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We made a boo-boo. Please trying upgrading the module again.
Thanks,
Sean Ewington
CodeProject
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Follow-up question though... super resolution seems to run, but with CPU only?
For some reason, GPU libraries were not installed???
Image detection YOLO v8 runs in GPU...
09:33:27:Preparing to install module 'SuperResolution'
09:33:27:Downloading module 'SuperResolution'
09:33:27:Installing module 'SuperResolution'
09:33:28:SuperResolution: Installing CodeProject.AI Analysis Module
09:33:28:SuperResolution: ======================================================================
09:33:28:SuperResolution: CodeProject.AI Installer
09:33:28:SuperResolution: ======================================================================
09:33:28:SuperResolution: 353.4Gb of 487Gb available on Windows
09:33:28:SuperResolution: General CodeProject.AI setup
09:33:28:SuperResolution: Creating Directories...done
09:33:28:SuperResolution: GPU support
09:33:29:SuperResolution: CUDA Present...Yes (CUDA 11.7, cuDNN 8.5)
09:33:29:SuperResolution: ROCm Present...No
09:33:31:SuperResolution: Reading SuperResolution settings.......done
09:33:31:SuperResolution: Installing module Super Resolution 2.0.0
09:33:31:SuperResolution: Installing Python 3.9
09:33:31:SuperResolution: Python 3.9 is already installed
09:33:38:SuperResolution: Creating Virtual Environment (Local)...done
09:33:38:SuperResolution: Confirming we have Python 3.9 in our virtual environment...present
09:33:38:SuperResolution: No custom setup steps for this module.
09:33:38:SuperResolution: Installing Python packages for Super Resolution
09:33:38:SuperResolution: [0;Installing GPU-enabled libraries: No
09:33:41:SuperResolution: Ensuring Python package manager (pip) is installed...done
09:33:52:SuperResolution: Ensuring Python package manager (pip) is up to date...done
09:33:52:SuperResolution: Python packages specified by requirements.txt
09:34:35:SuperResolution: - Installing ONNX, the Open Neural Network Exchange library...(✅ checked) done
09:35:43:SuperResolution: - Installing ONNX runtime, the scoring engine for ONNX models...(✅ checked) done
09:35:54:SuperResolution: - Installing resizeimage, which provides functions for easily resizing images...(✅ checked) done
09:35:55:SuperResolution: - Installing Pillow, a Python Image Library...Already installed
09:37:02:SuperResolution: - Installing PyTorch, for Tensor computation and Deep neural networks...(✅ checked) done
09:37:45:SuperResolution: - Installing NumPy, a package for scientific computing...Already installed
09:37:45:SuperResolution: Installing Python packages for the CodeProject.AI Server SDK
09:37:49:SuperResolution: Ensuring Python package manager (pip) is installed...done
09:37:52:SuperResolution: Ensuring Python package manager (pip) is up to date...done
09:37:52:SuperResolution: Python packages specified by requirements.txt
09:37:54:SuperResolution: - Installing Pillow, a Python Image Library...Already installed
09:37:55:SuperResolution: - Installing Charset normalizer...Already installed
09:38:04:SuperResolution: - Installing aiohttp, the Async IO HTTP library...(✅ checked) done
09:38:08:SuperResolution: - Installing aiofiles, the Async IO Files library...(✅ checked) done
09:38:11:SuperResolution: - Installing py-cpuinfo to allow us to query CPU info...(✅ checked) done
09:38:13:SuperResolution: - Installing Requests, the HTTP library...Already installed
09:38:14:SuperResolution: Scanning modulesettings for downloadable models...No models specified
09:38:22:SuperResolution: Self test: Self-test passed
09:38:22:SuperResolution: Module setup time 00:04:52.89
09:38:22:SuperResolution: Setup complete
09:38:22:SuperResolution: Total setup time 00:04:54.16
09:38:22:Module SuperResolution installed successfully.
09:38:22:Module SuperResolution not configured to AutoStart.
