|
Are you using Blue Iris?
Also: can you please click the "info" button on the right side of the line for ObjectDetectionYOLO in the dashboard. It will pop up a panel showing the settings. Please post that here. As well, if you can click on the System Info tab on the dashboard and post the settings your server is seeing that will help too.
Follow up: you mentioned you had uninstalled / reinstalled the modules.
You have your /app/modules docker folder mapped to /path/to/etc/ai, so can you please go to /path/to/etc/ai/ObjectDetectionYolo and let me know if the custom-models folder is there and if it contains models?
Another question: Are you familiar enough with docker to look into the file system? It would be really handy if you could take a peek at the /logs directory and open the log for the day the error happened (I assume today) and look for the word 'exception'. I've just found one uncaught exception that shouldn't be causing too many issues, but there may be something we're missing, and your logs may hold the key.
cheers
Chris Maunder
modified 21-Apr-23 12:44pm.
|
|
|
|
|
Yes I am using Blue Iris. 5.7.5.0 and going to update to 5.7.5.1 in a few moments since I saw it was just released.
In response to your follow up questions, I saw that we have the ability in this version to uninstall and install the default modules so I tried that as an additional troubleshooting step.
I do not have a custom-models folder in the ObjectDetectionYolo folder. I will include a list of the files/dir I do have in there though.
So I see an /app/logs directory, but nothing is showing an exception. I am not seeing a logs folder in the root though. If you can point me somewhere else I am happy to look.
|
|
|
|
|
Hi is there any way to install CodeProject.AI Server on Linux without Docker for production? Of course I have seen the solution for development, but I want to use it for production?
Current situation:
Proxmox Server with an Ubuntu LXC container and an agent dvr installation
I have ordered an Nvidia P4 as vGPU for the Proxmox Server. Maybe I have to change my setup to an Ubuntu vm and an agent dvr installation, but I will see when Nvidia GPU will arrive and starting with testing.
Why my question, I want to avoid to path through the full GPU to this vm and then path through to the CodeProject.AI Server container. At the moment I have no live experience with Nvidia vGPU, but all internet sources showing very complicated setup. And then additional path through will be crazy for me.
modified 20-Apr-23 22:01pm.
|
|
|
|
|
We're focussed on minimising our support requirements though because there are so many moving parts to this, but
if you know anyone who has experience in creating a package that can be installed via apt-get then I'd love to see a native Linux installation.
cheers
Chris Maunder
|
|
|
|
|
This one addresses a bucket load of issues we discovered, some of them pretty bizarre.
For those asking: Coral is not yet supported on Windows. We're close (maybe!) but not close enough to call it yet. However, for those running Docker on a Raspberry Pi? It's awesome.
cheers
Chris Maunder
|
|
|
|
|
Chris,
I am about 99% done with an Orange Pi 5 module. I will email the code in the next day or two.
|
|
|
|
|
Morning Chris,
First of all, excellent work. I am eager to dig into coral with this. I have 2.1.3 running on a pi4 but the only model avaialable when the TPU is selected is MobileNet SSD. Is there any docs or settings in Blue Iris that I would need to adjust to begin testing? Again thank you for all your hard work!
Kevin
|
|
|
|
|
Kevin,
It should work just like YOLOv5, just use default object detection setting in Blue Iris
Chris
Please confirm if I am correct.
|
|
|
|
|
Using the default model is correct. BI has been running on it for about 3 hours with great success... I am getting 35-70ms times. Intersting note, I am running on "small" for the model size. On small or tiny I get around the stated ms times. If I move up to "Medium" model size, the time jusmps up to 500ms+. I only tried, as on anything lower than medium, I found that blue iris' detect static objects didnt work well.
Thanks!
|
|
|
|
|
Windows 11
Intel 5820k
EVGA 2060 12GB
USING CP:AI Object Detection on Yolo 6.2
Still getting Error:500's and Multiple runtime Exceptions. Install seemed to go fine, Thank you for the install status indicators it helps to troubleshoot if the issue is with the install or something else.
