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IF YOU ARE HAVING A PROBLEM
- Take a look at the logs in
C:\Program Files\CodeProject\AI\logs and see if there's anything in there that screams 'something broke'.
- Check the FAQs in the CodeProject.AI Server documentation
- Make sure you've tested the server using the Explorer (blue link, top middle of the dashboard) to ensure it's a server issue rather than something else such as Blue Iris or another app using CodeProject.AI server.
- If there's no obvious answer, then copy and paste into a message the contents of the System Info tab, describe what you are doing, and what you see, and what you would expect.
Always include a copy and paste from the System Info tab of the dashboard. It gives us a ton of info on your setup. If an individual module is failing, click the 'Info' button to the right of the module's name in the status list and copy and paste that info too.
How to reinstall a module
Option 1. Go to the install modules tab on the dashboard and try re-installing the package. Make sure you have enough disk space and a reliable internet connection.
Option 2: (Option 1 with a vengeance): If that fails, head to the module's folder ([app root]\modules\module-id), open a terminal in admin mode, and run ..\..\setup. This will force a manual reinstall using the install script.
Docker: In Docker you will need to open a terminal into the docker container. You can do this using Docker Desktop, or Visual Studio Code with the Docker remote extension, or on the command using using docker attach. Then do a cd /app/modules/module-id where module-id is the id of the module you need to resinstall. Next, run sudo bash ../../setup.sh --verbosity info to force a manual reinstall of that module. (Set verbosity as quiet, info or loud to get less or more info)
cheers
Chris Maunder
modified 18-Feb-24 15:48pm.
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If you are a Blue Iris user and you are using custom models, then you would notice that the option, in Blue Iris, to set the custom model location is greyed out. This is because Blue Iris does not currently make changes to CodeProject.AI Server's settings. It can be done by manually starting CodeProject.AI with command line parameters (not a great solution), or editing the module settings files (a little messy), or setting system-wide environment variables (way easier). For version 1.6 we added an API to allow any app to change our settings programmatically, and we take care of stopping/restarting things and persisting the changes.
So: Blue Iris doesn't currently change CodeProject.AI Server's settings, so it doesn't provide you a way to change the custom model folder location from within Blue Iris.
Blue Iris will still use the contents of this folder to determine the calls it makes. If you don't specify a model to use in the Custom Models textbox, then Blue Iris will use all models in the custom models folder that it knows about.
Here we've specified a specific model to use. The Blue Iris help file explains more about how this works, including inclusive and exclusive filters on the models it finds.
CodeProject.AI Server doesn't know about Blue Iris' folder, so it can't tell what models it may be expected to use, nor can it tell Blue Iris about what models CodeProject.AI server has available. Our API allows Blue Iris to get a list of the AI models installed with CodeProject.AI Server, and also to set the folder where these models reside. But Blue Iris doesn't, yet, use that API.
So we do a hack.
At install time we sniff the registry to find where Blue Iris thinks the custom models should be. We then make empty copies of the models that we have, and copy them into that folder. If the folder doesn't exist (eg you were using C:\Program Files\CodeProject\AI\AnalysisLayer\CustomObjectDetection\assets, which no longer exists) then we create that folder, and then copy over the empty files.
When Blue Iris looks in that folder to decide what custom calls it can make, it sees the models, notes their names, and uses those names in the calls. CodeProject.AI Server has those models, so when the calls come through we can process them.
Blue Iris doesn't use the models. It uses the list of model names.
If you have your own models in the Blue Iris folder
You will need to copy them to the CodeProject.AI server's custom model folder (by default this is C:\Program Files\CodeProject\AI\AnalysisLayer\ObjectDetectionYolo\custom-models)
If you've modified the registry and have your own custom models
If you were using a folder in C:\Program Files\CodeProject\AI\AnalysisLayer\CustomObjectDetection\ (which no longer existed after the upgrade, but was recreated by our hack) you'll need to re-copy your custom model into that folder.
The simplest solutions are:
- Modify the registry (Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Perspective Software\Blue Iris\Options\AI, key 'deepstack_custompath') so Blue Iris looks in
C:\Program Files\CodeProject\AI\AnalysisLayer\ObjectDetectionYolo\custom-models for custom models, and copy your models into there.
or
- Modify
C:\Program Files\CodeProject\AI\AnalysisLayer\ObjectDetectionYolo\modulesettings.json file and set CUSTOM_MODELS_DIR to be whatever Blue Iris thinks the custom model folder is.
cheers
Chris Maunder
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Hi,
Since the install of the latest version of CP on my Blue Iris server, I get the message "Alert Cancelled AI not responding".
Consequently I do not get any notification on my phone when someone triggers a camera because there is no analysis done.
I reinstalled CP, no success.
Any suggestion on whatto do next?
I am on Windows 10
Thanks,
Michel.
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It works now
I uninstalled CP, then I used the software Everything from Voidtools to find every single file left that had CodeProject in it's name and deleted them all, then reinstalled CP and restarted the server and it works as it should.
Thanks
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Issue exists only with newer CPAI builds, occurs several times a day on different hardware (Intel with Tesla P4 vs Ryzen with RTX3090)
19:00:49:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\detect.py", line 141, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (48) must match the size of tensor b (60) at non-singleton dimension 2
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Hello,
Since Raspberry just announced their new "Raspberry Pi AI Kit" ( https://www.raspberrypi.com/products/ai-kit/[^] ) what would the possibility of getting a Hailo AI module natively added to CP.AI? I'm currently using a dual edge Coral TPU on my Pi5 but it has it's limitations
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Yeah I saw that - $70 for some serious power is pretty awesome.
The Hailo stack seems straightforward (though their site leaves something to be desired). Without access to the hardware we can't do anything here, but I'm sure it would be a very straightforward exercise for someone to adapt any of the existing object detection modules to use the Hailo models and TensorRT. The segmentation example, for instance, seems super simple.
cheers
Chris Maunder
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System specs below. I borrowed my sons video cards (2060 and 1080) to experiment and watched the system log times in BI, the ms remained unchanged. Last time I did this the response times all dropped under 100ms.
I did not get a screen cap but when the AI starts I get the use CUDA = True.
Is it possible the AI is using the Intel integrated graphics on the CPU instead of the 1050ti??
Server version: 2.6.5
System: Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs: Intel(R) Core(TM) i7-8086K CPU @ 4.00GHz (Intel)
1 CPU x 6 cores. 12 logical processors (x64)
GPU (Primary): NVIDIA GeForce GTX 1050 Ti (4 GiB) (NVIDIA)
Driver: 555.85, CUDA: 11.8.89 (up to: 12.5), Compute: 6.1, cuDNN: 8.5
System RAM: 16 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.15
.NET SDK: 7.0.405
Default Python: Not found
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
Intel(R) UHD Graphics 630:
Driver Version 31.0.101.2111
Video Processor Intel(R) UHD Graphics Family
NVIDIA GeForce GTX 1050 Ti:
Driver Version 32.0.15.5585
Video Processor NVIDIA GeForce GTX 1050 Ti
System GPU info:
GPU 3D Usage 34%
GPU RAM Usage 3.9 GiB
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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Did you install the module with the GPU(s) in place? The installer will install the libraries required for the hardware it sees at the time. It can't install updated libraries and drivers for hardware that's added later.
