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Using latest CPAI (2.5.6) with latest Coral module. Fresh install, every other module except Coral turned off. Blue Iris has face detection turned off.
I'm getting error 500 after almost every trigger from Blue Iris (latest stable).
Not using any custom models or anything. Literally a fresh install of CPAI from Docker on Linux, using Coral. (So default model: MobileNet SSD, default option: Multi-TPU).
modified 13-Mar-24 14:36pm.
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Hi,
Tried updating yolov8 to v1.4.0 and got this error:
Unable to download module 'ObjectDetectionYOLOv8' from https:
That URL doesn't seem valid; any ideas? It uninstalled the previous version and I'm now stuck.
Thanks
modified 13-Mar-24 18:30pm.
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I'm getting this error:
Error in Update ObjectDetectionYOLOv8: API server is offline (NetworkError when attempting to fetch resource.)
Also, no indication that an update was happening.
15:06:30:Server version: 2.5.6
15:06:35:Server: This is the latest version
15:06:51:Preparing to install module 'ObjectDetectionYOLOv8'
15:06:51:Downloading module 'ObjectDetectionYOLOv8'
15:06:51:Unable to download module 'ObjectDetectionYOLOv8' from https:
Now it's broken. No option to re-install
EDIT - Wait F5 to the rescue but have to re-install
EDIT 2 Nope, still broken
There also appears to be no way to revert to an older version. After trying to re-install YOLO V8 it just shows "Unknown"
modified 12-Mar-24 18:48pm.
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Thanks very much for the report. We're looking into it.
Thanks,
Sean Ewington
CodeProject
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Please try uninstalling and reinstalling the module, with "Do not use download cache" turned on.
Thanks,
Sean Ewington
CodeProject
modified 13-Mar-24 18:30pm.
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It's working for me now, although I had to reboot to get is to start detecting.
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Where did you find the update to 1.4.0 for YOLOV8 ?
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We actually ended up reverting the module for 2.5.6. You want to be using no later than YOLOv8 1.3.1.
Thanks,
Sean Ewington
CodeProject
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Nvidia 1050Ti (best I can do on my motherboard)
Hi,
In the hope it might fix my problem below, Is there a way to remove cuda 12.4.
I assume it was installed with Nvidia drivers. There is no mention in Windows Add/Remove. JUST 11.7 (& before 11.8), I had installed a variety in the past, removed 11.8 for the moment ..
ALPR GPU CUDA is started but does not detect anything, CPU mode does.
Now a few months after several days of trying to get CUDA enabled for ALPR, I gave up, CPU (only) worked but too slow.
New CPAI 2.5.6 thought have another go.
Only ever had CPU option before.
Object detection worked before & still OK in GPU, Cuda mode
ALPR CPU did work OK but was far too slow for what I wanted.
Back then tried dozens of combinations 11.7, 11.8, 12, CPAI versions, installs using all the procedures as described.
NOW, enabled but does not recognise any plates, No predictions returned using explorer & also in Blue Iris.
If I disable GPU mode & back to running in CPU it does find the plate OK.
