|
Can confirm, same for me.
|
|
|
|
|
I am experiencing a similar issue updating from 2.5.4 but the service for 2.5.5 wont start. I downgraded to 2.5.4 till code project figures out the obvious bugs in 2.5.5
|
|
|
|
|
Something is busted. We're on it! Just testing 2.5.6 which should fix most of the issues with 2.5.5
Thanks,
Sean Ewington
CodeProject
modified 28-Feb-24 11:51am.
|
|
|
|
|
2.5.6 is out for Windows only and should have addressed these issues. Please give it a try.
Thanks,
Sean Ewington
CodeProject
|
|
|
|
|
Anyone else getting this error with the lastest docker? This is happening for me both on a PI and the x64 dockers.
Unhandled exception. System.Collections.Generic.KeyNotFoundException: The given key 'version' was not present in the dictionary.
at System.Collections.Generic.Dictionary`2.get_Item(TKey key)
at CodeProject.AI.SDK.Common.SystemInfo.GetRuntimesAsync()
at CodeProject.AI.SDK.Common.SystemInfo.InitializeAsync()
at CodeProject.AI.Server.Program.Main(String[] args)
at CodeProject.AI.Server.Program.<Main>(String[] args)
|
|
|
|
|
I get the same error on the Windows version of 2.5.5.
|
|
|
|
|
Same here. Docker running on unraid. cuda12_2-2.5.5 build. First I thought it was because my updates kept stalling out, but they continued in the background. Still get the same error after multiple attempts. downgrading back to 2.5.4 now.
**EDIT Downgrade works fine.
modified 27-Feb-24 20:00pm.
|
|
|
|
|
I am seeing this in Docker.
codeproject-ai-server-cpu | /bin/bash: line 1: pstree: command not found
codeproject-ai-server-cpu | Unhandled exception. System.Collections.Generic.KeyNotFoundException: The given key 'version' was not present in the dictionary.
codeproject-ai-server-cpu | at System.Collections.Generic.Dictionary`2.get_Item(TKey key)
codeproject-ai-server-cpu | at CodeProject.AI.SDK.Common.SystemInfo.GetRuntimesAsync()
codeproject-ai-server-cpu | at CodeProject.AI.SDK.Common.SystemInfo.InitializeAsync()
codeproject-ai-server-cpu | at CodeProject.AI.Server.Program.Main(String[] args)
codeproject-ai-server-cpu | at CodeProject.AI.Server.Program.<Main>(String[] args)
codeproject-ai-server-cpu exited with code 0
|
|
|
|
|
|
same here, both arm and rpi images
|
|
|
|
|
I am having the same issue starting in 2.5.5 in rpi64 docker too.
Is there a way to pull 2.5.4 rpi image down again as my server is now broken
When I pull with :rpi64 there doesn't seem to be a way to specify the version of the image.
|
|
|
|
|
docker pull codeproject/ai-server:rpi64-2.5.4
|
|
|
|
|
|
Something is busted. We're on it! Just testing 2.5.6 which should fix most of the issues with 2.5.5
Thanks,
Sean Ewington
CodeProject
modified 28-Feb-24 11:52am.
|
|
|
|
|
Just playing around with our upcoming genAI module
cheers
Chris Maunder
|
|
|
|
|
Lol! Trained on a certain recent newsworthy manufacturers dataset...
Will it churn out code?
|
|
|
|
|
BI said "nothing to fly"
>64
It’s weird being the same age as old people. Live every day like it is your last; one day, it will be.
|
|
|
|
|
Hi, I run docker image codeproject/ai-server:rpi64 on RPI with USB Coral. Object detection (Coral) works nice there but is there a way to get there working also Face processing module? I cannot see any option how to install it.
modified 4-Mar-24 16:52pm.
|
|
|
|
|
Face Recognition doesn't (at the moment) support Coral.AI modules
cheers
Chris Maunder
|
|
|
|
|
Hi,
I'm running v2.5.4 with Object Detection (Coral) v2.14, for the life of me, I cannot get it working with YOLOv8. I'm getting the following all of the time, when it tries to detect something.