Try uninstalling / reinstalling the YOLO module with the GPUs in place.
cheers
Chris Maunder
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Hi, the 1050ti was in the system when YOLO was installed. I just upgraded the system from 2.5 RC4 where YOLO was working properly, see screencap below. I will try reinstalling.
thanks!
Quick follow up b4 I reinstall. I did custom and unchecked everything but YOLO8 when I installed, now I have no option to install other modules (see screencap below), is there something I need to check to be able to install other versions of YOLO at a later date if I want to experiment with them?
Thanks!
modified 3 days ago.
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So I reinstalled and YOLOv8 is now reporting GPU(CUDA) usage even after a system reboot. Response times in BI seem unchanged so maybe it was using GPU all along.
Will report back in a few days if nothing is changed.
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I just updated the CPAI from 2.6.2 to 2.6.5. For some reason, I'm having problems to download the segmentation model and the custom models for the YOLOv8 for some reason. I've re-installed the YOLOv8 but the problem remains.
When I tried to download the models, I got the following error:
06:21:02:Response rec'd from Object Detection (YOLOv8) command 'segment' (...cad0dd)
06:21:02:Object Detection (YOLOv8): Unable to create YOLO detector for model yolov8m-seg
06:21:09:Preparing to download model 'objectsegmentation-coco-yolov8-pt-nsmlx.zip' for module ObjectDetectionYOLOv8
06:21:09:Downloading model 'objectsegmentation-coco-yolov8-pt-nsmlx.zip' to 'C:\Program Files\CodeProject\AI\downloads\modules\ObjectDetectionYOLOv8\objectsegmentation-coco-yolov8-pt-nsmlx.zip'
06:21:39:Unable to download and install objectsegmentation-coco-yolov8-pt-nsmlx.zip: Unable to download 'objectsegmentation-coco-yolov8-pt-nsmlx.zip'. Error: The request was canceled due to the configured HttpClient.Timeout of 30 seconds elapsing.
06:27:08:Preparing to download model 'objectdetection-custom-yolov8-pt-m.zip' for module ObjectDetectionYOLOv8
06:27:08:Downloading model 'objectdetection-custom-yolov8-pt-m.zip' to 'C:\Program Files\CodeProject\AI\downloads\modules\ObjectDetectionYOLOv8\objectdetection-custom-yolov8-pt-m.zip'
06:27:38:Unable to download and install objectdetection-custom-yolov8-pt-m.zip: Unable to download 'objectdetection-custom-yolov8-pt-m.zip'. Error: The request was canceled due to the configured HttpClient.Timeout of 30 seconds elapsing.
Any idea what could have gone wrong?
Note: I have no problem downloading it when I was using 2.6.2. Not sure if something has changed or not.
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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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Thanks for that. I realize it's an unlikely culprit, but what's your bandwidth like? Even if there's no issue there, you might consider increasing your ModuleInstallTimeout value in appsettings.json. You can find that in C:\Program Files\CodeProject\AI\Server.
Thanks,
Sean Ewington
CodeProject
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Upload is 72 Mbs, Download is 82 Mbs. I checked the settings you are saying but it seems like it was already set to 20 minutes. However, I noticed the connection time out is 30 seconds. See the log:
22:18:02:Started Object Detection (YOLOv8) module
22:18:04:Server: This is the latest version
22:18:34:Preparing to download model 'objectsegmentation-coco-yolov8-pt-nsmlx.zip' for module ObjectDetectionYOLOv8
22:18:34:Downloading model 'objectsegmentation-coco-yolov8-pt-nsmlx.zip' to 'C:\Program Files\CodeProject\AI\downloads\modules\ObjectDetectionYOLOv8\objectsegmentation-coco-yolov8-pt-nsmlx.zip'
22:19:04:Unable to download and install objectsegmentation-coco-yolov8-pt-nsmlx.zip: Response timeout. Try increasing the timeout value
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I've tried rebooting the Ubuntu Server 22.04 host, restarting the CPAI service, using both toggle options for download cache, but I can't get out of this error on the Coral module install.
Using the 2.6.5 debian version.
EDIT: This error happens on attempt to install any module.
Any thoughts?
Trace log output:
07:38:03:Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
07:38:03:System: Linux
07:38:03:Operating System: Linux (Ubuntu 22.04)
07:38:03:CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
07:38:03: 1 CPU x 4 cores. 8 logical processors (x64)
07:38:03:GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
07:38:03:System RAM: 31 GiB
07:38:03:Platform: Linux
07:38:03:BuildConfig: Release
07:38:03:Execution Env: Native
07:38:03:Runtime Env: Production
07:38:03:Runtimes installed:
07:38:03: .NET runtime: 7.0.19
07:38:03: .NET SDK: 7.0.119
07:38:03: Default Python: 3.10.12
07:38:03: Go: Not found
07:38:03: NodeJS: Not found
07:38:03: Rust: Not found
07:38:03:App DataDir: /etc/codeproject/ai
07:38:03:Video adapter info:
07:38:03: HD Graphics 530 (rev 06):
07:38:03: Driver Version
07:38:03: Video Processor
07:38:03:STARTING CODEPROJECT.AI SERVER
07:38:03:RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
07:38:03:PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
07:38:03:DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
07:38:03:EXTERNAL_MODULES_PATH =
07:38:03:MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
07:38:03:PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
07:38:03:Data Dir = /etc/codeproject/ai
07:38:04:Server version: 2.6.5
07:38:04:ModuleRunner Start
07:38:04:Starting Background AI Modules
07:38:09:Current Version is 2.6.5
07:38:09:Server: This is the latest version
modified 4 days ago.
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Thanks very much for the report. Could you please share your System Info tab from your CodeProject.AI Server dashboard? Also, could you share the install logs for the module you try (and fail) to install?
Thanks,
Sean Ewington
CodeProject
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You bet, Sean.
System Information:
Server version: 2.6.5
System: Linux
Operating System: Linux (Ubuntu 22.04)
CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
1 CPU x 4 cores. 8 logical processors (x64)
GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
System RAM: 31 GiB
Platform: Linux
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.19
.NET SDK: 7.0.119
Default Python: 3.10.12
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
HD Graphics 530 (rev 06):
Driver Version
Video Processor
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
Even setting logging to verbosity to trace, the 404 error on any module install attempt isn't triggering any log entries. Nonetheless, here's my trace log. I am able to remove modules and watch them disappear from the /modules directory, but installing any back is causing issues. Thanks again!