08:21:32:System: Windows
08:21:32:Operating System: Windows (Microsoft Windows 10.0.19045)
08:21:32:CPUs: Intel(R) Core(TM) i7-4790 CPU @ 3.60GHz (Intel)
08:21:32: 1 CPU x 4 cores. 8 logical processors (x64)
08:21:32:GPU (Primary): NVIDIA GeForce GTX 1050 Ti (4 GiB) (NVIDIA)
08:21:32: Driver: 551.76, CUDA: 12.4 (up to: 12.4), Compute: 6.1, cuDNN: 8.9
08:21:32:System RAM: 16 GiB
08:21:32:Platform: Windows
08:21:32:BuildConfig: Release
08:21:32:Execution Env: Native
08:21:32:Runtime Env: Production
08:21:32:Runtimes installed:
08:21:32: .NET runtime: 7.0.10
08:21:32: .NET SDK: Not found
08:21:32: Default Python: 3.9.7
08:21:32: Go: Not found
08:21:32: NodeJS: Not found
08:21:32:App DataDir: C:\ProgramData\CodeProject\AI
08:21:32:Video adapter info:
08:21:32: NVIDIA GeForce GTX 1050 Ti:
08:21:32: Driver Version 31.0.15.5176
08:21:32: Video Processor NVIDIA GeForce GTX 1050 Ti
08:21:32: Intel(R) HD Graphics 4600:
08:21:32: Driver Version 20.19.15.5126
08:21:32: Video Processor Intel(R) HD Graphics Family
08:21:32:STARTING CODEPROJECT.AI SERVER
08:21:32:RUNTIMES_PATH = C:\Program Files\CodeProject\AI\runtimes
08:21:32:PREINSTALLED_MODULES_PATH = C:\Program Files\CodeProject\AI\preinstalled-modules
08:21:32:MODULES_PATH = C:\Program Files\CodeProject\AI\modules
08:21:32:PYTHON_PATH = \bin\windows\%PYTHON_NAME%\venv\Scripts\python
08:21:32:Data Dir = C:\ProgramData\CodeProject\AI
08:21:32:Server version: 2.5.6
08:21:36:
08:21:36:Attempting to start ALPR with C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python39\venv\Scripts\python "C:\Program Files\CodeProject\AI\modules\ALPR\ALPR_adapter.py"
08:21:36:
08:21:36:Module 'License Plate Reader' 3.0.2 (ID: ALPR)
08:21:36:Valid: True
08:21:36:Module Path: <root>\modules\ALPR
08:21:36:AutoStart: True
08:21:36:Queue: alpr_queue
08:21:36:Runtime: python3.9
08:21:36:Runtime Loc: Local
08:21:36:FilePath: ALPR_adapter.py
08:21:36:Pre installed: False
08:21:36:Start pause: 3 sec
08:21:36:Parallelism: 0
08:21:36:LogVerbosity:
08:21:36:Platforms: all
08:21:36:GPU Libraries: installed if available
08:21:36:GPU Enabled: enabled
08:21:36:Accelerator:
08:21:36:Half Precis.: enable
08:21:36:Environment Variables
08:21:36:AUTO_PLATE_ROTATE = false
08:21:36:MIN_COMPUTE_CAPABILITY = 6
08:21:36:MIN_CUDNN_VERSION = 7
08:21:36:OCR_OPTIMAL_CHARACTER_HEIGHT = 60
08:21:36:OCR_OPTIMAL_CHARACTER_WIDTH = 30
08:21:36:OCR_OPTIMIZATION = True
08:21:36:PLATE_CONFIDENCE = 0.50
08:21:36:PLATE_RESCALE_FACTOR = 2
08:21:36:PLATE_ROTATE_DEG = 0
08:21:36:
08:21:36:Started License Plate Reader module
08:21:38:Current Version is 2.5.6
08:21:38:Server: This is the latest version
08:21:39:
08:21:39:Attempting to start ObjectDetectionYOLOv5-6.2 with C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Scripts\python "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\detect_adapter.py"
08:21:39:
08:21:39:Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
08:21:39:Valid: True
08:21:39:Module Path: <root>\modules\ObjectDetectionYOLOv5-6.2
08:21:39:AutoStart: True
08:21:39:Queue: objectdetection_queue
08:21:39:Runtime: python3.7
08:21:39:Runtime Loc: Shared
08:21:39:FilePath: detect_adapter.py
08:21:39:Pre installed: False
08:21:39:Start pause: 1 sec
08:21:39:Parallelism: 0
08:21:39:LogVerbosity:
08:21:39:Platforms: all,!raspberrypi,!jetson
08:21:39:GPU Libraries: installed if available
08:21:39:GPU Enabled: enabled
08:21:39:Accelerator:
08:21:39:Half Precis.: enable
08:21:39:Environment Variables
08:21:39:APPDIR = <root>\modules\ObjectDetectionYOLOv5-6.2
08:21:39:CPAI_MODULE_ENABLE_GPU = True
08:21:39:CUSTOM_MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-6.2\custom-models
08:21:39:MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-6.2\assets
08:21:39:MODEL_SIZE = Medium
08:21:39:USE_CUDA = True
08:21:39:YOLOv5_AUTOINSTALL = false
08:21:39:YOLOv5_VERBOSE = false
08:21:39:
08:21:39:Started Object Detection (YOLOv5 6.2) module
08:21:50:Sending shutdown request to python/ObjectDetectionYOLOv5-6.2
08:22:01:detect_adapter.py: APPDIR: C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2
08:22:01:detect_adapter.py: MODEL_SIZE: medium
08:22:01:detect_adapter.py: MODELS_DIR: C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\assets
08:22:01:Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'Quit'
08:22:16:detect_adapter.py: Object Detection (YOLOv5 6.2) started.
