ewington
CodeProject
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I'm experiencing the exact same issue:
Server version: 2.6.2
System: Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs: Intel(R) Core(TM) i5-8259U CPU @ 2.30GHz (Intel)
1 CPU x 4 cores. 8 logical processors (x64)
GPU (Primary): Intel(R) Iris(R) Plus Graphics 655 (1,024 MiB) (Intel Corporation)
Driver: 31.0.101.2127
System RAM: 16 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.7
.NET SDK: Not found
Default Python: 3.10.7
Go: Not found
NodeJS: 12.16.3
Rust: Not found
Video adapter info:
Intel(R) Iris(R) Plus Graphics 655:
Driver Version 31.0.101.2127
Video Processor Intel(R) Iris(R) Plus Graphics Family
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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Thanks very much for that. And are you able to confirm that the GPU is actually being used for that module, but on the CodeProject.AI Server dashboard, CPU is displayed?
Thanks,
Sean Ewington
CodeProject
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I haven't been back to the machine yet, but the system info screen shows GPU usage=0.
Looked at the performance monitor just now, that shows occasional 3d activity, but nothing else. 1% memory constant. GPU0
Maybe it's not using the GPU.
I again clicked enable GPU, log says GPU enabled when the module restarts.
Maybe uninstall reinstall the module? I've uninstalled and reinstalled ver. 2.6.2 a couple of times already trying to figure out the Coral failed inferences. I just don't know.
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In my case, GPU is not used.
CPU (DirectML) is utilised despite selecting Enable GPU
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This is a naming issue. Here's the comment for the EnableGPU property:
public bool? EnableGPU { get; set; } = true;
cheers
Chris Maunder
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How can we force the use of GPU?
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You can't. That module uses DirectML which means it will use the GPU if it can, meaning if the correct drivers are installed, and if the GPU is supported by DirectML. With DirectML, the use of the internal GPU is assumed, so if it's not actually using the GPU it's not something (AFAIK) we can really influence.
The only thing I would say is to be careful when trying to determine if the GPU is being used or not. A quote from an issue regarding DirectML using Tensorflow:
Quote: One thing to keep in mind is that if you're using Task Manager to monitor GPU usage, it can sometimes be misleading because the default Task Manager GPU usage graph looks for 3D workloads which are different from compute workloads like tensorflow-directml
cheers
Chris Maunder
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Interesting. I do recall that prior to upgrading to CPAI ver2.6.2 (using 2.5.6) the YoloV5.NET model displayed that it was utilising the GPU, however, it seems to utilise CPU with this upgrade. I haven’t rolled back to CPAI ver2.5.6 to confirm my recollection though.
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Yes.
I'm going to try rolling back to 2.5.4.
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Me too.
Rolled back to CPAI ver. 2.5.6. YOLOv5 .NET connected to GPU on startup, and shows it is using GPU (Intel 630) without any user intervention.