09:38:22:Installer exited with code 0
----- Running log... ------
09:39:23:Update SuperResolution. Setting AutoStart=true
09:39:23:Restarting Super Resolution to apply settings change
09:39:23:
09:39:23:Module 'Super Resolution' 2.0.0 (ID: SuperResolution)
09:39:23:Valid: True
09:39:23:Module Path: <root>\modules\SuperResolution
09:39:24:AutoStart: True
09:39:24:Queue: superresolution_queue
09:39:24:Runtime: python3.9
09:39:24:Runtime Loc: Local
09:39:24:FilePath: superres_adapter.py
09:39:24:Start pause: 0 sec
09:39:24:Parallelism: 1
09:39:24:LogVerbosity:
09:39:24:Platforms: all
09:39:24:GPU Libraries: not installed
09:39:24:GPU Enabled: disabled
09:39:24:Accelerator:
09:39:24:Half Precis.: enable
09:39:24:Environment Variables
09:39:24:PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION = python
09:39:24:
09:39:24:Started Super Resolution module
09:39:37:Update SuperResolution. Setting AutoStart=false
09:39:37:Stopping Super Resolution
09:39:37:Sending shutdown request to python/SuperResolution
09:39:38:superres_adapter.py: Super Resolution started.
09:39:38:Module SuperResolution has shutdown
09:39:38:superres_adapter.py: has exited
09:40:10:SuperResolution went quietly
modified 9-Apr-24 11:21am.
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Despite what the logs say, can you please confirm the GPU isn't actually getting used for the Super Resolution module?
Thanks,
Sean Ewington
CodeProject
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here is the log:
reating runtimes path '/app/runtimes'
Creating downloaded models path '/app/downloads/models'
** Old modulesettings schema found for SuperResolution, but not compatible with this server version.
** Old modulesettings schema found for FaceProcessing, but not compatible with this server version.
** Old modulesettings schema found for ALPR, but not compatible with this server version.
** Old modulesettings schema found for OCR, but not compatible with this server version.
Unable to start the server: An item with the same key has already been added. Key: FaceProcessing.
Check that another instance is not running on the same port.
modified 17-Apr-24 13:41pm.
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Can you please look in your /modules folder and list the folders there?
Could also be that you simply need to re-install the module. What platform are you running on?
Thanks,
Sean Ewington
CodeProject
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I had alot of extras that was related to non gpu use and other enhancements.
Tried uninstalling and reinstalling, which didnt help.
Once i deleted the folders for the docker, it worked. I reinstalled the add-ons, which broke it again.
Re-deleted, left it vanilla and its still working since yesterday.
Running in unraid.
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Thanks very much for the follow-up. Could you please let me know which add-ons you mean? (or modules?)
Thanks,
Sean Ewington
CodeProject
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License Plate Reader, Optical Character Recognition, Super Resolution, Training for YoloV5 6.2
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Thanks again. This issue has been found, fixed and will be available in the next version.
Thanks,
Sean Ewington
CodeProject
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I know the YoloV5 6.2 training module has been around for a bit now, I'm wondering if a v8 version is being planned or will be coming at any point in the future?
modified 16-Apr-24 12:06pm.
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Yes! At some point.
Thanks,
Sean Ewington
CodeProject
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After upgrading from v2.5.6 to 2.6.2 the docker container fails with following message:
Creating runtimes path '/app/runtimes'
Creating downloaded models path '/app/downloads/models'
Unable to start the server: An item with the same key has already been added. Key: ObjectDetectionCoral.
Check that another instance is not running on the same port.
Press Enter to close.
Does anybody know how to fix that issue?
Thanks a lot
Tbs
modified 15-Apr-24 13:01pm.
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Can you please look in your /modules folder and list the folders there?
Could also be that you simply need to re-install the module. What platform are you running on?
Thanks,
Sean Ewington
CodeProject
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This issue has been found, fixed and will be available in the next version.
Thanks,
Sean Ewington
CodeProject
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In future, Face Recognition can sync database?
or something I miss information for do that?
modified 16-Apr-24 12:05pm.
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No plans at the moment, sorry.
cheers
Chris Maunder
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Error message:
14:15:31:Started Object Detection (YOLOv5 6.2) module
14:15:31:detect_adapter.py: Traceback (most recent call last):
14:15:31:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\detect_adapter.py", line 13, in
14:15:31:detect_adapter.py: from module_runner import ModuleRunner
14:15:31:detect_adapter.py: File "../../SDK/Python\module_runner.py", line 30, in
14:15:31:detect_adapter.py: import aiohttp
14:15:31:detect_adapter.py: ModuleNotFoundError: No module named 'aiohttp'
modified 16-Apr-24 12:05pm.
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It fails if you choose to only install Yolo 6.2, if you set it to install all the default options of Yolo 5 and face, it works.
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Is there a way to prevent the TPU from automatically shutting down after 120 seconds of inactivity? It takes quite a while for an image to be recognized afterwards.
