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Thanks very much for your report. Can you please share your System Info tab from the CodeProject.AI Server dashboard, and the logs you get when the server goes offline?
Thanks,
Sean Ewington
CodeProject
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It seems to be working now, but here is my info:
System Info Tab:
I do get this error in my server logs:
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The option is there for YOLO.NET but not LPR. How do I disable the GPU for that module?
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Edit the modulesettings.json file in /modules/ALPR and set "EnableGPU": false
cheers
Chris Maunder
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When I'm running the YOLOv5 .NET model with GPU (DirectML) on my i5-13500H CPU (onboard Iris Xe GPU with 80EU's) something very strange happens.
It seems that whenever the requested model is changed a massive delay happens. For example, if I run the benchmark built into codeplatform and try to benchmark the ipcam-combined model Codeproject will essentially freeze for a very long time, up to 8 minutes! During this time the GPU usage is 0 and the CPU usage is anywhere from 10-35%. After this initial period codeproject becomes responsive again, I proceed with the benchmark again and things happen very quickly - I benchmark at ~21 operations per second with the ipcam-combined model.
This same initial freeze then speed up also happens the first time Blue Iris sends an alert to Codeproject for processing when it is selecting a custom model such as ipcam-combined. This behavior repeats itself any time Codeproject is restarted for whatever reason.
Does anyone know what is going on here? Here's some logs to show the behavior:
<pre>Server version: 2.3.4-Beta
System: Windows
Operating System: Windows (Microsoft Windows 10.0.20348)
CPUs: 13th Gen Intel(R) Core(TM) i5-13500H (Intel)
1 CPU x 12 cores. 16 logical processors (x64)
GPU: Intel(R) Iris(R) Xe Graphics (1,024 MiB) (Intel Corporation)
Driver: 31.0.101.4900
System RAM: 32 GiB
Target: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
.NET framework: .NET 7.0.13
Video adapter info:
Intel(R) Iris(R) Xe Graphics:
Driver Version 31.0.101.4900
Video Processor Intel(R) Iris(R) Xe Graphics Family
System GPU info:
GPU 3D Usage 12%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
15:54:36:Module 'Object Detection (YOLOv5 .NET)' 1.7.1 (ID: ObjectDetectionNet)
15:54:36:Module Path: C:\Program Files\CodeProject\AI\modules\ObjectDetectionNet
15:54:36:AutoStart: True
15:54:36:Queue: objectdetection_queue
15:54:36:Platforms: windows,linux,linux-arm64,macos,macos-arm64
15:54:36:GPU Libraries: installed if available
15:54:36:GPU Enabled: enabled
15:54:36:Parallelism: 0
15:54:36:Accelerator:
15:54:36:Starting C:\Program Files...ctionNet\ObjectDetectionNet.exe
15:54:36:Attempting to start ObjectDetectionNet with C:\Program Files\CodeProject\AI\modules\ObjectDetectionNet\ObjectDetectionNet.exe
15:54:36:Half Precis.: enable
15:54:36:Runtime: execute
15:54:36:Runtime Loc: Shared
15:54:36:FilePath: ObjectDetectionNet.exe
15:54:36:Pre installed: False
15:54:36:Start pause: 1 sec
15:54:36:LogVerbosity:
15:54:36:Valid: True
15:54:36:Environment Variables
15:54:36:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%\custom-models
15:54:36:MODELS_DIR = %CURRENT_MODULE_PATH%\assets
15:54:36:MODEL_SIZE = large
15:54:36:
15:54:36:Started Object Detection (YOLOv5 .NET) module
15:58:07:ObjectDetectionNet.exe: Application started. Press Ctrl+C to shut down.
15:58:07:ObjectDetectionNet.exe: Hosting environment: Production
15:58:07:ObjectDetectionNet.exe: Content root path: C:\Program Files\CodeProject\AI\modules\ObjectDetectionNet
15:58:08:Object Detection (YOLOv5 .NET): Object Detection (YOLOv5 .NET) module started.
16:05:28:Client request 'list-custom' in queue 'objectdetection_queue' (...d2de92)
16:05:28:Request 'list-custom' dequeued from 'objectdetection_queue' (...d2de92)
16:05:28:Object Detection (YOLOv5 .NET): Command completed in 10 ms.