Link to post in insiders forum: CodeProject.AI Server Insiders Discussion Boards[^]
|
|
|
|
|
Getting heaps of errors after the upgrade had to rollback to 2.0.8. I noticed this build installed really fast compared to 2.0.8 for example I never saw this build install pip, where as when I rolled back the PIP install took place again.
Blue iris throws a 404 error AI timeout too
11:22:07:
11:22:07:Started Face Processing module
11:22:07:face.py: Traceback (most recent call last):
11:22:07:face.py: File "C:\Program Files\CodeProject\AI\modules\FaceProcessing\intelligencelayer\face.py", line 21, in
11:22:07:face.py: from request_data import RequestData
11:22:07:face.py: File "../../SDK/Python\request_data.py", line 8, in
11:22:07:face.py: from PIL import Image
11:22:07:face.py: ModuleNotFoundError: No module named 'PIL'
11:22:07:Module FaceProcessing has shutdown
11:22:07:face.py: has exited
11:22:10:Server: This is the latest version
11:22:04:Server version: 2.1.3-Beta
11:22:06:Connection id "0HMQ21C195DRQ", Request id "0HMQ21C195DRQ:00000001": An unhandled exception was thrown by the application.
11:22:07:
11:22:07:Module 'Face Processing' (ID: FaceProcessing)
11:22:07:AutoStart: True
11:22:07:Queue: faceprocessing_queue
11:22:07:Platforms: windows,linux,linux-arm64,macos,macos-arm64
11:22:07:GPU: Support enabled
11:22:07:Parallelism: 0
11:22:07:Accelerator:
11:22:07:Half Precis.: enable
11:22:07:Runtime: python37
11:22:07:Runtime Loc: Shared
11:22:07:FilePath: intelligencelayer\face.py
11:22:07:Pre installed: False
11:22:07:Start pause: 1 sec
11:22:07:LogVerbosity:
11:22:07:Valid: True
11:22:07:Environment Variables
11:22:07:APPDIR = %CURRENT_MODULE_PATH%\intelligencelayer
11:22:07:CPAI_MODULE_SUPPORT_GPU = True
11:22:07:DATA_DIR = %DATA_DIR%
11:22:07:MODE = MEDIUM
11:22:07:MODELS_DIR = %CURRENT_MODULE_PATH%\assets
11:22:07:PROFILE = desktop_gpu
11:22:07:USE_CUDA = True
11:22:07:YOLOv5_AUTOINSTALL = false
11:22:07:YOLOv5_VERBOSE = false
11:22:07:
11:22:07:Started Face Processing module
11:22:07:face.py: Traceback (most recent call last):
11:22:07:face.py: File "C:\Program Files\CodeProject\AI\modules\FaceProcessing\intelligencelayer\face.py", line 21, in
11:22:07:face.py: from request_data import RequestData
11:22:07:face.py: File "../../SDK/Python\request_data.py", line 8, in
11:22:07:face.py: from PIL import Image
11:22:07:face.py: ModuleNotFoundError: No module named 'PIL'
11:22:07:Module FaceProcessing has shutdown
11:22:07:face.py: has exited
11:22:10:Server: This is the latest version
Server version: 2.1.3-Beta
Operating System: Windows (Microsoft Windows 10.0.19044)
CPUs: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
1 CPU x 6 cores. 12 logical processors (x64)
GPU: NVIDIA T600 (4 GiB) (NVidia)
Driver: 528.49 CUDA: 12.0 Compute: 7.5
System RAM: 16 GiB
Target: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
.NET framework: .NET 7.0.3
System GPU info:
GPU 3D Usage 4%
GPU RAM Usage 472 MiB
Video adapter info:
NVIDIA T600:
Driver Version 31.0.15.2849
Video Processor NVIDIA T600
Global Environment variables:
CPAI_APPROOTPATH = C:\Program Files\CodeProject\AI
CPAI_PORT = 32168
modified 21-Apr-23 3:06am.
|
|
|
|
|
Sounds great.
Is coral support for non rpi docker planned?
|
|
|
|
|
Excellent news!
|
|
|
|
|
Thanks for your hard work.