08:22:17:Module ObjectDetectionYOLOv5-6.2 has shutdown
08:22:17:detect_adapter.py: has exited
08:22:23:ObjectDetectionYOLOv5-6.2 went quietly
08:22:23:
08:22:23:Attempting to start ObjectDetectionYOLOv5-6.2 with C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Scripts\python "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\detect_adapter.py"
08:22:23:
08:22:23:Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
08:22:23:Valid: True
08:22:23:Module Path: <root>\modules\ObjectDetectionYOLOv5-6.2
08:22:23:AutoStart: True
08:22:23:Queue: objectdetection_queue
08:22:23:Runtime: python3.7
08:22:23:Runtime Loc: Shared
08:22:23:FilePath: detect_adapter.py
08:22:23:Pre installed: False
08:22:23:Start pause: 1 sec
08:22:23:Parallelism: 0
08:22:23:LogVerbosity:
08:22:23:Platforms: all,!raspberrypi,!jetson
08:22:23:GPU Libraries: installed if available
08:22:23:GPU Enabled: enabled
08:22:23:Accelerator:
08:22:23:Half Precis.: enable
08:22:23:Environment Variables
08:22:23:APPDIR = <root>\modules\ObjectDetectionYOLOv5-6.2
08:22:23:CPAI_MODULE_ENABLE_GPU = True
08:22:23:CUSTOM_MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-6.2\custom-models
08:22:23:MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-6.2\assets
08:22:23:MODEL_SIZE = Medium
08:22:23:USE_CUDA = True
08:22:23:YOLOv5_AUTOINSTALL = false
08:22:23:YOLOv5_VERBOSE = false
08:22:23:
08:22:23:Started Object Detection (YOLOv5 6.2) module
08:22:39:detect_adapter.py: APPDIR: C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2
08:22:39:detect_adapter.py: MODEL_SIZE: medium
08:22:39:detect_adapter.py: MODELS_DIR: C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\assets
modified 13-Mar-24 14:37pm.
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This user had the same issue as you and I think it may be worth going through their thread (though they're on a different system).
CodeProject.AI Server: AI the easy way.[^]
Thanks,
Sean Ewington
CodeProject
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SOLVED. Windows 10
I cannot really advise what fixed this but just to advise of things I tried & there were dozens & dozens of variations, reboots etc etc. I had tried even more a while ago but was on an older CPAI. Now latest 2.5.6, not sure relevant or just finally hit the right pattern. Below might not be 100% as was rather bashing about in desperation. Once is did show Cuda enabled but did not read a plate, later crashed on other fiddling.
I have Licence plate working 1050Ti, Cuda 11.8 CuDNN to match.
11.8 is reported in Nvidia components (this was 12.4 before despite not being mentioned in Add/Remove)
I always had 11.8 with cmd "nvcc --version" despite Nvidia reporting 12.4
I uninstalled Licence Plate
I Add/Removed NVidia graphics driver, then from Device manager as seemed to remain.