2024-06-02 07:22:17: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:22:17: ** System: Linux
2024-06-02 07:22:17: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:22:17: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:22:17: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:22:17: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:22:17: ** System RAM: 31 GiB
2024-06-02 07:22:17: ** Platform: Linux
2024-06-02 07:22:17: ** BuildConfig: Release
2024-06-02 07:22:17: ** Execution Env: Native
2024-06-02 07:22:17: ** Runtime Env: Production
2024-06-02 07:22:17: ** Runtimes installed:
2024-06-02 07:22:17: ** .NET runtime: 7.0.19
2024-06-02 07:22:17: ** .NET SDK: 7.0.119
2024-06-02 07:22:17: ** Default Python: 3.10.12
2024-06-02 07:22:17: ** Go: Not found
2024-06-02 07:22:17: ** NodeJS: Not found
2024-06-02 07:22:17: ** Rust: Not found
2024-06-02 07:22:17: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:22:17: Video adapter info:
2024-06-02 07:22:17: HD Graphics 530 (rev 06):
2024-06-02 07:22:17: Driver Version
2024-06-02 07:22:17: Video Processor
2024-06-02 07:22:17: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:22:17: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:22:17: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:22:17: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:22:17: EXTERNAL_MODULES_PATH =
2024-06-02 07:22:17: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:22:17: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:22:17: Data Dir = /etc/codeproject/ai
2024-06-02 07:22:17: ** Server version: 2.6.5
2024-06-02 07:22:17: ModuleRunner Start
2024-06-02 07:22:17: Starting Background AI Modules
2024-06-02 07:22:20: ** Setting up initial modules. Please be patient...
2024-06-02 07:22:20: ** Installing initial module FaceProcessing.
2024-06-02 07:22:20: Preparing to install module 'FaceProcessing'
2024-06-02 07:22:21: Downloading module 'FaceProcessing'
2024-06-02 07:22:21: Installing module 'FaceProcessing'
2024-06-02 07:22:21: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:22:21: FaceProcessing: Setting verbosity to quiet
2024-06-02 07:22:21: FaceProcessing: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m======================================================================[0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m======================================================================[0m
2024-06-02 07:22:21: FaceProcessing: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:22:21: FaceProcessing: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[42mGPU support [0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[104mProcessing module FaceProcessing 1.10.2 [0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mInstalling Python 3.8[0m
2024-06-02 07:22:22: FaceProcessing: [0;92m[49mPython 3.8 is already installed[0m
2024-06-02 07:22:22: Current Version is 2.6.5
2024-06-02 07:22:22: Server: This is the latest version
2024-06-02 07:22:29: FaceProcessing: [0;97m[49mEnsuring PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:22:30: FaceProcessing: [0;97m[49mUpgrading PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:22:30: FaceProcessing: [0;97m[49mInstalling Virtual Environment tools for Linux...[0m
2024-06-02 07:22:31: FaceProcessing: [0;39m[49mSearching for python3-pip python3-setuptools python3.8...[0m[0;92m[49mAll good.[0m
2024-06-02 07:22:33: FaceProcessing: [0;97m[49mCreating Virtual Environment (Shared)...[0m [0;92m[49mdone[0m
2024-06-02 07:22:33: FaceProcessing: [0;97m[49mChecking for Python 3.8...[0m[0;37m[49m(Found Python 3.8.19) [0m[0;92m[49mAll good[0m
2024-06-02 07:22:35: FaceProcessing: [0;97m[49mUpgrading PIP in virtual environment...[0m [0;92m[49mdone[0m
2024-06-02 07:22:37: FaceProcessing: [0;97m[49mInstalling updated setuptools in venv...[0m [0;92m[49mdone[0m
2024-06-02 07:22:59: FaceProcessing: [0;97m[49mDownloading Face models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mMoving contents of models-face-pt.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mInstalling Python packages for Face Processing[0m
2024-06-02 07:22:59: FaceProcessing: [0;35m[49mInstalling GPU-enabled libraries: [0m[0;92m[49mIf available[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:23:01: FaceProcessing: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:23:01: FaceProcessing: [0;35m[49mPython packages will be specified by requirements.linux.txt[0m
2024-06-02 07:23:08: FaceProcessing: [0;97m[49m - Installing Pandas, a data analysis / data manipulation tool...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:18: FaceProcessing: [0;97m[49m - Installing CoreMLTools, for working with .mlmodel format models...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:23: FaceProcessing: [0;97m[49m - Installing OpenCV, the Open source Computer Vision library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:24: FaceProcessing: [0;97m[49m - Installing Pillow, a Python Image Library...[0m [0;91m[49m(❌ failed check) [0m[0;92m[49mdone[0m
2024-06-02 07:23:30: FaceProcessing: [0;97m[49m - Installing SciPy, a library for mathematics, science, and engineering...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:30: FaceProcessing: [0;97m[49m - Installing PyYAML, a library for reading configuration files...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:23:49: FaceProcessing: [0;97m[49m - Installing Torch, for Tensor computation and Deep neural networks...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:10: FaceProcessing: [0;97m[49m - Installing TorchVision, for Computer Vision based AI...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:22: FaceProcessing: [0;97m[49m - Installing Seaborn, a data visualization library based on matplotlib...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:22: FaceProcessing: [0;39m[49mInstalling Python packages for the CodeProject.AI Server SDK[0m
2024-06-02 07:24:22: FaceProcessing: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:24:24: FaceProcessing: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:24:24: FaceProcessing: [0;35m[49mPython packages will be specified by requirements.txt[0m
2024-06-02 07:24:24: FaceProcessing: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:24:27: FaceProcessing: [0;97m[49m - Installing Charset normalizer...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:30: FaceProcessing: [0;97m[49m - Installing aiohttp, the Async IO HTTP library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:32: FaceProcessing: [0;97m[49m - Installing aiofiles, the Async IO Files library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:34: FaceProcessing: [0;97m[49m - Installing py-cpuinfo to allow us to query CPU info...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:37: FaceProcessing: [0;97m[49m - Installing Requests, the HTTP library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:37: FaceProcessing: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:24:42: FaceProcessing: Fusing layers...
2024-06-02 07:24:42: FaceProcessing: YOLOv5m summary: 316 layers, 21468630 parameters, 0 gradients
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mSelf test: [0m[0;92m[49mSelf-test passed[0m
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mModule setup time 00:02:24[0m
2024-06-02 07:24:46: FaceProcessing: [0;97m[42m Setup complete [0m
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mTotal setup time 00:02:25[0m
2024-06-02 07:24:46: Module FaceProcessing installed successfully.
2024-06-02 07:24:46: Installer exited with code 0
2024-06-02 07:24:46: ** Installing initial module ObjectDetectionYOLOv5Net.