So we can go to CUDA 12.1 ?
Can you show us what is absolutely necessary to install in CUDA because there is a lot of things.
Thank you again !
|
|
|
|
|
If you're on CUDA 12.1 it should all just work (it does on my machine!)
cheers
Chris Maunder
|
|
|
|
|
2.1.3 is broken.
Downloaded, prompted to uninstall previous veriosn. Did that. Installed 2.1.3, it started and now all I get it:
07:40:13:
07:40:13:Started Object Detection (YOLOv5 6.2) module
07:40:14:Server: This is the latest version
07:40:14:detect_adapter.py: Traceback (most recent call last):
07:40:14:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect_adapter.py", line 20, in
07:40:14:detect_adapter.py: from detect import init_detect, do_detection
07:40:14:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 9, in
07:40:14:detect_adapter.py: from yolov5.models.common import DetectMultiBackend, AutoShape
07:40:14:detect_adapter.py: ModuleNotFoundError: No module named 'yolov5'
07:40:15:Module ObjectDetectionYolo has shutdown
07:40:15:detect_adapter.py: has exited
07:40:16:face.py: GPU in use: NVIDIA GeForce GTX 1650 SUPER
07:40:27:Connection id "0HMQ2EP77S13C", Request id "0HMQ2EP77S13C:00000001": An unhandled exception was thrown by the application.
It's running face detection in GPU mode but YOLO in CPU, which was previously GPU. But then just crashes...
🤷
|
|
|
|
|
Well have it running now, looks like it tries to download something from China during install and that was being blocked by my filtering.
Anyhow, it's installed and running now but it's not detecting anything in BlueIris...
|
|
|
|
|
Logs, looks like there's some errors during startup.
Install Modules
08:48:44:Connection id "0HMQ2FTR3VJBG", Request id "0HMQ2FTR3VJBG:00000001": An unhandled exception was thrown by the application.
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (15) must match the size of tensor b (12) at non-singleton dimension 2
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 (24) must match the size of tensor b (30) at non-singleton dimension 2
08:49:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a80390) took 333ms
|
|
|
|
|
Looking more, the errors repeat, not just at startup...
|
|
|
|
|
What GPU are you using?
cheers
Chris Maunder
|
|
|
|
|
Yes, ALPR and OCR both use paddlepaddle, an AI package developed by Baidu (Chinese version of Google). The Python packages for paddlepaddle are hosted in China.
cheers
Chris Maunder
|
|
|
|
|
Can you please uninstall / reinstall the ObjectDetectionYolo module via the dashboard ('modules' tab)? The "No module named 'yolov5'" means the yolo python package didn't get installed properly.
cheers
Chris Maunder
|
|
|
|
|
Hello, I'm using a 1650 Super.
I stopped BlueIris and went ahead and completely uninstalled AI (add/remove programs) and deleted the directories under Program Files and ProgramData.
After instilling I let the server run and it installed and ran:
Face Processing
Object Detection (YOLOv5 .NET)
Object Detection (YOLOv5 6.2)
All these were running using CUDA.
After it was done installing I started BlueIris and waited for it to settle and now The following are running (using CUDA):
Object Detection (YOLOv5 6.2)
YOLOv5 .NET is stopped as well as Face Processing but I have Face Processing disabled in BI atm.
It's hard for me to test completely atm as I'm away from home (can't walk in front of the camera and we don't live on a super active street) but BI is showing AI is active. Earlier when I was able to test it was sowing active as well, just not "finding" anything.
I saw an error just after installing but I don't think there has been once since...
11:40:44:YOLOv5_AUTOINSTALL = false
11:40:44:YOLOv5_VERBOSE = false
11:40:44:
11:40:44:Started Object Detection (YOLOv5 6.2) module
11:40:44:Installer exited with code 0
11:40:45:Module ObjectDetectionYolo started successfully.