I did not reinstall Nvidia. I used the BAT & it loaded 11.8 & this was confirmed in Nvidia/control panel/components.
(I Had tried below with LP installed & did not work, think an error when starting)
Lots of reboots & I think other bits & pieces but it eventually started working & reading the plates correctly!
I am sure had done these steps when I tried some months ago (I tried hundreds of combinations) so not sure what was the magic bullet this time.
modified 13-Mar-24 14:37pm.
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Hello, I can't seem to get Project AI Object Detection to enable my newly installed Tesla P4. Any idea what I'm doing wrong? YOLOv5 Doesn't have the option to enable the GPU and only the CPU shows.
18:46:20:System: Windows
18:46:20:Operating System: Windows (Microsoft Windows 10.0.19045)
18:46:20:CPUs: Intel(R) Core(TM) i5-3570 CPU @ 3.40GHz (Intel)
18:46:20: 1 CPU x 4 cores. 4 logical processors (x64)
18:46:20:GPU (Primary): Tesla P4 (8 GiB) (NVIDIA)
18:46:20: Driver: 551.61, CUDA: 12.4 (up to: 12.4), Compute: 6.1, cuDNN: 8.9
18:46:20:System RAM: 16 GiB
18:46:20:Platform: Windows
18:46:20:BuildConfig: Release
18:46:20:Execution Env: Native
18:46:20:Runtime Env: Production
18:46:20:Runtimes installed:
18:46:20: .NET runtime: 7.0.10
18:46:20: .NET SDK: Not found
18:46:20: Default Python: Not found
18:46:20: Go: Not found
18:46:20: NodeJS: Not found
18:46:20:App DataDir: C:\ProgramData\CodeProject\AI
18:46:20:Video adapter info:
18:46:20: Intel(R) HD Graphics:
18:46:20: Driver Version 10.18.10.4425
18:46:20: Video Processor Intel(R) HD Graphics Family
18:46:20: NVIDIA Tesla P4:
18:46:20: Driver Version 31.0.15.5161
18:46:20: Video Processor
18:46:20:STARTING CODEPROJECT.AI SERVER
18:46:20:RUNTIMES_PATH = C:\Program Files\CodeProject\AI\runtimes
18:46:20:PREINSTALLED_MODULES_PATH = C:\Program Files\CodeProject\AI\preinstalled-modules
18:46:20:MODULES_PATH = C:\Program Files\CodeProject\AI\modules
18:46:20:PYTHON_PATH = \bin\windows\%PYTHON_NAME%\venv\Scripts\python
18:46:20:Data Dir = C:\ProgramData\CodeProject\AI
18:46:20:Server version: 2.5.6
18:46:23:
18:46:23:Module 'Object Detection (YOLOv5 3.1)' 1.9.1 (ID: ObjectDetectionYOLOv5-3.1)
18:46:23:Valid: True
18:46:23:Module Path: <root>\modules\ObjectDetectionYOLOv5-3.1
18:46:23:AutoStart: True
18:46:23:Queue: objectdetection_queue
18:46:23:Runtime: python3.7
18:46:23:Runtime Loc: Local
18:46:23:FilePath: detect_adapter.py
18:46:23:Pre installed: False
18:46:23:Start pause: 1 sec
18:46:23:Parallelism: 0
18:46:23:LogVerbosity:
18:46:23:Platforms: all,!macos-arm64
18:46:23:GPU Libraries: installed if available
18:46:23:GPU Enabled: enabled
18:46:23:Accelerator:
18:46:23:Half Precis.: enable
18:46:23:Environment Variables
18:46:23:APPDIR = <root>\modules\ObjectDetectionYOLOv5-3.1
18:46:23:CPAI_MODULE_ENABLE_GPU = True
18:46:23:DATA_DIR = C:\ProgramData\CodeProject\AI
18:46:23:MODE = MEDIUM
18:46:23:MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-3.1\assets
18:46:23:PROFILE = desktop_gpu
18:46:23:TEMP_PATH = <root>\modules\ObjectDetectionYOLOv5-3.1\tempstore
18:46:23:USE_CUDA = True
18:46:23:YOLOv5_VERBOSE = false
18:46:23:
18:46:23:Started Object Detection (YOLOv5 3.1) module
18:46:26:Server: This is the latest version
18:49:12:Sending shutdown request to python/ObjectDetectionYOLOv5-3.1
18:49:12:detect_adapter.py: Object Detection (YOLOv5 3.1) started.