Server version: 2.5.6
System: Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs: Intel(R) Core(TM) i5-7500 CPU @ 3.40GHz (Intel)
1 CPU x 4 cores. 4 logical processors (x64)
GPU (Primary): Intel(R) HD Graphics 630 (1,024 MiB) (Intel Corporation)
Driver: 31.0.101.2111
System RAM: 16 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.5
.NET SDK: Not found
Default Python: Not found
Go: Not found
NodeJS: Not found
Video adapter info:
Intel(R) HD Graphics 630:
Driver Version 31.0.101.2111
Video Processor Intel(R) HD Graphics Family
System GPU info:
GPU 3D Usage 10%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
Module 'Object Detection (YOLOv5 .NET)' 1.9.3 (ID: ObjectDetectionYOLOv5Net)
Valid: True
Module Path: <root>\modules\ObjectDetectionYOLOv5Net
AutoStart: True
Queue: objectdetection_queue
Runtime: dotnet
Runtime Loc: Shared
FilePath: bin\ObjectDetectionYOLOv5Net.exe
Pre installed: False
Start pause: 1 sec
Parallelism: 0
LogVerbosity:
Platforms: all
GPU Libraries: installed if available
GPU Enabled: enabled
Accelerator:
Half Precis.: enable
Environment Variables
CUSTOM_MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5Net\custom-models
MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5Net\assets
MODEL_SIZE = MEDIUM
Status Data: {
"inferenceDevice": "GPU",
"inferenceLibrary": "DirectML",
"canUseGPU": true,
"successfulInferences": 179,
"failedInferences": 0,
"numInferences": 179,
"averageInferenceMs": 245,
"histogram": {
"person": 63,
"car": 262,
"bus": 19,
"truck": 2
},
"numItemsFound": 346
}
Started: 16 May 2024 7:52:55 AM Central Standard Time
LastSeen: 16 May 2024 8:07:00 AM Central Standard Time
Status: Started
Requests: 179 (includes status calls)
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i have a fresh install of code project 2.6.4 on ubuntu server 24.04, object detection installed fine on on the install but trying to install LPR and Training and i get a 404 error for both of them
Server version: 2.6.4
System: Linux
Operating System: Linux (Ubuntu 24.04)
CPUs: 12th Gen Intel(R) Core(TM) i7-12700K (Intel)
1 CPU x 12 cores. 20 logical processors (x64)
GPU (Primary): NVIDIA GeForce RTX 2060 (6 GiB) (NVIDIA)
Driver: 535.161.08, CUDA: 12.2 (up to: 12.2), Compute: 7.5, cuDNN:
System RAM: 31 GiB
Platform: Linux
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.18
.NET SDK: 7.0.118
Default Python: 3.12.3
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
TU104 [GeForce RTX 2060] (rev a1):
Driver Version
Video Processor
System GPU info:
GPU 3D Usage 10%
GPU RAM Usage 1.9 GiB
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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Are you still getting 404s?
cheers
Chris Maunder
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Upgraded to 2.6.2, Blue Iris intermittent AI Error 500 are back.
Can anyone explain the actual root cause of these errors? I'm getting a bit tired of the game between BI and CodeProject where updating one or the other has a 75% chance of re-introducing these errors.
Thanks
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I'm sure you've reported stuff before but it's extremely difficult for us to remember everyone's details on everything.
Can you please let us know
- what version of the server you're using
- on which module you're seeing the error
- The actual error (screen shot would be good)
- Have you tested the image that's throwing the 500 using the CodeProject.AI Explorer. It uses the same API as Blue Iris
cheers
Chris Maunder
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For sure. For reference I was on 2.5.4 w/ Blue Iris 5.8.8.12 and had no AI errors.
Updated to CodeProject 2.6.2. Intermittent errors started every 15-30min on random cameras.
Decided to upgrade BI to latest 5.9.0.5. Still exist.
I'm using Coral TPU, tried various models and sizes. Multi-TPU disabled.
I don't know what images it's failing on unfortunately; BI doesn't give me the optics into that.
 09-05-24-1817 hosted at ImgBB — ImgBB[^]
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Does it work better if multi-TPU is enabled?
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Coral on Windows is not very reliable I'm afraid. It works, but intermittent errors are not uncommon. I use the .NET Object Detection module on Windows since it uses DirectML and so will make the best use of available hardware.
cheers
Chris Maunder
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What do you recommend for Coral? Docker? Linux? I can pivot if it's known to be more reliable.
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I’ve been running Ubuntu 20.04 and it’s been rock solid.
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I'd second Seth's suggestion on Ubuntu if you want to use Coral.
cheers
Chris Maunder
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Spun up an Ubuntu 22.04 VM, passed the PCI-E Coral through to the VM (running on Proxmox), installed CPAI 2.6.4 and so far so good, no 500 errors.
Running in multi-tpu mode even though I only have a single card.
EfficientDetLite small model.
Averaging 10-15ms.
Thanks for the suggestion. Decoupling CPAI and BI has been on my list to do for a while just wasn't sure the Linux version of CPAI was more stable and worth the effort.
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