12:51:35:Response rec'd from Object Detection (Coral) command 'detect' (...362187)
12:51:36:Object Detection (Coral): [IndexError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\objectdetection_coral_adapter.py", line 167, in _do_detection
result = do_detect(opts, img, score_threshold)
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\objectdetection_coral.py", line 222, in do_detect
objs = detect.get_objects(interpreter, score_threshold, scale)
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\bin\windows\python39\venv\lib\site-packages\pycoral\adapters\detect.py", line 214, in get_objects
elif common.output_tensor(interpreter, 3).size == 1:
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\bin\windows\python39\venv\lib\site-packages\pycoral\adapters\common.py", line 29, in output_tensor
return interpreter.tensor(interpreter.get_output_details()[i]['index'])()
IndexError: list index out of range
I've tried changing the size of the model, to no avail.
<pre>12:45:12:Server version: 2.5.4
12:45:15:
12:45:15:Module 'Object Detection (Coral)' 2.1.4 (ID: ObjectDetectionCoral)
12:45:15:Valid: True
12:45:15:Module Path: <root>\modules\ObjectDetectionCoral
12:45:15:AutoStart: True
12:45:15:Queue: objectdetection_queue
12:45:15:Runtime: python3.9
12:45:15:Runtime Loc: Local
12:45:15:FilePath: objectdetection_coral_adapter.py
12:45:15:Pre installed: False
12:45:15:Start pause: 1 sec
12:45:15:Parallelism: 1
12:45:15:LogVerbosity:
12:45:15:Platforms: all
12:45:15:GPU Libraries: installed if available
12:45:15:GPU Enabled: enabled
12:45:15:Accelerator:
12:45:15:Half Precis.: enable
12:45:15:Environment Variables
12:45:15:CPAI_CORAL_MODEL_NAME = YOLOv8
12:45:15:CPAI_CORAL_MULTI_TPU = False
12:45:15:MODELS_DIR = <root>\modules\ObjectDetectionCoral\assets
12:45:15:MODEL_SIZE = medium
12:45:15:
12:45:15:Started Object Detection (Coral) module
12:45:17:Server: This is the latest version
12:45:22:objectdetection_coral_adapter.py: Using model yolov8, size medium
12:45:22:objectdetection_coral_adapter.py: TPU detected
12:45:22:objectdetection_coral_adapter.py: Using Edge TPU
I've only managed to get the MobileNet model working, but it is not very accurate even on large.
I've tried to run ..\..\setup again, as well
Thanks in advance for any help!
David
|
|
|
|
|
Try enabling the multi-TPU option.
|
|
|
|
|
Thanks! That seems to have fixed it, slightly counter intuitive, as I only have one USB TPU.
Are the following errors OK?
15:55:11:System: Windows
15:55:11:Operating System: Windows (Microsoft Windows 11 version 10.0.22621)
15:55:11:CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
15:55:11: 1 CPU x 4 cores. 8 logical processors (x64)
15:55:11:GPU (Primary): Intel(R) HD Graphics 530 (1,024 MiB) (Intel Corporation)
15:55:11: Driver: 27.20.100.9664
15:55:11:System RAM: 24 GiB
15:55:11:Platform: Windows
15:55:11:BuildConfig: Release
15:55:11:Execution Env: Native
15:55:11:Runtime Env: Production
15:55:11:.NET framework: .NET 7.0.5
15:55:11:Default Python:
15:55:11:App DataDir: C:\ProgramData\CodeProject\AI
15:55:11:Video adapter info:
15:55:11: Intel(R) HD Graphics 530:
15:55:11: Driver Version 27.20.100.9664
15:55:11: Video Processor Intel(R) HD Graphics Family
15:55:11:STARTING CODEPROJECT.AI SERVER
15:55:11:RUNTIMES_PATH = C:\Program Files\CodeProject\AI\runtimes
15:55:11:PREINSTALLED_MODULES_PATH = C:\Program Files\CodeProject\AI\preinstalled-modules
15:55:11:MODULES_PATH = C:\Program Files\CodeProject\AI\modules
15:55:11:PYTHON_PATH = \bin\windows\%PYTHON_NAME%\venv\Scripts\python
15:55:11:Data Dir = C:\ProgramData\CodeProject\AI
15:55:11:Server version: 2.5.4
15:55:14:
15:55:14:Module 'Object Detection (Coral)' 2.1.4 (ID: ObjectDetectionCoral)
15:55:14:Valid: True
15:55:14:Module Path: <root>\modules\ObjectDetectionCoral
15:55:14:AutoStart: True
15:55:14:Queue: objectdetection_queue
15:55:14:Runtime: python3.9
15:55:14:Runtime Loc: Local
15:55:14:FilePath: objectdetection_coral_adapter.py
15:55:14:Pre installed: False
15:55:14:Start pause: 1 sec
15:55:14:Parallelism: 1
15:55:14:LogVerbosity:
15:55:14:Platforms: all
15:55:14:GPU Libraries: installed if available
15:55:14:GPU Enabled: enabled
15:55:14:Accelerator:
15:55:14:Half Precis.: enable
15:55:14:Environment Variables
15:55:14:CPAI_CORAL_MODEL_NAME = YOLOv8
15:55:14:CPAI_CORAL_MULTI_TPU = True
15:55:14:MODELS_DIR = <root>\modules\ObjectDetectionCoral\assets
15:55:14:MODEL_SIZE = large
15:55:14:
15:55:14:Started Object Detection (Coral) module
15:55:16:Server: This is the latest version
15:55:21:objectdetection_coral_adapter.py: Using model yolov8, size large
15:55:21:objectdetection_coral_adapter.py: TPU detected
15:55:21:objectdetection_coral_adapter.py: Attempting multi-TPU initialisation
15:55:21:objectdetection_coral_adapter.py: Supporting multiple Edge TPUs
15:55:21:objectdetection_coral_adapter.py: WARNING: Logging before InitGoogleLogging() is written to STDERR
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.973263 14256 pipelined_model_runner.cc:171] Thread: 14256 receives empty request
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.973263 14256 pipelined_model_runner.cc:244] Thread: 14256 is shutting down the pipeline...