18:49:13:Module ObjectDetectionYOLOv5-3.1 has shutdown
18:49:13:detect_adapter.py: has exited
18:49:45:ObjectDetectionYOLOv5-3.1 went quietly
18:49:45:
18:49:45:Module 'Object Detection (YOLOv5 3.1)' 1.9.1 (ID: ObjectDetectionYOLOv5-3.1)
18:49:45:Valid: True
18:49:45:Module Path: <root>\modules\ObjectDetectionYOLOv5-3.1
18:49:45:AutoStart: True
18:49:45:Queue: objectdetection_queue
18:49:45:Runtime: python3.7
18:49:45:Runtime Loc: Local
18:49:45:FilePath: detect_adapter.py
18:49:45:Pre installed: False
18:49:45:Start pause: 1 sec
18:49:45:Parallelism: 0
18:49:45:LogVerbosity:
18:49:45:Platforms: all,!macos-arm64
18:49:45:GPU Libraries: installed if available
18:49:45:GPU Enabled: enabled
18:49:45:Accelerator:
18:49:45:Half Precis.: enable
18:49:45:Environment Variables
18:49:45:APPDIR = <root>\modules\ObjectDetectionYOLOv5-3.1
18:49:45:CPAI_MODULE_ENABLE_GPU = True
18:49:45:DATA_DIR = C:\ProgramData\CodeProject\AI
18:49:45:MODE = MEDIUM
18:49:45:MODELS_DIR = <root>\modules\ObjectDetectionYOLOv5-3.1\assets
18:49:45:PROFILE = desktop_gpu
18:49:45:TEMP_PATH = <root>\modules\ObjectDetectionYOLOv5-3.1\tempstore
18:49:45:USE_CUDA = True
18:49:45:YOLOv5_VERBOSE = false
18:49:45:
18:49:45:Started Object Detection (YOLOv5 3.1) module
modified 14-Mar-24 12:19pm.
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Thank you! That did help keep YOLOv5 from crashing but YOLOv5 still only uses the CPU and no option to enable GPU. Whats odd is that BlueIris is responding 50x faster as before I installed the Tesla P4. Here is the system info:
Server version: 2.5.6
System: Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs: Intel(R) Core(TM) i5-3570 CPU @ 3.40GHz (Intel)
1 CPU x 4 cores. 4 logical processors (x64)
GPU (Primary): Intel(R) HD Graphics (2 GiB) (Intel Corporation)
Driver: 10.18.10.4425
System RAM: 16 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.10
.NET SDK: Not found
Default Python: Not found
Go: Not found
NodeJS: Not found
Video adapter info:
Intel(R) HD Graphics:
Driver Version 10.18.10.4425
Video Processor Intel(R) HD Graphics Family
NVIDIA Tesla P4:
Driver Version 30.0.14.7168
Video Processor Tesla P4
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 4 MiB
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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Could you please run the nvidia-smi command and then the nvcc --version command and let me know what it shows?