2024-06-02 07:24:46: Preparing to install module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:46: Downloading module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:46: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:24:46:
2024-06-02 07:24:46: Attempting to start FaceProcessing with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:24:46: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr.../FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:24:46:
2024-06-02 07:24:46: ** Module 'Face Processing' 1.10.2 (ID: FaceProcessing)
2024-06-02 07:24:46: ** Valid: True
2024-06-02 07:24:46: ** Module Path: <root>/modules/FaceProcessing
2024-06-02 07:24:46: ** Module Location: Internal
2024-06-02 07:24:46: ** AutoStart: True
2024-06-02 07:24:46: ** Queue: faceprocessing_queue
2024-06-02 07:24:46: ** Runtime: python3.8
2024-06-02 07:24:46: ** Runtime Location: Shared
2024-06-02 07:24:46: ** FilePath: intelligencelayer/face.py
2024-06-02 07:24:46: ** Start pause: 3 sec
2024-06-02 07:24:46: ** Parallelism: 0
2024-06-02 07:24:46: ** LogVerbosity:
2024-06-02 07:24:46: ** Platforms: all,!jetson
2024-06-02 07:24:46: ** GPU Libraries: installed if available
2024-06-02 07:24:46: ** GPU: use if supported
2024-06-02 07:24:46: ** Accelerator:
2024-06-02 07:24:46: ** Half Precision: enable
2024-06-02 07:24:46: ** Environment Variables
2024-06-02 07:24:46: ** APPDIR = <root>/modules/FaceProcessing/intelligencelayer
2024-06-02 07:24:46: ** DATA_DIR = /etc/codeproject/ai
2024-06-02 07:24:46: ** MODE = MEDIUM
2024-06-02 07:24:46: ** MODELS_DIR = <root>/modules/FaceProcessing/assets
2024-06-02 07:24:46: ** PROFILE = desktop_gpu
2024-06-02 07:24:46: ** USE_CUDA = True
2024-06-02 07:24:46: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:24:46: ** YOLOv5_VERBOSE = false
2024-06-02 07:24:46:
2024-06-02 07:24:46: Started Face Processing module
2024-06-02 07:24:47: Installing module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:47: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: Setting verbosity to quiet
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m======================================================================[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m======================================================================[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[42mGPU support [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:48: ObjectDetectionYOLOv5Net: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:24:48: ObjectDetectionYOLOv5Net: [0;97m[104mProcessing module ObjectDetectionYOLOv5Net 1.10.1 [0m
2024-06-02 07:24:49: Module FaceProcessing started successfully.
2024-06-02 07:24:51: face.py: Vision AI services setup: Retrieving environment variables...
2024-06-02 07:24:51: face.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer
2024-06-02 07:24:51: face.py: PROFILE: desktop_cpu
2024-06-02 07:24:51: face.py: USE_CUDA: False
2024-06-02 07:24:51: face.py: DATA_DIR: /etc/codeproject/ai
2024-06-02 07:24:51: face.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/assets
2024-06-02 07:24:51: face.py: MODE: MEDIUM
2024-06-02 07:24:51: face.py: Running init for Face Processing
2024-06-02 07:24:59: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading ObjectDetectionYOLOv5Net-CPU-1.10.1.zip...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:24:59: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of ObjectDetectionYOLOv5Net-CPU-1.10.1.zip to bin...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:15: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading YOLO ONNX models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:15: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of yolonet-models.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading Custom YOLO ONNX models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of yolonet-custom-models.zip to custom-models...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mSelf test: [0m[0;91m[49mSelf-test failed[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mModule setup time 00:00:40[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;97m[42m Setup complete [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mTotal setup time 00:00:40[0m
2024-06-02 07:25:27: Module ObjectDetectionYOLOv5Net installed successfully.
2024-06-02 07:25:27: Installer exited with code 0
2024-06-02 07:25:27: ** Installing initial module ObjectDetectionYOLOv5-6.2.
2024-06-02 07:25:27: Preparing to install module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Downloading module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Module ObjectDetectionYOLOv5Net not configured to AutoStart.
2024-06-02 07:25:27: Installing module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: Setting verbosity to quiet
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m======================================================================[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m======================================================================[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[42mGPU support [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[104mProcessing module ObjectDetectionYOLOv5-6.2 1.9.1 [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python 3.8[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;92m[49mPython 3.8 is already installed[0m
2024-06-02 07:25:35: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;97m[49mUpgrading PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;92m[49mVirtual Environment already present[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;97m[49mChecking for Python 3.8...[0m[0;37m[49m(Found Python 3.8.19) [0m[0;92m[49mAll good[0m
2024-06-02 07:25:37: ObjectDetectionYOLOv5-6.2: [0;97m[49mUpgrading PIP in virtual environment...[0m [0;92m[49mdone[0m
2024-06-02 07:25:39: ObjectDetectionYOLOv5-6.2: [0;97m[49mInstalling updated setuptools in venv...[0m [0;92m[49mdone[0m
2024-06-02 07:25:48: ObjectDetectionYOLOv5-6.2: [0;97m[49mDownloading Standard YOLO models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:48: ObjectDetectionYOLOv5-6.2: [0;39m[49mMoving contents of models-yolo5-pt.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;97m[49mDownloading Custom YOLO models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;39m[49mMoving contents of custom-models-yolo5-pt.zip to custom-models...[0m[0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python packages for Object Detection (YOLOv5 6.2)[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;35m[49mInstalling GPU-enabled libraries: [0m[0;92m[49mIf available[0m
2024-06-02 07:26:01: ObjectDetectionYOLOv5-6.2: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;35m[49mPython packages will be specified by requirements.linux.txt[0m
2024-06-02 07:26:03: Client request 'detect' in queue 'objectdetection_queue' (#reqid defdc9a8-ee88-4389-8e04-0ad75cd660da)
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pandas, a data analysis / data manipulation tool...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:04: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing CoreMLTools, for working with .mlmodel format models...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:05: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing OpenCV, the Open source Computer Vision library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:05: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:06: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing SciPy, a library for mathematics, science, and engineering...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:07: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing PyYAML, a library for reading configuration files...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:07: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Torch, for Tensor computation and Deep neural networks...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:08: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing TorchVision, for Computer Vision based AI...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:16: Client request 'detect' in queue 'objectdetection_queue' (#reqid a472c6a3-a230-46bb-b68b-cc12095941d9)
2024-06-02 07:26:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid 46857a83-cd48-4d28-bdc0-ce7b83d6ed52)
2024-06-02 07:26:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid 7af82754-343b-427f-badd-b1685e557ef5)
2024-06-02 07:27:10: Client request 'detect' in queue 'objectdetection_queue' (#reqid ee9b791b-568f-4486-957b-fca4aab392a4)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 41bc3ca4-d62f-4bff-9ad6-a11d9879ff87)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid bd85da5a-0c1a-4ba4-b2cd-cc6b60e5cbea)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 87ffce30-1d26-4581-add1-f8f70ca86130)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 16c8b2a3-df04-4ef1-abcd-78390c5c5b92)
2024-06-02 07:27:12: Client request 'detect' in queue 'objectdetection_queue' (#reqid a82a3c3b-b662-4c07-921f-ca2b079ac5d8)
2024-06-02 07:27:12: Client request 'detect' in queue 'objectdetection_queue' (#reqid 1e793dae-13a1-46e2-999f-2d7d637dbf96)
2024-06-02 07:27:13: Client request 'detect' in queue 'objectdetection_queue' (#reqid e784fe62-2547-4c11-8b3f-b6e87aea4f6b)
2024-06-02 07:27:13: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4c01c768-1cbd-4044-95a7-1775b8dc08b2)
2024-06-02 07:27:14: Client request 'detect' in queue 'objectdetection_queue' (#reqid b9dbd409-27e6-49c6-aebf-1b1dd8da38e7)
2024-06-02 07:27:14: Client request 'detect' in queue 'objectdetection_queue' (#reqid 46acd8a2-40e7-496b-80f7-5a7b0dbb4ad6)
2024-06-02 07:27:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 56dc363c-f0d8-4f35-8c84-0dee69b63034)
2024-06-02 07:27:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3a793ffe-1420-4ff7-951b-54b0f39f2455)
2024-06-02 07:27:21: Client request 'detect' in queue 'objectdetection_queue' (#reqid 62171111-a941-4902-bca6-9bdc3d35fb45)
2024-06-02 07:27:39: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Ultralytics YoloV5 package for object detection in images...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Seaborn, a data visualization library based on matplotlib...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python packages for the CodeProject.AI Server SDK[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:27:42: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:27:42: ObjectDetectionYOLOv5-6.2: [0;35m[49mPython packages will be specified by requirements.txt[0m
2024-06-02 07:27:43: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:44: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Charset normalizer...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e)
2024-06-02 07:27:45: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing aiohttp, the Async IO HTTP library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3e85084a-851c-493c-937a-298430365ced)
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a)
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817)
2024-06-02 07:27:46: Client request 'detect' in queue 'objectdetection_queue' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6)
2024-06-02 07:27:46: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing aiofiles, the Async IO Files library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:46: Client request 'detect' in queue 'objectdetection_queue' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9)
2024-06-02 07:27:47: Client request 'detect' in queue 'objectdetection_queue' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996)
2024-06-02 07:27:47: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing py-cpuinfo to allow us to query CPU info...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:47: Client request 'detect' in queue 'objectdetection_queue' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81)
2024-06-02 07:27:48: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881)
2024-06-02 07:27:48: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Requests, the HTTP library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:48: ObjectDetectionYOLOv5-6.2: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:27:48: Client request 'detect' in queue 'objectdetection_queue' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be)
2024-06-02 07:27:49: Client request 'detect' in queue 'objectdetection_queue' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136)
2024-06-02 07:27:49: Client request 'detect' in queue 'objectdetection_queue' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58)
2024-06-02 07:27:50: Client request 'detect' in queue 'objectdetection_queue' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c)
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: Fusing layers...