16:05:28:Response received (...d2de92)
16:21:17:Client request 'custom' in queue 'objectdetection_queue' (...7b4aad)
16:21:17:Request 'custom' dequeued from 'objectdetection_queue' (...7b4aad)
16:21:17:Client request 'custom' in queue 'objectdetection_queue' (...d25877)
16:21:17:Request 'custom' dequeued from 'objectdetection_queue' (...d25877)
16:21:17:Client request 'custom' in queue 'objectdetection_queue' (...99875d)
16:21:17:Request 'custom' dequeued from 'objectdetection_queue' (...99875d)
16:21:17:Client request 'custom' in queue 'objectdetection_queue' (...15edb6)
16:21:17:Request 'custom' dequeued from 'objectdetection_queue' (...15edb6)
16:21:18:Client request 'custom' in queue 'objectdetection_queue' (...757f9e)
16:21:18:Request 'custom' dequeued from 'objectdetection_queue' (...757f9e)
16:22:18:Client request 'custom' in queue 'objectdetection_queue' (...5f3346)
16:22:18:Client request 'custom' in queue 'objectdetection_queue' (...ca5c64)
16:22:18:Request 'custom' dequeued from 'objectdetection_queue' (...ca5c64)
16:22:18:Request 'custom' dequeued from 'objectdetection_queue' (...5f3346)
16:22:18:Client request 'custom' in queue 'objectdetection_queue' (...b31c45)
16:22:18:Request 'custom' dequeued from 'objectdetection_queue' (...b31c45)
16:22:19:Client request 'custom' in queue 'objectdetection_queue' (...9b4760)
16:22:19:Request 'custom' dequeued from 'objectdetection_queue' (...9b4760)
16:22:19:Client request 'custom' in queue 'objectdetection_queue' (...9e5a5b)
16:22:19:Request 'custom' dequeued from 'objectdetection_queue' (...9e5a5b)
16:23:20:Client request 'custom' in queue 'objectdetection_queue' (...ed2068)
16:23:20:Client request 'custom' in queue 'objectdetection_queue' (...a24196)
16:23:20:Client request 'custom' in queue 'objectdetection_queue' (...e0684e)
16:23:20:Client request 'custom' in queue 'objectdetection_queue' (...a7def0)
16:23:21:Client request 'custom' in queue 'objectdetection_queue' (...943db6)
16:24:21:Client request 'custom' in queue 'objectdetection_queue' (...e3c9f9)
16:24:21:Client request 'custom' in queue 'objectdetection_queue' (...f67a5f)
16:24:21:Client request 'custom' in queue 'objectdetection_queue' (...768f06)
16:24:22:Client request 'custom' in queue 'objectdetection_queue' (...2309ad)
16:24:22:Client request 'custom' in queue 'objectdetection_queue' (...c1a18f)
16:25:23:Client request 'custom' in queue 'objectdetection_queue' (...fa5965)
16:25:23:Client request 'custom' in queue 'objectdetection_queue' (...93e26d)
16:25:23:Client request 'custom' in queue 'objectdetection_queue' (...b028e0)
16:25:23:Client request 'custom' in queue 'objectdetection_queue' (...dc519a)
16:25:24:Client request 'custom' in queue 'objectdetection_queue' (...00a47e)
16:25:51:Client request 'custom' in queue 'objectdetection_queue' (...83cf7e)
16:25:51:Client request 'custom' in queue 'objectdetection_queue' (...c18195)
16:25:51:Client request 'custom' in queue 'objectdetection_queue' (...7d07d9)
16:25:51:Client request 'custom' in queue 'objectdetection_queue' (...e44898)
16:25:52:Client request 'custom' in queue 'objectdetection_queue' (...e25ee2)
16:26:52:Client request 'custom' in queue 'objectdetection_queue' (...cce684)
16:26:52:Client request 'custom' in queue 'objectdetection_queue' (...d01fec)
16:26:52:Client request 'custom' in queue 'objectdetection_queue' (...d5f422)
16:26:53:Client request 'custom' in queue 'objectdetection_queue' (...53c7d2)
16:26:53:Client request 'custom' in queue 'objectdetection_queue' (...ac9171)
16:30:13:Object Detection (YOLOv5 .NET): Command completed in 536094 ms.
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...ed2068)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...a24196)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...e0684e)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...a7def0)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...943db6)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...e3c9f9)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...f67a5f)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...768f06)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...2309ad)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...c1a18f)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...93e26d)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...fa5965)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...b028e0)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...dc519a)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...00a47e)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...83cf7e)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...c18195)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...7d07d9)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...e44898)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...e25ee2)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...cce684)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...d01fec)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...d5f422)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...53c7d2)
16:30:13:Request 'custom' dequeued from 'objectdetection_queue' (...ac9171)
16:30:14:Object Detection (YOLOv5 .NET): Command completed in 537330 ms.
16:30:15:Object Detection (YOLOv5 .NET): Command completed in 538117 ms.
16:30:16:Object Detection (YOLOv5 .NET): Command completed in 538000 ms.
16:30:16:Object Detection (YOLOv5 .NET): Command completed in 538203 ms.