Thanks,
Sean Ewington
CodeProject
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[nvidia-smi.exe]
Unable to determine the device handle for GPU 0000:01:00.0: GPU is lost. Reboot the system to recover this GPU
[nvcc --version]
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Sep_21_10:41:10_Pacific_Daylight_Time_2022
Cuda compilation tools, release 11.8, V11.8.89
Build cuda_11.8.r11.8/compiler.31833905_0
[nvidia-smi.exe] after reboot
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 471.68 Driver Version: 471.68 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla P4 WDDM | 00000000:01:00.0 Off | 0 |
| N/A 34C P8 7W / 75W | 146MiB / 7680MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 852 C+G Insufficient Permissions N/A |
+-----------------------------------------------------------------------------+
modified 12-Mar-24 13:27pm.
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Okay, just a random thought: Do you know if your YOLOv5 was installed with the dependencies necessary to run on GPU? Perhaps it was 'not detected' previously, so those required dependencies were not downloaded?
Maybe, worth to try to reinstall YoloV5?
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Just reinstalled YOLOv5. GPU still not showing available to enable. Thank you for the suggestion though.
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it may not be relevant but I am having similar issues with YOLO not working on 2 CodePorject installs. Both systems where I am having problems are using a Tesla P4 with the Nvidia Grid drivers, CUDA 11.8 and CUDNN 8.9.
CodeProject.AI Server: AI the easy way.[^]
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Sounds very similar. Does your object detection work as if there is no issues... as if the Tesla is processing images?
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Actually, no. I took a picture from one of my BlueIris alerts and tried Object detection in explorer. For both systems where I am having issues object detection immediately reports back "No predictions returned" I took the same picture and ran it through object detection on a temp machine I threw an OS and CodeProject on just to see what would happen and it works perfectly, it correctly detected a person, a car, even a backpack. I installed CodeProject exactly the same way on all 3 systems and the OS is the same, the only difference is the hardware. I can't imagine why the Tesla GPU would cause this but it's starting to feel like that's part of my issue.
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I just noticed that you are using YOLOv5 3.1. And based on your first post, your Tesla P4 is having CUDA 12.4:
18:46:20:GPU (Primary): Tesla P4 (8 GiB) (NVIDIA)
18:46:20: Driver: 551.61, CUDA: 12.4 (up to: 12.4), Compute: 6.1, cuDNN: 8.9
Based on the description of YOLOv5 3.1, it is for CUDA 10 or 11 for older GPUs
Object Detection (YOLOv5 3.1)
2024-02-08
GPL-3.0Provides Object Detection using YOLOv5 3.1 targeting CUDA 10 or 11 for older GPUs.
Project by Chris Maunder, Matthew Dennis, based on Deepstack. Uses Python, PyTorch, YOLO. Your CUDA version is above the 3.1's description. Maybe that's why it is not using GPU?
Now, if you look at the YOLOv5 6.2's description, it is for 11.5+ which matches with your Tesla P4's setup:
Object Detection (YOLOv5 6.2)
2024-02-08
GPL-3.0Provides Object Detection using YOLOv5 6.2 targeting CUDA 11.5+, PyTorch < 2.0 for newer GPUs.
Project by Matthew Dennis, based on Ultralytics YOLOv5.
My computer that has Tesla P4 is using YOLOv5 6.2 and it is using the GPU.
I hope this solves it.
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Thank you! Based on your suggestion I did a full tear-down and used the GRID driver, CUDA 11.8, cuDNN-8.9.4 and YOLOv5 6.2. Everything worked for a good 10 minutes and then it crashed. Do you recommend a specific CUDA version?
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This is what I have for my GPU:
GPU (Primary): Tesla P4 (8 GiB) (NVIDIA)
Driver: 538.15, CUDA: 12.2 (up to: 12.2), Compute: 6.1, cuDNN: 8.9
I'm using the driver version of 538.15 from the following link: Drivers for NVIDIA RTX Virtual Workstation (vWS) | Compute Engine Documentation | Google Cloud[^].
Note: Left side of 538.15 says the CUDA version is 16.3, I don't know why it is saying that because it seems to be incorrect.
If possible, please post the log so we know what errors your CodeProject AI ran into. It should give some idea what caused the crash. And if it is something deeper, it might be helpful for Sean and others.
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