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: Adding AutoShape...
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mSelf test: [0m[0;92m[49mSelf-test passed[0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mModule setup time 00:02:26[0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;97m[42m Setup complete [0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mTotal setup time 00:02:27[0m
2024-06-02 07:27:54: Module ObjectDetectionYOLOv5-6.2 installed successfully.
2024-06-02 07:27:54: Installer exited with code 0
2024-06-02 07:27:54: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:27:54:
2024-06-02 07:27:54: Attempting to start ObjectDetectionYOLOv5-6.2 with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:27:54: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr...jectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:27:54:
2024-06-02 07:27:54: ** Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
2024-06-02 07:27:54: ** Valid: True
2024-06-02 07:27:54: ** Module Path: <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:54: ** Module Location: Internal
2024-06-02 07:27:54: ** AutoStart: True
2024-06-02 07:27:54: ** Queue: objectdetection_queue
2024-06-02 07:27:54: ** Runtime: python3.8
2024-06-02 07:27:54: ** Runtime Location: Shared
2024-06-02 07:27:54: ** FilePath: detect_adapter.py
2024-06-02 07:27:54: ** Start pause: 1 sec
2024-06-02 07:27:54: ** Parallelism: 0
2024-06-02 07:27:54: ** LogVerbosity:
2024-06-02 07:27:54: ** Platforms: all,!raspberrypi,!jetson
2024-06-02 07:27:54: ** GPU Libraries: installed if available
2024-06-02 07:27:54: ** GPU: use if supported
2024-06-02 07:27:54: ** Accelerator:
2024-06-02 07:27:54: ** Half Precision: enable
2024-06-02 07:27:54: ** Environment Variables
2024-06-02 07:27:54: ** APPDIR = <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:54: ** CUSTOM_MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/custom-models
2024-06-02 07:27:54: ** MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:27:54: ** MODEL_SIZE = Medium
2024-06-02 07:27:54: ** USE_CUDA = True
2024-06-02 07:27:54: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:27:54: ** YOLOv5_VERBOSE = false
2024-06-02 07:27:54:
2024-06-02 07:27:54: Started Object Detection (YOLOv5 6.2) module
2024-06-02 07:27:55: Module ObjectDetectionYOLOv5-6.2 started successfully.
2024-06-02 07:27:58: detect_adapter.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:58: detect_adapter.py: MODEL_SIZE: medium
2024-06-02 07:27:58: detect_adapter.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:27:58: detect_adapter.py: Running init for Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid defdc9a8-ee88-4389-8e04-0ad75cd660da)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a472c6a3-a230-46bb-b68b-cc12095941d9)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 7af82754-343b-427f-badd-b1685e557ef5)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 46857a83-cd48-4d28-bdc0-ce7b83d6ed52)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid ee9b791b-568f-4486-957b-fca4aab392a4)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 41bc3ca4-d62f-4bff-9ad6-a11d9879ff87)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 16c8b2a3-df04-4ef1-abcd-78390c5c5b92)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 87ffce30-1d26-4581-add1-f8f70ca86130)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 1e793dae-13a1-46e2-999f-2d7d637dbf96)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid e784fe62-2547-4c11-8b3f-b6e87aea4f6b)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 4c01c768-1cbd-4044-95a7-1775b8dc08b2)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid b9dbd409-27e6-49c6-aebf-1b1dd8da38e7)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 46acd8a2-40e7-496b-80f7-5a7b0dbb4ad6)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 56dc363c-f0d8-4f35-8c84-0dee69b63034)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3a793ffe-1420-4ff7-951b-54b0f39f2455)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 62171111-a941-4902-bca6-9bdc3d35fb45)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3e85084a-851c-493c-937a-298430365ced)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid bd85da5a-0c1a-4ba4-b2cd-cc6b60e5cbea)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a82a3c3b-b662-4c07-921f-ca2b079ac5d8)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: detect_adapter.py: Fusing layers...
2024-06-02 07:27:58: detect_adapter.py: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:27:58: detect_adapter.py: Adding AutoShape...
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Model Path is /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets/yolov5m.pt in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e) ['Found car, car'] took 867ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817) ['Found car, car'] took 913ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a) ['Found car, car, car'] took 934ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3e85084a-851c-493c-937a-298430365ced) ['Found car, car'] took 967ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9) ['Found car, car'] took 633ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81) ['Found car'] took 676ms
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996) ['Found car'] took 606ms
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6) ['Found car, car'] took 649ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be) ['Found car'] took 673ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136) ['Found car'] took 664ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881) ['Found car'] took 710ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58) ['Found car'] took 710ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c) ['Found car'] took 290ms
2024-06-02 07:28:11: Update ObjectDetectionYOLOv5-6.2. Setting AutoStart=false
2024-06-02 07:28:11: *** Stopping Object Detection (YOLOv5 6.2)
2024-06-02 07:28:11: Sending shutdown request to pt_main_thread/ObjectDetectionYOLOv5-6.2
2024-06-02 07:28:11: Client request 'Quit' in queue 'objectdetection_queue' (#reqid 889aace6-c64f-41ec-840b-f152ee0a9b71)
2024-06-02 07:28:11: Request 'Quit' dequeued from 'objectdetection_queue' (#reqid 889aace6-c64f-41ec-840b-f152ee0a9b71)
2024-06-02 07:28:11: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'Quit' in Object Detection (YOLOv5 6.2)
2024-06-02 07:28:14: Update FaceProcessing. Setting AutoStart=false
2024-06-02 07:28:14: *** Stopping Face Processing
2024-06-02 07:28:14: Sending shutdown request to pt_main_thread/FaceProcessing
2024-06-02 07:28:14: Client request 'Quit' in queue 'faceprocessing_queue' (#reqid b07211a2-25ba-4da9-85df-18d99d141738)
2024-06-02 07:28:14: Request 'Quit' dequeued from 'faceprocessing_queue' (#reqid b07211a2-25ba-4da9-85df-18d99d141738)
2024-06-02 07:28:14: Face Processing: Retrieved faceprocessing_queue command 'Quit' in Face Processing
2024-06-02 07:28:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653)
2024-06-02 07:28:15: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653)
2024-06-02 07:28:15: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653) ['Found car'] took 323ms
2024-06-02 07:28:16: detect_adapter.py: Object Detection (YOLOv5 6.2) started.