16:30:53:Object Detection (YOLOv5 .NET): Command completed in 514774 ms.
16:30:53:Object Detection (YOLOv5 .NET): Command completed in 47 ms.
16:30:54:Object Detection (YOLOv5 .NET): Command completed in 515471 ms.
16:30:54:Object Detection (YOLOv5 .NET): Command completed in 48 ms.
16:30:54:Object Detection (YOLOv5 .NET): Command completed in 515674 ms.
16:33:43:Client request 'custom' in queue 'objectdetection_queue' (...0ccd1e)
16:33:43:Request 'custom' dequeued from 'objectdetection_queue' (...0ccd1e)
16:33:43:Client request 'custom' in queue 'objectdetection_queue' (...4962bd)
16:33:43:Request 'custom' dequeued from 'objectdetection_queue' (...4962bd)
16:33:44:Client request 'custom' in queue 'objectdetection_queue' (...b79671)
16:33:44:Request 'custom' dequeued from 'objectdetection_queue' (...b79671)
16:33:44:Object Detection (YOLOv5 .NET): Command completed in 95 ms.
16:33:44:Response received (...0ccd1e): No objects found
16:33:44:Object Detection (YOLOv5 .NET): Command completed in 144 ms.
16:33:44:Response received (...4962bd): No objects found
16:33:44:Object Detection (YOLOv5 .NET): Command completed in 153 ms.
16:33:44:Response received (...b79671): No objects found
16:33:44:Client request 'custom' in queue 'objectdetection_queue' (...8f275f)
16:33:44:Request 'custom' dequeued from 'objectdetection_queue' (...8f275f)
16:33:44:Object Detection (YOLOv5 .NET): Command completed in 80 ms.
16:33:44:Response received (...8f275f): No objects found
16:33:45:Client request 'custom' in queue 'objectdetection_queue' (...e70e84)
16:33:45:Request 'custom' dequeued from 'objectdetection_queue' (...e70e84)
16:33:45:Object Detection (YOLOv5 .NET): Command completed in 80 ms.
16:33:45:Response received (...e70e84): No objects found
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Thanks very much for your report. When you're only using the CodeProject.AI Server Explorer, do you ever see these long detection times?
Thanks,
Sean Ewington
CodeProject
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Thanks for getting back!
Yes, it seems to happen when I switch models away from the Standard model the first time after the application is started. For example and to be more clear:
1. Start CodeProject.AI
2. Run Standard Benchmark in explorer, no problem
3. Select ipcam-combined
4. Hit Go - Wait quite a while as the application appears to hang.
5. After application becomes responsive again hit Go again and everything is very responsive from then on.
This same thing happens the first time blue iris asks to use the ipcam-combined model as well.
Please let me know if there are any debug logs or whatnot I can provide to help!
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Hmmm. Could you please share your System Info tab from the CodeProject.AI Server dashboard, and any logs from CodeProject.AI Server hangs, and your Blue Iris AI settings?
Thanks,
Sean Ewington
CodeProject
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Which one is better: p1000 or t400? I have the option to buy one of them, t400 is just 30$ more expensive, it's newer but has fewer CUDA cores. And so far I haven't found proper reviews about t400 for codeproject AI. I'm planning to use with 2-3 cameras 2mp.
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I've been using the T400 for years and it works very well - about a dozen cameras including a 4K camera.
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Is there a help file of sorts that explains what all the different options are? I have searched the forum and was empty handed. I would like to play around with it, but not sure what everything is. Thanks
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Given that the UI has had many features added. A article explaining, high level overview explaining the basics and how tweak the settings to optimize training. This is something that is lacking from Codeproject.AI.
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Hi.
The Background Remover module has been unavailable for several versions (and months). It is on the list of modules, but it cannot be installed.
In the docker GPU version.
Is this module available?
<a href='/Uploads/Content/Images/51fd8bc8-8906-4661-9b81-ca845f800180.png' target=_blank><img src='/Uploads/Content/Images/51fd8bc8-8906-4661-9b81-ca845f800180-small.png' width='600' height='346' /></a>
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The module does not support Linux
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Thanks.
Version 1.1 of the module worked without problem in docker.
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2.3.4 is a fail on my machine. Is there a link for older versions? Thanks!
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couldn't resist. reloaded 2.3.4. YOLO.NET appears to work, no LPR.  ![Java | [Coffee]](https://www.codeproject.com/script/Forums/Images/coffee.gif)
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I've tried codeproject/ai-server:cuda12_2-2.3.2, codeproject/ai-server:gpu, codeproject/ai-server:cuda11_7 and it continues to not use the gpu although it shows up next to the cpu reading. I'm only able to install cuda12.3. I thought 12_2 would work with it, but this is not the case. Will CPI be updated to use 12.3 cuda? Or is it possible for Google Coral TPU can be used for Facial Recognition? Thanks.