11:43:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'list-custom' (...db7036) took 2ms
11:43:11:Sending shutdown request to python/FaceProcessing
11:43:19:Module FaceProcessing has shutdown
11:43:19:face.py: has exited
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5dab75) took 1181ms
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0af8e8) took 4686ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...be144e) took 4756ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...646b54) took 1212ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...84d7ea) took 4732ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5b4f3c) took 4735ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, 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 1102, 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 28, 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 1102, 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 1102, 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 1102, 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 (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...afb61c) took 274ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f0d2ea) took 308ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bf5017) took 318ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...617d4e) took 294ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1b2eca) took 527ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ffcb7d) took 252ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8f78fc) took 531ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d5dc0d) took 267ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e20448) took 252ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d95413) took 34ms
11:43:44:FaceProcessing went quietly
11:43:44:Sending shutdown request to python/ObjectDetectionYolo
11:43:49:detect_adapter.py: GPU compute capability is 7.5
11:43:49:detect_adapter.py: Using half-precision for the device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: GPU compute capability is 7.5
11:43:49:detect_adapter.py: Using half-precision for the device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:50:Module ObjectDetectionYolo has shutdown
11:43:50:detect_adapter.py: has exited
11:44:17:ObjectDetectionYolo went quietly
11:44:17:
11:44:17:Module 'Object Detection (YOLOv5 6.2)' (ID: ObjectDetectionYolo)
11:44:17:AutoStart: True
11:44:17:Queue: objectdetection_queue
11:44:17:Platforms: all
11:44:17:GPU: Support enabled
11:44:17:Parallelism: 0
11:44:17:Accelerator:
11:44:17:Half Precis.: enable
11:44:17:Runtime: python37
11:44:17:Runtime Loc: Shared
11:44:17:FilePath: detect_adapter.py
11:44:17:Pre installed: False
11:44:17:Start pause: 1 sec
11:44:17:LogVerbosity:
11:44:17:Valid: True
11:44:17:Environment Variables
11:44:17:APPDIR = %CURRENT_MODULE_PATH%
11:44:17:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
11:44:17:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
11:44:17:MODEL_SIZE = Medium
11:44:17:USE_CUDA = True
11:44:17:YOLOv5_AUTOINSTALL = false
11:44:17:YOLOv5_VERBOSE = false
11:44:17:CPAI_MODULE_SUPPORT_GPU = True
11:44:17:
11:44:17:Started Object Detection (YOLOv5 6.2) module
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d1944d) took 3725ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...064d88) took 3735ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6b57d8) took 3755ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5ef1e7) took 3767ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b25837) took 3764ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fd8afa) took 3795ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ba2a54) took 536ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...25dd10) took 559ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6d6888) took 555ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...2735fd) took 583ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4b88b4) took 577ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4f12ba) took 601ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f28a2e) took 457ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...239311) took 490ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...772a83) took 491ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...30f837) took 508ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d46fb0) took 611ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e7fd2b) took 686ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...21db1d) took 348ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c8293a) took 380ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4e213d) took 384ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9b79a2) took 348ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6bb00e) took 515ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fb5101) took 406ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...127954) took 723ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b3ff0b) took 573ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7638bd) took 441ms
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...685bc9) took 138ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6ca581) took 134ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0afa87) took 138ms
11:45:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...724c81) took 352ms
11:45:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4c8558) took 505ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e985cc) took 562ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...99cbcf) took 580ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...702bad) took 588ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d00071) took 578ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d566a0) took 598ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d76476) took 405ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...886224) took 447ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f3d2ff) took 481ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...57a183) took 483ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3242fd) took 536ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...84d708) took 567ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7112e9) took 300ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...106b38) took 289ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...080cfc) took 281ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5bfc7a) took 289ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...97939a) took 286ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...20b7ef) took 256ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...29c334) took 191ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...917a96) took 184ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...3c236b) took 143ms