2024-06-02 07:28:16: detect_adapter.py: Inference processing will occur on device 'CPU'
2024-06-02 07:28:16: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:28:17: ** Module ObjectDetectionYOLOv5-6.2 has shutdown
2024-06-02 07:28:18: face.py: Face Processing started.
2024-06-02 07:28:19: ** Module FaceProcessing has shutdown
2024-06-02 07:28:34: Client request 'detect' in queue 'objectdetection_queue' (#reqid bf32f212-9f73-450e-8435-f85614498088)
2024-06-02 07:28:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid c46d7d95-5930-41cb-b7d1-7e035e0db5a6)
2024-06-02 07:28:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid dc9f51d1-d2f4-49b4-ac87-1db40808877d)
2024-06-02 07:28:44: ObjectDetectionYOLOv5-6.2 went quietly
2024-06-02 07:28:47: FaceProcessing went quietly
2024-06-02 07:28:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid 24c3a277-f4f6-4c57-8a95-c88fbcfd7d94)
2024-06-02 07:29:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4639be16-b91c-4c35-b72a-84730209ef39)
2024-06-02 07:29:20: Client request 'detect' in queue 'objectdetection_queue' (#reqid e1c2929a-8fc8-4cdc-9175-4bfddab9cf3c)
2024-06-02 07:29:50: ModuleRunner Stop
2024-06-02 07:29:50: ObjectDetectionYOLOv5-6.2 doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: ObjectDetectionYOLOv5Net doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: FaceProcessing doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: ModuleRunner Stopped
2024-06-02 07:29:51: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:29:51: ** System: Linux
2024-06-02 07:29:51: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:29:51: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:29:51: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:29:51: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:29:51: ** System RAM: 31 GiB
2024-06-02 07:29:51: ** Platform: Linux
2024-06-02 07:29:51: ** BuildConfig: Release
2024-06-02 07:29:51: ** Execution Env: Native
2024-06-02 07:29:51: ** Runtime Env: Production
2024-06-02 07:29:51: ** Runtimes installed:
2024-06-02 07:29:51: ** .NET runtime: 7.0.19
2024-06-02 07:29:51: ** .NET SDK: 7.0.119
2024-06-02 07:29:51: ** Default Python: 3.10.12
2024-06-02 07:29:51: ** Go: Not found
2024-06-02 07:29:51: ** NodeJS: Not found
2024-06-02 07:29:51: ** Rust: Not found
2024-06-02 07:29:51: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:29:51: Video adapter info:
2024-06-02 07:29:51: HD Graphics 530 (rev 06):
2024-06-02 07:29:51: Driver Version
2024-06-02 07:29:51: Video Processor
2024-06-02 07:29:51: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:29:51: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:29:51: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:29:51: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:29:51: EXTERNAL_MODULES_PATH =
2024-06-02 07:29:51: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:29:51: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:29:51: Data Dir = /etc/codeproject/ai
2024-06-02 07:29:51: ** Server version: 2.6.5
2024-06-02 07:29:51: ModuleRunner Start
2024-06-02 07:29:51: Starting Background AI Modules
2024-06-02 07:29:54: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:29:54:
2024-06-02 07:29:54: Attempting to start ObjectDetectionYOLOv5-6.2 with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:29:54: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr...jectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:29:54:
2024-06-02 07:29:54: ** Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
2024-06-02 07:29:54: ** Valid: True
2024-06-02 07:29:54: ** Module Path: <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:54: ** Module Location: Internal
2024-06-02 07:29:54: ** AutoStart: True
2024-06-02 07:29:54: ** Queue: objectdetection_queue
2024-06-02 07:29:54: ** Runtime: python3.8
2024-06-02 07:29:54: ** Runtime Location: Shared
2024-06-02 07:29:54: ** FilePath: detect_adapter.py
2024-06-02 07:29:54: ** Start pause: 1 sec
2024-06-02 07:29:54: ** Parallelism: 0
2024-06-02 07:29:54: ** LogVerbosity:
2024-06-02 07:29:54: ** Platforms: all,!raspberrypi,!jetson
2024-06-02 07:29:54: ** GPU Libraries: installed if available
2024-06-02 07:29:54: ** GPU: use if supported
2024-06-02 07:29:54: ** Accelerator:
2024-06-02 07:29:54: ** Half Precision: enable
2024-06-02 07:29:54: ** Environment Variables
2024-06-02 07:29:54: ** APPDIR = <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:54: ** CUSTOM_MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/custom-models
2024-06-02 07:29:54: ** MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:29:54: ** MODEL_SIZE = Medium
2024-06-02 07:29:54: ** USE_CUDA = True
2024-06-02 07:29:54: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:29:54: ** YOLOv5_VERBOSE = false
2024-06-02 07:29:54:
2024-06-02 07:29:54: Started Object Detection (YOLOv5 6.2) module
2024-06-02 07:29:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1)
2024-06-02 07:29:55: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:29:55:
2024-06-02 07:29:55: Attempting to start FaceProcessing with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:29:55: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr.../FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:29:55:
2024-06-02 07:29:55: ** Module 'Face Processing' 1.10.2 (ID: FaceProcessing)
2024-06-02 07:29:55: ** Valid: True
2024-06-02 07:29:55: ** Module Path: <root>/modules/FaceProcessing
2024-06-02 07:29:55: ** Module Location: Internal
2024-06-02 07:29:55: ** AutoStart: True
2024-06-02 07:29:55: ** Queue: faceprocessing_queue
2024-06-02 07:29:55: ** Runtime: python3.8
2024-06-02 07:29:55: ** Runtime Location: Shared
2024-06-02 07:29:55: ** FilePath: intelligencelayer/face.py
2024-06-02 07:29:55: ** Start pause: 3 sec
2024-06-02 07:29:55: ** Parallelism: 0
2024-06-02 07:29:55: ** LogVerbosity:
2024-06-02 07:29:55: ** Platforms: all,!jetson
2024-06-02 07:29:55: ** GPU Libraries: installed if available
2024-06-02 07:29:55: ** GPU: use if supported
2024-06-02 07:29:55: ** Accelerator:
2024-06-02 07:29:55: ** Half Precision: enable
2024-06-02 07:29:55: ** Environment Variables
2024-06-02 07:29:55: ** APPDIR = <root>/modules/FaceProcessing/intelligencelayer
2024-06-02 07:29:55: ** DATA_DIR = /etc/codeproject/ai
2024-06-02 07:29:55: ** MODE = MEDIUM
2024-06-02 07:29:55: ** MODELS_DIR = <root>/modules/FaceProcessing/assets
2024-06-02 07:29:55: ** PROFILE = desktop_gpu
2024-06-02 07:29:55: ** USE_CUDA = True
2024-06-02 07:29:55: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:29:55: ** YOLOv5_VERBOSE = false
2024-06-02 07:29:55:
2024-06-02 07:29:55: Started Face Processing module
2024-06-02 07:29:56: Current Version is 2.6.5
2024-06-02 07:29:56: Server: This is the latest version
2024-06-02 07:29:58: detect_adapter.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:58: detect_adapter.py: MODEL_SIZE: medium
2024-06-02 07:29:58: detect_adapter.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:29:58: detect_adapter.py: Running init for Object Detection (YOLOv5 6.2)
2024-06-02 07:29:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1)
2024-06-02 07:29:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:29:58: detect_adapter.py: Fusing layers...