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Thanks very much for your message. Could you please share your System Info tab from the CodeProject.AI Server dashboard, and any logs you have for errors you are getting?
Currently to have the Object Detection Coral module work as a face detector you would need an object detection model for coral trained on faces. Something like: mediapipe/mediapipe/examples/coral/models at master · google/mediapipe · GitHub[^]
Thanks,
Sean Ewington
CodeProject
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```
Server version: 2.3.2-Alpha
System: Docker
Operating System: Linux (Linux 6.2.16-19-pve #1 SMP PREEMPT_DYNAMIC PMX 6.2.16-19 (2023-10-24T12:07Z))
CPUs: AMD Ryzen 5 3600 6-Core Processor (AMD)
1 CPU x 6 cores. 12 logical processors (x64)
GPU: NVIDIA GeForce GTX 1660 SUPER (6 GiB) (NVIDIA)
Driver: 545.23.06 CUDA: 12.3 (max supported: 12.3) Compute: 7.5
System RAM: 63 GiB
Target: Linux
BuildConfig: Release
Execution Env: Docker
Runtime Env: Production
.NET framework: .NET 7.0.13
Video adapter info:
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 209 MiB
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
```
```
20:57:49:face.py: CPAI_MODULE_REQUIRED_MB not found. Setting to default 0
20:57:49:face.py: USE_MPS not found. Setting to default True
20:57:49:face.py: APPDIR: /app/preinstalled-modules/FaceProcessing/intelligencelayer
20:57:49:face.py: PROFILE: desktop_cpu
20:57:49:face.py: USE_CUDA: False
20:57:49:face.py: DATA_DIR: /etc/codeproject/ai
20:57:49:face.py: MODELS_DIR: /app/preinstalled-modules/FaceProcessing/assets
20:57:49:face.py: MODE: MEDIUM
20:57:49:Running init for Face Processing
20:57:49:Face Processing: Face Processing started.
```
20:57:22:face.py: /usr/local/lib/python3.8/dist-packages/torch/cuda/__init__.py:88: UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:109.)
20:57:22:face.py: return torch._C._cuda_getDeviceCount() > 0
```
Module 'Face Processing' 1.8.1 (ID: FaceProcessing)
Module Path: <root>/preinstalled-modules/FaceProcessing
AutoStart: True
Queue: faceprocessing_queue
Platforms: windows,linux,linux-arm64,macos,macos-arm64
GPU Libraries: installed if available
GPU Enabled: enabled
Parallelism: 0
Accelerator:
Half Precis.: enable
Runtime: python3.8
Runtime Loc: Shared
FilePath: intelligencelayer/face.py
Pre installed: True
Start pause: 3 sec
LogVerbosity:
Valid: True
Environment Variables
APPDIR = <root>/preinstalled-modules/FaceProcessing/intelligencelayer
DATA_DIR = /etc/codeproject/ai
MODE = MEDIUM
MODELS_DIR = <root>/preinstalled-modules/FaceProcessing/assets
PROFILE = desktop_gpu
USE_CUDA = True
YOLOv5_AUTOINSTALL = false
YOLOv5_VERBOSE = false
Started: 28 Nov 2023 3:04:14 AM Coordinated Universal Time
LastSeen: 28 Nov 2023 3:06:07 AM Coordinated Universal Time
Status: Started
Processed: 0
Provider:
CanUseGPU: False
HardwareType: CPU
```
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Thanks very much for that. Could you please run the nvidia-smi command and then the nvcc --version command and let me know what it shows?
Thanks,
Sean Ewington
CodeProject
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Dear team!
I'm having systematic error during installation on a Windows 10 OS. Cuda 11.8. CodeProject 3.2.4 but also tested with older releases.
Particularity: PROXMOX VM with GPU GTX1070 passthrough. (should not be a problem anyway)
GPU is well recognized and working fine under Windows.
Also last week I've installed the same CodeProject inside an UBUNTU VM/GPU Passthrough and everything was working fine, CodeProject was excellent in recognition using the GPU mode.
But I want to put BLUEIRIS + CodeProject to be on the same system: so on WINDOWS.... (BI exists only on Windows)
I've uninstalled, reinstalled many times, I've tested with CUDA 12.2 then 11.8, same problem.
detect_adapter.py: ImportError: DLL load failed: The specified module could not be found.
Then CodeProject is accepting only the CPU mode and not the GPU one on Windows.
(althought the same configuration with UBUNTU VM is working fine and GPU is working well)
Here is the full log during installation. It's weird.