11:45:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e63329) took 400ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cd675e) took 232ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...43af6b) took 249ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ba1941) took 428ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ffc8c3) took 270ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...853c2f) took 250ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fcda3e) took 268ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d58a3c) took 234ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fa54f3) took 100ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e3f8ee) took 97ms
11:45:48:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...634750) took 348ms
11:45:48:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:48:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2af8ea) took 36ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...454fe7) took 257ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c56c4b) took 144ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e9a8bb) took 142ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e3c096) took 54ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7ad4f4) took 111ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e00f0f) took 65ms
11:46:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7aaff3) took 98ms
11:46:04:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b9406d) took 50ms
11:46:09:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e2d328) took 343ms
11:46:09:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:09:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...291f8d) took 68ms
11:46:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fed145) took 356ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ec1cdb) took 731ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5a427a) took 454ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...cfc7d8) took 466ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3c34b9) took 499ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5f4453) took 559ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3a1da2) took 642ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d4b51f) took 331ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...891469) took 350ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f0888e) took 412ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...8f11d3) took 432ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cfb66c) took 417ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...77ac46) took 386ms
11:46:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...052dc6) took 251ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...024dfa) took 237ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bac8f3) took 231ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...98d4c3) took 216ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a85c01) took 155ms
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4d9b2f) took 345ms
11:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...31019a) took 54ms
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...580272) took 99ms
11:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...531e50) took 52ms
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d3a1a4) took 98ms
11:47:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bcd124) took 50ms
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3c17fc) took 96ms
11:47:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...96f86e) took 53ms
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...22e956) took 302ms
11:47:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7f12f7) took 411ms
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...10aed6) took 424ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...2c6f4a) took 450ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...57b386) took 479ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3e4c7d) took 588ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4dae33) took 542ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ba9a57) took 403ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3a847f) took 409ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bfaeff) took 391ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9e04a0) took 371ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...07f6c7) took 452ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...73cfdb) took 316ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ddb4e3) took 343ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8e9b6e) took 331ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e4d89c) took 317ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0e2502) took 310ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1fd6ff) took 142ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8a97f2) took 136ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...27c58e) took 128ms
11:47:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a73161) took 308ms
11:47:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...dcacd7) took 72ms
11:47:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fafc8b) took 143ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b2a41f) took 164ms
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1cca67) took 83ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a0c1fa) took 79ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...dd8c29) took 94ms
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...eb6eda) took 50ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fc74e3) took 152ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...841564) took 162ms
11:47:36:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:36:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2b3719) took 80ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...08816e) took 73ms
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0e56ad) took 408ms
11:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ebbc86) took 143ms
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5d1a72) took 146ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9d3296) took 60ms
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bbc82b) took 110ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e48eab) took 148ms
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...85281a) took 112ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8524ea) took 54ms
11:48:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e1a8d0) took 370ms
11:48:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1596b7) took 66ms
11:48:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e75682) took 296ms