2024-06-02 07:29:59: detect_adapter.py: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:29:59: detect_adapter.py: Adding AutoShape...
2024-06-02 07:29:59: Object Detection (YOLOv5 6.2): Model Path is /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets/yolov5m.pt in Object Detection (YOLOv5 6.2)
2024-06-02 07:29:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1) ['Found car'] took 525ms
2024-06-02 07:29:59: face.py: Vision AI services setup: Retrieving environment variables...
2024-06-02 07:29:59: face.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer
2024-06-02 07:29:59: face.py: PROFILE: desktop_cpu
2024-06-02 07:29:59: face.py: USE_CUDA: False
2024-06-02 07:29:59: face.py: DATA_DIR: /etc/codeproject/ai
2024-06-02 07:29:59: face.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/assets
2024-06-02 07:29:59: face.py: MODE: MEDIUM
2024-06-02 07:29:59: face.py: Running init for Face Processing
2024-06-02 07:30:30: Update ObjectDetectionYOLOv5-6.2. Setting AutoStart=false
2024-06-02 07:30:30: *** Stopping Object Detection (YOLOv5 6.2)
2024-06-02 07:30:30: Sending shutdown request to pt_main_thread/ObjectDetectionYOLOv5-6.2
2024-06-02 07:30:30: Client request 'Quit' in queue 'objectdetection_queue' (#reqid 18a3c4ac-f272-4eab-b10b-5b302eab88d7)
2024-06-02 07:30:30: Request 'Quit' dequeued from 'objectdetection_queue' (#reqid 18a3c4ac-f272-4eab-b10b-5b302eab88d7)
2024-06-02 07:30:30: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'Quit' in Object Detection (YOLOv5 6.2)
2024-06-02 07:30:35: Client request 'detect' in queue 'objectdetection_queue' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e)
2024-06-02 07:30:35: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e)
2024-06-02 07:30:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98)
2024-06-02 07:30:36: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98)
2024-06-02 07:30:36: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e) ['Found dining table, bench, potted plant...'] took 270ms
2024-06-02 07:30:36: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98) ['No objects found'] took 271ms
2024-06-02 07:30:46: detect_adapter.py: Object Detection (YOLOv5 6.2) started.
2024-06-02 07:30:46: detect_adapter.py: Inference processing will occur on device 'CPU'
2024-06-02 07:30:46: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:30:46: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:30:47: ** Module ObjectDetectionYOLOv5-6.2 has shutdown
2024-06-02 07:30:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid c0d031fc-a881-40a9-ace4-74d071d64885)
2024-06-02 07:30:55: Update FaceProcessing. Setting AutoStart=false
2024-06-02 07:30:55: *** Stopping Face Processing
2024-06-02 07:30:55: Sending shutdown request to pt_main_thread/FaceProcessing
2024-06-02 07:30:55: Client request 'Quit' in queue 'faceprocessing_queue' (#reqid f3d8081d-8370-4cd0-8cd0-19d90dd9f5fe)
2024-06-02 07:30:55: Request 'Quit' dequeued from 'faceprocessing_queue' (#reqid f3d8081d-8370-4cd0-8cd0-19d90dd9f5fe)
2024-06-02 07:30:55: Face Processing: Retrieved faceprocessing_queue command 'Quit' in Face Processing
2024-06-02 07:31:02: face.py: Face Processing started.
2024-06-02 07:31:03: ** Module FaceProcessing has shutdown
2024-06-02 07:31:03: ObjectDetectionYOLOv5-6.2 went quietly
2024-06-02 07:31:11: ObjectDetectionYOLOv5Net doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:16: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4a315cf3-ea72-48aa-b095-5a9618cfe9c7)
2024-06-02 07:31:18: ObjectDetectionYOLOv5-6.2 doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:19: Client request 'detect' in queue 'objectdetection_queue' (#reqid 15c2fe28-2ed0-4b61-a879-60f429d5a499)
2024-06-02 07:31:28: FaceProcessing went quietly
2024-06-02 07:31:34: FaceProcessing doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid e2257dcd-5bd4-42b2-847e-036be206b948)
2024-06-02 07:31:43: Client request 'detect' in queue 'objectdetection_queue' (#reqid f478e51b-168c-4059-bd42-cd8d5bb51f8b)
2024-06-02 07:31:53: Client request 'detect' in queue 'objectdetection_queue' (#reqid 9870d00f-2ea1-4459-bf57-62c1f7a2e225)
2024-06-02 07:31:58: Client request 'detect' in queue 'objectdetection_queue' (#reqid cc510725-9cd5-44d7-96d6-a28f9aecb9bd)
2024-06-02 07:32:28: ModuleRunner Stop
2024-06-02 07:32:28: ModuleRunner Stopped
2024-06-02 07:32:28: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:32:28: ** System: Linux
2024-06-02 07:32:28: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:32:28: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:32:28: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:32:28: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:32:28: ** System RAM: 31 GiB
2024-06-02 07:32:28: ** Platform: Linux
2024-06-02 07:32:28: ** BuildConfig: Release
2024-06-02 07:32:28: ** Execution Env: Native
2024-06-02 07:32:28: ** Runtime Env: Production
2024-06-02 07:32:28: ** Runtimes installed:
2024-06-02 07:32:28: ** .NET runtime: 7.0.19
2024-06-02 07:32:28: ** .NET SDK: 7.0.119
2024-06-02 07:32:28: ** Default Python: 3.10.12
2024-06-02 07:32:28: ** Go: Not found
2024-06-02 07:32:28: ** NodeJS: Not found
2024-06-02 07:32:28: ** Rust: Not found
2024-06-02 07:32:28: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:32:28: Video adapter info:
2024-06-02 07:32:28: HD Graphics 530 (rev 06):
2024-06-02 07:32:28: Driver Version
2024-06-02 07:32:28: Video Processor
2024-06-02 07:32:28: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:32:28: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:32:28: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:32:28: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:32:28: EXTERNAL_MODULES_PATH =
2024-06-02 07:32:28: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:32:28: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:32:28: Data Dir = /etc/codeproject/ai
2024-06-02 07:32:28: ** Server version: 2.6.5
2024-06-02 07:32:28: ModuleRunner Start
2024-06-02 07:32:28: Starting Background AI Modules
2024-06-02 07:32:34: Current Version is 2.6.5
2024-06-02 07:32:34: Server: This is the latest version
2024-06-02 07:33:32: ModuleRunner Stop
2024-06-02 07:33:32: ModuleRunner Stopped
2024-06-02 07:38:03: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:38:03: ** System: Linux
2024-06-02 07:38:03: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:38:03: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:38:03: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:38:03: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:38:03: ** System RAM: 31 GiB
2024-06-02 07:38:03: ** Platform: Linux
2024-06-02 07:38:03: ** BuildConfig: Release
2024-06-02 07:38:03: ** Execution Env: Native
2024-06-02 07:38:03: ** Runtime Env: Production
2024-06-02 07:38:03: ** Runtimes installed:
2024-06-02 07:38:03: ** .NET runtime: 7.0.19
2024-06-02 07:38:03: ** .NET SDK: 7.0.119
2024-06-02 07:38:03: ** Default Python: 3.10.12
2024-06-02 07:38:03: ** Go: Not found
2024-06-02 07:38:03: ** NodeJS: Not found
2024-06-02 07:38:03: ** Rust: Not found
2024-06-02 07:38:03: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:38:03: Video adapter info:
2024-06-02 07:38:03: HD Graphics 530 (rev 06):
2024-06-02 07:38:03: Driver Version
2024-06-02 07:38:03: Video Processor
2024-06-02 07:38:03: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:38:03: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:38:03: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:38:03: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:38:03: EXTERNAL_MODULES_PATH =
2024-06-02 07:38:03: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:38:03: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:38:03: Data Dir = /etc/codeproject/ai
2024-06-02 07:38:04: ** Server version: 2.6.5
2024-06-02 07:38:04: ModuleRunner Start
2024-06-02 07:38:04: Starting Background AI Modules
2024-06-02 07:38:09: Current Version is 2.6.5
2024-06-02 07:38:09: Server: This is the latest version
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This was due to the docker container I had been testing but quit due to error 500's. I rebooted the host and it started up the CPAI docker container w/ host networking like it was supposed to. Deleting the container immediately resolved the 404 issues. I had 32168 on one instance and 32169 on another - only reason I think everything was acting "ok".