12:41:19:System: Docker (fa0761f44809)
12:41:19:Operating System: Linux (Ubuntu 22.04)
12:41:19:CPUs: 13th Gen Intel(R) Core(TM) i5-1340P (Intel)
12:41:19: 1 CPU x 12 cores. 16 logical processors (x64)
12:41:19:System RAM: 31 GiB
12:41:19:Platform: Linux
12:41:19:BuildConfig: Release
12:41:19:Execution Env: Docker
12:41:19:Runtime Env: Production
12:41:19:Runtimes installed:
12:41:19: .NET runtime: 7.0.17
12:41:19: .NET SDK: Not found
12:41:19: Default Python: 3.10.12
12:41:19: Go: Not found
12:41:19: NodeJS: Not found
12:41:19: Rust: Not found
12:41:19:App DataDir: /etc/codeproject/ai
12:41:19:Video adapter info:
12:41:19:STARTING CODEPROJECT.AI SERVER
12:41:19:RUNTIMES_PATH = /app/runtimes
12:41:19:PREINSTALLED_MODULES_PATH = /app/preinstalled-modules
12:41:19:DEMO_MODULES_PATH = /app/demos/modules
12:41:19:MODULES_PATH = /app/modules
12:41:19:PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
12:41:19:Data Dir = /etc/codeproject/ai
12:41:19:Server version: 2.6.2
12:45:04:Started Object Detection (Coral) module
12:45:08:objectdetection_coral_adapter.py: TPU detected
12:45:08:objectdetection_coral_adapter.py: Attempting multi-TPU initialisation
12:45:08:objectdetection_coral_adapter.py: Supporting multiple Edge TPUs
12:45:48:Response rec'd from Object Detection (Coral) command 'detect' (...8c51a5) ['Found car, car, car...'] took 245ms
12:45:56:Response rec'd from Object Detection (Coral) command 'detect' (...3a38f2) ['Found car, car, car...'] took 75ms
12:45:57:Response rec'd from Object Detection (Coral) command 'detect' (...1c094c) ['Found car, car, car...'] took 80ms
12:45:57:Response rec'd from Object Detection (Coral) command 'detect' (...cb4a86) ['Found car, car, car...'] took 74ms
12:45:58:Response rec'd from Object Detection (Coral) command 'detect' (...08b14a) ['Found car, car, car...'] took 75ms
12:45:58:Response rec'd from Object Detection (Coral) command 'detect' (...ec2923) ['Found car, car, car...'] took 78ms
12:46:45:Response rec'd from Object Detection (Coral) command 'custom' (...229416) ['Found car, car, car...'] took 80ms
12:46:46:Response rec'd from Object Detection (Coral) command 'detect' (...d7ac0a) ['Found car, car, car...'] took 74ms
12:46:47:Response rec'd from Object Detection (Coral) command 'custom' (...883f24) ['Found car, car, car...'] took 74ms
12:48:50:objectdetection_coral_adapter.py: WARNING:root:No work in 120.0 seconds, watchdog shutting down TPUs.
12:56:18:Response rec'd from Object Detection (Coral) command 'detect' (...0b333f) ['Found car, person, car...'] took 3430ms
13:04:01:Response rec'd from Object Detection (Coral) command 'custom' (...14da1e) ['Found car, car, car...'] took 54ms
modified 5-Apr-24 17:46pm.
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Thanks for pointing this out. I'm not sure why it'd take so long to start up. (For example, it looks like your first iteration took 245ms.) The intent is if something is stalled for whatever reason in the processing pipeline, the watchdog will reset things in the background so CPAI doesn't sit stalled for hours.
I've added some code that should make the recycle process faster and I've increased the watchdog timeout so it takes longer to trigger. Likely in the next CPAI release. Hopefully that'll fix the problem for you.
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I also experience this, with the first detection after the TPU has shutdown often taking > 2 seconds.. which seems to have the knock on effect of making a TPU equipped host report a very high detection time to mesh hosts, and thus never receiving any mesh offload work unless I run a load of detections through manually to get the time down 
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With object detection yolov5.net 1.10.1 i just update and i cant get it to use the gpu ( i have a P1000) i select it in the menu it restarts and go back to CPU (DirectML) is this a bug ?
What I have tried:
ReInstall object detection yolov5.net 1.10.1 , pc restart , reinstalling CPAI
modified 5-Apr-24 17:46pm.
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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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