11:48:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...453bd4) took 721ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d0c286) took 531ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6ed06c) took 543ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...336fb6) took 558ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...61e6d8) took 656ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c92283) took 715ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4739df) took 447ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...184d1e) took 462ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7863ff) took 472ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...9d526c) took 505ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ef0cc1) took 463ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f330cd) took 347ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0a82f0) took 273ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d6ff0e) took 319ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6542b3) took 268ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e7e753) took 264ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2e5e9b) took 277ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...652fac) took 233ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...43f0ce) took 197ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...00cf84) took 184ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a5ebf6) took 181ms
Server version: 2.1.3-Beta
Operating System: Windows (Microsoft Windows 10.0.19044)
CPUs: Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
1 CPU x 6 cores. 12 logical processors (x64)
GPU: NVIDIA GeForce GTX 1650 SUPER (4 GiB) (NVidia)
Driver: 531.68 CUDA: 12.1 Compute: 7.5
System RAM: 32 GiB
Target: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
.NET framework: .NET 7.0.3
System GPU info:
GPU 3D Usage 5%
GPU RAM Usage 487 MiB
Video adapter info:
NVIDIA GeForce GTX 1650 SUPER:
Driver Version 31.0.15.3168
Video Processor NVIDIA GeForce GTX 1650 SUPER
Microsoft Remote Display Adapter:
Driver Version 10.0.19041.2075
Video Processor
Intel(R) UHD Graphics 630:
Driver Version 30.0.101.1692
Video Processor Intel(R) UHD Graphics Family
Global Environment variables:
CPAI_APPROOTPATH = C:\Program Files\CodeProject\AI
CPAI_PORT = 32168
|
|
|
|
|
I saw that you put up 2.1.4 and tried to install that (closed BI first). I go this error:
Full log:
[355C:2DAC][2023-04-21T13:22:12]i001: Burn v3.11.2.4516, Windows v10.0 (Build 19044: Service Pack 0), path: C:\Users\Adam\AppData\Local\Temp\{8E8220FA-6D90-41C9-A3C6-95228629DB62}\.cr\CodeProject.AI.Server-2.1.4.exe
[355C:2DAC][2023-04-21T13:22:12]i009: Command Line: '-burn.clean.room=C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.Server-2.1.4.exe -burn.filehandle.attached=568 -burn.filehandle.self=684'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleOriginalSource' to value 'C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.Server-2.1.4.exe'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleOriginalSourceFolder' to value 'C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleLog' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212.log'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleName' to value 'CodeProject.AI Server'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleManufacturer' to value 'CodeProject'
[355C:1874][2023-04-21T13:22:12]i000: Setting numeric variable 'WixStdBALanguageId' to value 1033
[355C:1874][2023-04-21T13:22:12]i000: Setting version variable 'WixBundleFileVersion' to value '2.1.4.0'
[355C:2DAC][2023-04-21T13:22:12]i100: Detect begin, 2 packages
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.0 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting700Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.1 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting701Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.2 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting702Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting703Installed' to value 1
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.4 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting704Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.5 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting705Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i102: Detected related bundle: {fdcf2cac-9761-450b-8636-5b1b91a09b3c}, type: Upgrade, scope: PerMachine, version: 2.1.3.0, operation: MajorUpgrade
[355C:2DAC][2023-04-21T13:22:12]i103: Detected related package: {3083037B-8E2C-4F9C-81A0-8FE695504DA1}, scope: PerMachine, version: 2.1.3.0, language: 0 operation: MajorUpgrade
[355C:2DAC][2023-04-21T13:22:12]i103: Detected related package: {3083037B-8E2C-4F9C-81A0-8FE695504DA1}, scope: PerMachine, version: 2.1.3.0, language: 0 operation: None
[355C:2DAC][2023-04-21T13:22:12]i101: Detected package: dotnet_hosting_7.0.3_win.exe, state: Absent, cached: Complete
[355C:2DAC][2023-04-21T13:22:12]i101: Detected package: CODEPROJECTAISERVER, state: Absent, cached: None
[355C:2DAC][2023-04-21T13:22:12]i199: Detect complete, result: 0x0
[355C:1874][2023-04-21T13:22:15]i000: Setting numeric variable 'EulaAcceptCheckbox' to value 1
[355C:2DAC][2023-04-21T13:22:15]i200: Plan begin, 2 packages, action: Install
[355C:2DAC][2023-04-21T13:22:15]w321: Skipping dependency registration on package with no dependency providers: dotnet_hosting_7.0.3_win.exe
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleLog_dotnet_hosting_7.0.3_win.exe' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_000_dotnet_hosting_7.0.3_win.exe.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleRollbackLog_dotnet_hosting_7.0.3_win.exe' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_000_dotnet_hosting_7.0.3_win.exe_rollback.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleRollbackLog_CODEPROJECTAISERVER' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_001_CODEPROJECTAISERVER_rollback.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleLog_CODEPROJECTAISERVER' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_001_CODEPROJECTAISERVER.log'
[355C:2DAC][2023-04-21T13:22:15]i201: Planned package: dotnet_hosting_7.0.3_win.exe, state: Absent, default requested: Present, ba requested: Present, execute: Install, rollback: Uninstall, cache: No, uncache: No, dependency: None
[355C:2DAC][2023-04-21T13:22:15]i201: Planned package: CODEPROJECTAISERVER, state: Absent, default requested: Present, ba requested: Present, execute: Install, rollback: Uninstall, cache: Yes, uncache: No, dependency: Register
[355C:2DAC][2023-04-21T13:22:15]i207: Planned related bundle: {fdcf2cac-9761-450b-8636-5b1b91a09b3c}, type: Upgrade, default requested: Absent, ba requested: Absent, execute: Uninstall, rollback: Install, dependency: None
[355C:2DAC][2023-04-21T13:22:15]i299: Plan complete, result: 0x0
[355C:2DAC][2023-04-21T13:22:15]i300: Apply begin
[355C:2DAC][2023-04-21T13:22:15]i010: Launching elevated engine process.