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.973263 14256 pipelined_model_runner.cc:254] Thread: 14256 Pipeline is off.
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.973263 13396 pipelined_model_runner.cc:206] Queue is empty and `StopWaiters()` is called.
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.973263 14256 pipelined_model_runner.cc:171] Thread: 14256 receives empty request
15:55:21:objectdetection_coral_adapter.py: E20240226 15:55:21.973263 14256 pipelined_model_runner.cc:239] Thread: 14256 Pipeline was turned off before.
15:55:21:objectdetection_coral_adapter.py: I20240226 15:55:21.975266 14256 pipelined_model_runner.cc:206] Queue is empty and `StopWaiters()` is called.
15:55:21:objectdetection_coral_adapter.py: E20240226 15:55:21.975266 14256 pipelined_model_runner.cc:239] Thread: 14256 Pipeline was turned off before.
15:55:21:objectdetection_coral_adapter.py: E20240226 15:55:21.975266 14256 pipelined_model_runner.cc:146] Failed to shutdown status: INTERNAL: Pipeline was turned off before.
15:55:27:Response rec'd from Object Detection (Coral) command 'detect' (...e3e58a) [''] took 5543ms
15:55:27:Response rec'd from Object Detection (Coral) command 'detect' (...f3b589) [''] took 346ms
15:55:28:Response rec'd from Object Detection (Coral) command 'detect' (...8ce805) [''] took 342ms
15:55:28:Response rec'd from Object Detection (Coral) command 'detect' (...207b05) [''] took 412ms
15:55:29:Response rec'd from Object Detection (Coral) command 'detect' (...c81b17) [''] took 408ms
15:57:09:Response rec'd from Object Detection (Coral) command 'd
Thanks
|
|
|
|
|
The multi-TPU code is basically a newer, different, code path. In theory it’s better, but it may also have more bugs and need to be matured a bit more. So it’s not the default.
I don’t see any problems in the above messages that you’re seeing.
FWIW, the USB connection tends to have its own flakey emergent properties. Sometimes it’s hard to get working reliably. Good to hear it’s working for you.
Also, I’d not recommend the large model with a single Coral TPU. Basically, the large YOLO model is 44 MB in size, but the TPU only contains 8 MB in cache, so most of the model runs on the CPU. You can get one or two more TPUs for better performance. With only one TPU, I’d run a small YOLO model.
|
|
|
|
|
|
I'm struggling to understand what's happening and I require assistance. I had to opt for Yolo.net as the standard version that utilises CUDA consistently crashed after 12 hours. The discussion on this topic seems to have ceased. Nonetheless, could someone elucidate why, despite having quite aggressive trigger settings in Blue Iris (Night Profile: Min Confidence 60%, Pre-Trigger images: 3, Post-Trigger images: 30, Analyse one image every 100ms), CodeProject failed to detect me walking past my camera upon my return home? Here is the screenshot with AI analysis.
It keeps happening quite frequently now and when I was using CUDA (Yolo 5.6.2) I'm sure it was detecting and processing way better than this. Any ideas? Can I force the AI to recheck in this instance ?
It's important I address this as the image below could have well been an intruder !
|
|
|
|