Could you please help me? How to solve? What to test?
I'm ready to provide every log/or make specific test.
Thank you all! 
Bye
15:53:00:System: Windows
15:53:00:Operating System: Windows (Microsoft Windows 10.0.19044)
15:53:00:CPUs: QEMU Virtual CPU version 2.5+
15:53:00: 2 CPUs x 4 cores. 4 logical processors (x64)
15:53:00:GPU: NVIDIA GeForce GTX 1070 (8 GiB) (NVIDIA)
15:53:00: Driver: 536.23 CUDA: 11.8.89 (max supported: 12.2) Compute: 6.1
15:53:00:System RAM: 8 GiB
15:53:00:Target: Windows
15:53:00:BuildConfig: Release
15:53:00:Execution Env: Native
15:53:00:Runtime Env: Production
15:53:00:.NET framework: .NET 7.0.10
15:53:00:App DataDir: C:\ProgramData\CodeProject\AI
15:53:00:Video adapter info:
15:53:00: NVIDIA GeForce GTX 1070:
15:53:00: Driver Version 31.0.15.3623
15:53:00: Video Processor NVIDIA GeForce GTX 1070
15:53:00: Microsoft Basic Display Adapter:
15:53:00: Driver Version 10.0.19041.868
15:53:00: Video Processor SeaBIOS VBE(C) 2011
15:53:00:STARTING CODEPROJECT.AI SERVER
15:53:00:RUNTIMES_PATH = C:\Program Files\CodeProject\AI\runtimes
15:53:00:PREINSTALLED_MODULES_PATH = C:\Program Files\CodeProject\AI\preinstalled-modules
15:53:00:MODULES_PATH = C:\Program Files\CodeProject\AI\modules
15:53:00:PYTHON_PATH = \bin\windows\%PYTHON_DIRECTORY%\venv\Scripts\python
15:53:00:Data Dir = C:\ProgramData\CodeProject\AI
15:53:00:Server version: 2.3.4-Beta
15:53:03:Setting up initial modules. Please be patient...
15:53:03:Installing initial module FaceProcessing.
15:53:03:Preparing to install module 'FaceProcessing'
15:53:03:Downloading module 'FaceProcessing'
15:53:04:Installing module 'FaceProcessing'
15:53:04:FaceProcessing: Installing CodeProject.AI Analysis Module
15:53:04:FaceProcessing: ========================================================================
15:53:04:FaceProcessing: CodeProject.AI Installer
15:53:04:FaceProcessing: ========================================================================
15:53:04:FaceProcessing: General CodeProject.AI setup
15:53:04:FaceProcessing: Creating Directories...Done
15:53:04:FaceProcessing: GPU support
15:53:04:FaceProcessing: CUDA Present...Yes (version 11.8)
15:53:05:FaceProcessing: ROCm Present...False
15:53:05:FaceProcessing: Installing module FaceProcessing 1.8.1
15:53:05:FaceProcessing: Installing Python 3.7
15:53:05:Server: This is the latest version
15:53:11:FaceProcessing: Downloading Python 3.7 interpreter...Expanding...Done.
15:53:25:FaceProcessing: Creating Virtual Environment (Shared)...Done
15:53:25:FaceProcessing: Confirming we have Python 3.7 in our virtual environment...present
15:53:48:FaceProcessing: Downloading YOLO models...Expanding...Done.