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Q1. Can this be run on Windows 7 SP1? If unable that's too bad. (many others like "LocalAI" never answer this question)
Q2. What is the minimum reqirement to use this for text generation/chat? How much memory do I need and/or GPU?
Q3. Can I use this without internet (offline); does this really work without it? I'm planning to download the installer and install offline.
Q4. Does your AI can process non-English language? Can I teach it based on my text data?
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1. Probably not. [.NET 7 is not supported in Windows 7](https://github.com/dotnet/core/issues/7556). Having said that, recompiling everything in .NET 6 should work, but you'd have to ensure WMIC and Powershell were installed too.
Windows 7 is simply too old for us to be supporting, but technically the code *should* be fine.
2. What is the minimum requirement to use this for text generation/chat? How much memory do I need and/or GPU?
It all works on CPUs, it's just slow. The more RAM the better. I run 16Gb systems on all my machines (except RPi/Jetson) and generative AI works fine on these. Even 8Gb should be good, but I would no go lower.
3. Installation needs to happen online so it can download the libraries needed for your particular Hardware / OS combo. Once it's installed it's fully offline.
4. Does your AI can process non-English language? Can I teach it based on my text data?
Whatever GGUF format LLama model you can find will work. Training yourself is a task beyond what we can help you with
cheers
Chris Maunder
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My primary host is running UnRaid 6.12.9 with a CPAI docker container and a Windows VM running BlueIris. I have another Linux Mint machine on the network running CPAI with no docker container. Both instances of CPAI can see each other, sort of.
If I set Blue Iris to target the remote Linux machine, everything works fine, excess requests get passed back to the Unraid machine, processed, sent back. Everything is happy.
But if I set Blue Iris to target the docker running on the same machine as itself, it still sees the other Mint machine and tries to send overflow to it, but times out with no response.
The status of the Unraid server from the Mint remote wavers from active true to active false every few seconds.
I just upgraded to CPAI 2.6.5 but had the same behaviour under 2.6.2. UDP ports are open to the docker container.
I want to keep the docker on the Unraid as the primary instance because the remote mint machine is used frequently and is prone to going down for various reasons, and blue iris is unable to automatically switch servers.
From the Unraid Server:
Current Server mesh status
UnraidServer
Hostname: 172.17.0.8
System: Docker (Linux) Tesla P4
Platform: Docker
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
mintMachine
Routes Available: (16366 processed)
vision/custom 43.7ms (avg process time), 15756 processed
vision/custom/list 0ms (avg process time), 0 processed
vision/detection 0ms (avg process time), 0 processed
vision/face 20ms (avg process time), 610 processed
vision/face/match 0ms (avg process time), 0 processed
Remote Servers in mesh: 1
mintMachine
Hostname: mintMachine
System: Linux (Linux) NVIDIA GeForce GTX 1660 Ti with Max-Q Design
Platform: Linux
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
UnraidServer
Routes Available: (3 processed)
vision/custom 3000ms (avg round trip), 2 requests forwarded
vision/custom/list 0ms (avg round trip), 0 requests forwarded
vision/detection 0ms (avg round trip), 0 requests forwarded
vision/face 0ms (avg round trip), 1 requests forwarded
vision/face/match 0ms (avg round trip), 0 requests forwarded
From the Linux Mint remote machine:
Current Server mesh status
mintMachine
Hostname: mintMachine
System: Linux (Linux) NVIDIA GeForce GTX 1660 Ti with Max-Q Design
Platform: Linux
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
UnraidServer
Routes Available: (0 processed)
vision/custom 0ms (avg process time), 0 processed
vision/custom/list 0ms (avg process time), 0 processed
vision/detection 0ms (avg process time), 0 processed
vision/face 0ms (avg process time), 0 processed
vision/face/match 0ms (avg process time), 0 processed
Remote Servers in mesh: 1
UnraidServer
Hostname: 192.168.1.101
System: Docker (Linux) Tesla P4
Platform: Docker
Active: false
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
mintMachine
Routes Available: (0 processed)
vision/custom 0ms (avg round trip), 0 requests forwarded
vision/custom/list 0ms (avg round trip), 0 requests forwarded
vision/detection 0ms (avg round trip), 0 requests forwarded
vision/face 0ms (avg round trip), 0 requests forwarded
vision/face/match 0ms (avg round trip), 0 requests forwarded
modified 31-May-24 14:55pm.
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I think I might have got this licked.
I added the IP address of the Mint remote machine to the known mesh servers in appdata/codeprojectai/data/serversettings.json on the Unraid server
"KnownMeshHostnames": [ "192.168.1.103" ],
I already had it in the appsettings.json on the Mint machine pointing it at the Unraid server, so not sure if you need both pointing at each other, but it seems to be working.
Hopefully this helps out someone having the same issues as me!
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Actually I'm still having some issues.
I haven't been able narrow down exactly when it happens, but it seems like after either end reboots the mesh is broken and it starts trying to look for the hostname instead of the IP address, which for whatever reason doesn't make it through the docker network interface, so you have to disable the mesh on the satellite, reboot the docker, then restart the mesh on the satellite again. Nothing relevant really comes up in the logs to give any insight on why this is happening.
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