[355C:2DAC][2023-04-21T13:22:16]i011: Launched elevated engine process.
[355C:2DAC][2023-04-21T13:22:16]i012: Connected to elevated engine.
[2748:2894][2023-04-21T13:22:16]i358: Pausing automatic updates.
[2748:2894][2023-04-21T13:22:16]i359: Paused automatic updates.
[2748:2894][2023-04-21T13:22:16]i360: Creating a system restore point.
[2748:2894][2023-04-21T13:22:22]i361: Created a system restore point.
[2748:2894][2023-04-21T13:22:22]i370: Session begin, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, options: 0x7, disable resume: No
[2748:2894][2023-04-21T13:22:22]i000: Caching bundle from: 'C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\.be\CodeProject.AI.Server-2.1.4.exe' to: 'C:\ProgramData\Package Cache\{5096f3b1-3ad0-4196-ba43-e567978fb15d}\CodeProject.AI.Server-2.1.4.exe'
[2748:2894][2023-04-21T13:22:22]i320: Registering bundle dependency provider: {5096f3b1-3ad0-4196-ba43-e567978fb15d}, version: 2.1.4.0
[2748:2894][2023-04-21T13:22:22]i371: Updating session, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: Active, restart initiated: No, disable resume: No
[2748:235C][2023-04-21T13:22:23]i304: Verified existing payload: dotnet_hosting_7.0.3_win.exe at path: C:\ProgramData\Package Cache\799a2e153ab905add5a1c3ec06373e51753e8ed2\dotnet-hosting-7.0.3-win.exe.
[355C:26FC][2023-04-21T13:22:23]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:23]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 11BF669C0CFD7DFA18C90760686C7AEE62E69DD0
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:22:37]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:22:37]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[355C:26FC][2023-04-21T13:22:37]e349: Application requested retry of payload: CODEPROJECTAISERVER, encountered error: 0x80091007. Retrying...
[355C:26FC][2023-04-21T13:22:37]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:40]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 58098953CF49E6F4E47DC7772E40273001736F8D
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:22:53]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:22:53]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[355C:26FC][2023-04-21T13:22:53]e349: Application requested retry of payload: CODEPROJECTAISERVER, encountered error: 0x80091007. Retrying...
[355C:26FC][2023-04-21T13:22:53]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:56]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 58098953CF49E6F4E47DC7772E40273001736F8D
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:23:06]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:23:06]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[2748:235C][2023-04-21T13:23:06]i351: Removing cached package: dotnet_hosting_7.0.3_win.exe, from path: C:\ProgramData\Package Cache\799a2e153ab905add5a1c3ec06373e51753e8ed2\
[355C:2DAC][2023-04-21T13:23:06]e000: Error 0x80091007: Failed while caching, aborting execution.
[2748:2894][2023-04-21T13:23:06]i372: Session end, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: None, restart: None, disable resume: No
[2748:2894][2023-04-21T13:23:06]i330: Removed bundle dependency provider: {5096f3b1-3ad0-4196-ba43-e567978fb15d}
[2748:2894][2023-04-21T13:23:06]i352: Removing cached bundle: {5096f3b1-3ad0-4196-ba43-e567978fb15d}, from path: C:\ProgramData\Package Cache\{5096f3b1-3ad0-4196-ba43-e567978fb15d}\
[2748:2894][2023-04-21T13:23:06]i371: Updating session, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: None, restart initiated: No, disable resume: No
[355C:2DAC][2023-04-21T13:23:06]i399: Apply complete, result: 0x80091007, restart: None, ba requested restart: No
|
|
|
|
|
Ok, a reboot and redownload of 2.1.4 and it installed. Currently showing that YOLOv5 6.2 is running, others stopped (I still have face processing off in BI). BI is showing that it's sending to AI, and AI look to be receiving but I can't say for sure until something crosses a camera or I get home.
|
|
|
|
|