15:53:50:FaceProcessing: Copying contents of models.zip to assets...done
15:53:50:FaceProcessing: Cleaning up...done
15:53:50:FaceProcessing: Installing Python packages for FaceProcessing
15:53:50:FaceProcessing: [0;Installing GPU-enabled libraries: If available
15:53:54:FaceProcessing: Ensuring Python package manager (pip) is installed...Done
15:54:07:FaceProcessing: Ensuring Python package manager (pip) is up to date...Done
15:54:07:FaceProcessing: Python packages specified by requirements.windows.cuda.txt
15:54:09:FaceProcessing: - Installing urllib3, the HTTP client for Python...(✔️ checked) Done
15:54:31:FaceProcessing: - Installing Pandas, a data analysis / data manipulation tool...(✔️ checked) Done
15:55:05:FaceProcessing: - Installing CoreMLTools, for working with .mlmodel format models...(✔️ checked) Done
15:55:15:FaceProcessing: - Installing OpenCV, the Open source Computer Vision library...(✔️ checked) Done
15:55:18:FaceProcessing: - Installing Pillow, a Python Image Library...(✔️ checked) Done
15:55:36:FaceProcessing: - Installing SciPy, a library for mathematics, science, and engineering...(✔️ checked) Done
15:55:36:FaceProcessing: - Installing PyYAML, a library for reading configuration files...Already installed
15:57:38:FaceProcessing: - Installing PyTorch, an open source machine learning framework...(✔️ checked) Done
15:59:28:FaceProcessing: - Installing TorchVision, for working with computer vision models...(✔️ checked) Done
16:00:04:FaceProcessing: - Installing Seaborn, a data visualization library based on matplotlib...(✔️ checked) Done
16:00:04:FaceProcessing: Installing Python packages for the CodeProject.AI Server SDK
16:00:05:FaceProcessing: Ensuring Python package manager (pip) is installed...Done
16:00:07:FaceProcessing: Ensuring Python package manager (pip) is up to date...Done
16:00:07:FaceProcessing: Python packages specified by requirements.txt
16:00:08:FaceProcessing: - Installing Pillow, a Python Image Library...Already installed
16:00:09:FaceProcessing: - Installing Charset normalizer...Already installed
16:00:14:FaceProcessing: - Installing aiohttp, the Async IO HTTP library...(✔️ checked) Done
16:00:16:FaceProcessing: - Installing aiofiles, the Async IO Files library...(✔️ checked) Done
16:00:18:FaceProcessing: - Installing py-cpuinfo to allow us to query CPU info...(✔️ checked) Done
16:00:19:FaceProcessing: - Installing Requests, the HTTP library...Already installed
16:00:19:FaceProcessing: Setup complete
16:00:19:Module FaceProcessing installed successfully.
16:00:19:
16:00:19:Module 'Face Processing' 1.8.1 (ID: FaceProcessing)
16:00:19:Module Path: C:\Program Files\CodeProject\AI\modules\FaceProcessing
16:00:19:AutoStart: True
16:00:19:Queue: faceprocessing_queue
16:00:19:Platforms: windows,linux,linux-arm64,macos,macos-arm64
16:00:19:GPU Libraries: installed if available
16:00:19:GPU Enabled: enabled
16:00:19:Parallelism: 0
16:00:19:Accelerator:
16:00:19:Half Precis.: enable
16:00:19:Runtime: python3.7
16:00:19:Runtime Loc: Shared
16:00:19:FilePath: intelligencelayer\face.py
16:00:19:Pre installed: False
16:00:19:Start pause: 3 sec
16:00:19:LogVerbosity:
16:00:19:Valid: True
16:00:19:Environment Variables
16:00:19:APPDIR = %CURRENT_MODULE_PATH%\intelligencelayer
16:00:19:DATA_DIR = %DATA_DIR%
16:00:19:MODE = MEDIUM
16:00:19:MODELS_DIR = %CURRENT_MODULE_PATH%\assets
16:00:19:PROFILE = desktop_gpu
16:00:19:USE_CUDA = True
16:00:19:YOLOv5_AUTOINSTALL = false
16:00:19:YOLOv5_VERBOSE = false
16:00:19:
16:00:19:Started Face Processing module
16:00:19:Installer exited with code 0
16:00:19:Installing initial module ObjectDetectionNet.
16:00:19:Preparing to install module 'ObjectDetectionNet'
16:00:19:Downloading module 'ObjectDetectionNet'
16:00:20:Installing module 'ObjectDetectionNet'
16:00:20:ObjectDetectionNet: Installing CodeProject.AI Analysis Module
16:00:20:ObjectDetectionNet: ========================================================================
16:00:20:ObjectDetectionNet: CodeProject.AI Installer
16:00:20:ObjectDetectionNet: ========================================================================
16:00:20:ObjectDetectionNet: General CodeProject.AI setup
16:00:20:ObjectDetectionNet: Creating Directories...Done
16:00:20:ObjectDetectionNet: GPU support
16:00:20:ObjectDetectionNet: CUDA Present...Yes (version 11.8)
16:00:20:ObjectDetectionNet: ROCm Present...False
16:00:20:ObjectDetectionNet: Installing module ObjectDetectionNet 1.7.1
16:00:22:Module FaceProcessing started successfully.
16:00:24:face.py: GPU in use: NVIDIA GeForce GTX 1070
16:00:24:face.py: Traceback (most recent call last):
16:00:24:face.py: File "C:\Program Files\CodeProject\AI\modules\FaceProcessing\intelligencelayer\face.py", line 41, in
16:00:24:face.py: from process import YOLODetector
16:00:24:face.py: File "C:\Program Files\CodeProject\AI\modules\FaceProcessing\intelligencelayer\.\process.py", line 2, in
16:00:24:face.py: import cv2
16:00:24:face.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\cv2\__init__.py", line 181, in
16:00:24:face.py: bootstrap()
16:00:24:face.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\cv2\__init__.py", line 153, in bootstrap
16:00:24:face.py: native_module = importlib.import_module("cv2")
16:00:24:face.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\lib\importlib\__init__.py", line 127, in import_module
16:00:24:face.py: return _bootstrap._gcd_import(name[level:], package, level)
16:00:24:face.py: ImportError: DLL load failed: The specified module could not be found.
16:00:24:Module FaceProcessing has shutdown
16:00:24:face.py: has exited
16:00:30:ObjectDetectionNet: Downloading ObjectDetectionNet-DirectML-1.7.1.zip...Expanding...Done.
16:00:31:ObjectDetectionNet: Copying contents of ObjectDetectionNet-DirectML-1.7.1.zip to ...done
16:00:31:ObjectDetectionNet: Cleaning up...done
16:00:41:ObjectDetectionNet: Downloading YOLO ONNX models...Expanding...Done.
16:00:42:ObjectDetectionNet: Copying contents of yolonet-models.zip to assets...done
16:00:42:ObjectDetectionNet: Cleaning up...done
16:00:52:ObjectDetectionNet: Downloading Custom YOLO ONNX models...Expanding...Done.
16:00:52:ObjectDetectionNet: Copying contents of yolonet-custom-models.zip to custom-models...done
16:00:52:ObjectDetectionNet: Cleaning up...done
16:00:52:ObjectDetectionNet: Setup complete
16:00:52:Module ObjectDetectionNet installed successfully.
16:00:52:Module ObjectDetectionNet not configured to AutoStart.
16:00:52:Installer exited with code 0
16:00:52:Installing initial module ObjectDetectionYolo.
16:00:52:Preparing to install module 'ObjectDetectionYolo'
16:00:52:Downloading module 'ObjectDetectionYolo'
16:00:52:Installing module 'ObjectDetectionYolo'
16:00:54:ObjectDetectionYolo: Installing CodeProject.AI Analysis Module
16:00:54:ObjectDetectionYolo: ========================================================================
16:00:54:ObjectDetectionYolo: CodeProject.AI Installer
16:00:54:ObjectDetectionYolo: ========================================================================
16:00:54:ObjectDetectionYolo: General CodeProject.AI setup
16:00:54:ObjectDetectionYolo: Creating Directories...Done
16:00:54:ObjectDetectionYolo: GPU support
16:00:54:ObjectDetectionYolo: CUDA Present...Yes (version 11.8)
16:00:54:ObjectDetectionYolo: ROCm Present...False
16:00:54:ObjectDetectionYolo: Installing module ObjectDetectionYolo 1.7.1
16:00:54:ObjectDetectionYolo: Installing Python 3.7
16:00:54:ObjectDetectionYolo: Python 3.7 is already installed
16:00:54:ObjectDetectionYolo: Creating Virtual Environment (Shared)...Virtual Environment already present
16:00:55:ObjectDetectionYolo: Confirming we have Python 3.7 in our virtual environment...present
16:01:01:ObjectDetectionYolo: Downloading Standard YOLO models...Expanding...Done.
16:01:01:ObjectDetectionYolo: Copying contents of models-yolo5-pt.zip to assets...done
16:01:01:ObjectDetectionYolo: Cleaning up...done
16:01:11:ObjectDetectionYolo: Downloading Custom YOLO models...Expanding...Done.
16:01:11:ObjectDetectionYolo: Copying contents of custom-models-yolo5-pt.zip to custom-models...done
16:01:11:ObjectDetectionYolo: Cleaning up...done
16:01:11:ObjectDetectionYolo: Installing Python packages for ObjectDetectionYolo
16:01:11:ObjectDetectionYolo: [0;Installing GPU-enabled libraries: If available
16:01:13:ObjectDetectionYolo: Ensuring Python package manager (pip) is installed...Done
16:01:15:ObjectDetectionYolo: Ensuring Python package manager (pip) is up to date...Done
16:01:15:ObjectDetectionYolo: Python packages specified by requirements.windows.cuda.txt
16:01:16:ObjectDetectionYolo: - Installing Pandas, a data analysis / data manipulation tool...Already installed
16:01:17:ObjectDetectionYolo: - Installing CoreMLTools, for working with .mlmodel format models...Already installed
16:01:18:ObjectDetectionYolo: - Installing OpenCV, the Open source Computer Vision library...Already installed
16:01:18:ObjectDetectionYolo: - Installing Pillow, a Python Image Library...Already installed
16:01:19:ObjectDetectionYolo: - Installing SciPy, a library for mathematics, science, and engineering...Already installed
16:01:20:ObjectDetectionYolo: - Installing PyYAML, a library for reading configuration files...Already installed
16:01:21:ObjectDetectionYolo: - Installing PyTorch, an open source machine learning framework...Already installed
16:01:22:ObjectDetectionYolo: - Installing TorchVision, for working with computer vision models...Already installed
16:03:40:ObjectDetectionYolo: - Installing Ultralytics YoloV5 package for object detection in images...(✔️ checked) Done
16:03:41:ObjectDetectionYolo: - Installing Seaborn, a data visualization library based on matplotlib...Already installed
16:03:41:ObjectDetectionYolo: Installing Python packages for the CodeProject.AI Server SDK
16:03:42:ObjectDetectionYolo: Ensuring Python package manager (pip) is installed...Done
16:03:45:ObjectDetectionYolo: Ensuring Python package manager (pip) is up to date...Done
16:03:45:ObjectDetectionYolo: Python packages specified by requirements.txt
16:03:46:ObjectDetectionYolo: - Installing Pillow, a Python Image Library...Already installed
16:03:47:ObjectDetectionYolo: - Installing Charset normalizer...Already installed
16:03:48:ObjectDetectionYolo: - Installing aiohttp, the Async IO HTTP library...Already installed
16:03:49:ObjectDetectionYolo: - Installing aiofiles, the Async IO Files library...Already installed
16:03:50:ObjectDetectionYolo: - Installing py-cpuinfo to allow us to query CPU info...Already installed
16:03:50:ObjectDetectionYolo: - Installing Requests, the HTTP library...Already installed
16:03:50:ObjectDetectionYolo: Setup complete
16:03:50:Module ObjectDetectionYolo installed successfully.
16:03:50:
16:03:50:Module 'Object Detection (YOLOv5 6.2)' 1.7.1 (ID: ObjectDetectionYolo)
16:03:50:Module Path: C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo
16:03:50:AutoStart: True
16:03:50:Queue: objectdetection_queue
16:03:50:Platforms: all
16:03:50:GPU Libraries: installed if available
16:03:50:GPU Enabled: enabled
16:03:50:Parallelism: 0
16:03:50:Accelerator:
16:03:50:Half Precis.: enable
16:03:50:Runtime: python3.7
16:03:50:Runtime Loc: Shared
16:03:50:FilePath: detect_adapter.py
16:03:50:Pre installed: False
16:03:50:Start pause: 1 sec
16:03:50:LogVerbosity:
16:03:50:Valid: True
16:03:50:Environment Variables
16:03:50:APPDIR = %CURRENT_MODULE_PATH%
16:03:50:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
16:03:50:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
16:03:50:MODEL_SIZE = Medium
16:03:50:USE_CUDA = True
16:03:50:YOLOv5_AUTOINSTALL = false
16:03:50:YOLOv5_VERBOSE = false
16:03:50:
16:03:50:Started Object Detection (YOLOv5 6.2) module
16:03:50:Installer exited with code 0
16:03:51:Module ObjectDetectionYolo started successfully.
16:03:52:detect_adapter.py: Traceback (most recent call last):
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect_adapter.py", line 20, in
16:03:52:detect_adapter.py: from detect import do_detection
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 8, in
16:03:52:detect_adapter.py: from yolov5.models.common import DetectMultiBackend, AutoShape
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\__init__.py", line 1, in
16:03:52:detect_adapter.py: from yolov5.helpers import YOLOv5
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\helpers.py", line 3, in
16:03:52:detect_adapter.py: from yolov5.models.common import AutoShape, DetectMultiBackend
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 18, in
16:03:52:detect_adapter.py: import cv2
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\cv2\__init__.py", line 181, in
16:03:52:detect_adapter.py: bootstrap()
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\cv2\__init__.py", line 153, in bootstrap
16:03:52:detect_adapter.py: native_module = importlib.import_module("cv2")
16:03:52:detect_adapter.py: File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\lib\importlib\__init__.py", line 127, in import_module
16:03:52:detect_adapter.py: return _bootstrap._gcd_import(name[level:], package, level)
16:03:52:detect_adapter.py: ImportError: DLL load failed: The specified module could not be found.
16:03:52:Module ObjectDetectionYolo has shutdown
16:03:52:detect_adapter.py: has exited
modified 9-Nov-23 10:37am.
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Today I've tested also with 1050Ti card on Ubuntu: it's working fine, as with my GTX1070.
Please any tips about how to solve? import CV2 seems to be the problem, how to force a python lib update using venv on CodeProject??
And I've tested with the WINDOWS as problem remains the same with 1050Ti:
detect_adapter.py: ImportError: DLL load failed: The specified module could not be found.
Any help please ???
modified 15-Nov-23 4:26am.
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Chris, Mike & others: any help please?! 
this is the first time I have such problem, it seems that python lib or DLL is not correctly loaded but what's the best approach to solve this problem?
Thanks for your help and tips!
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