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Thanks very much for the report. Could you please share your System Info tab from your CodeProject.AI Server dashboard? Also, could you share the install logs for the module you try (and fail) to install?
Thanks,
Sean Ewington
CodeProject
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You bet, Sean.
System Information:
Server version: 2.6.5
System: Linux
Operating System: Linux (Ubuntu 22.04)
CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
1 CPU x 4 cores. 8 logical processors (x64)
GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
System RAM: 31 GiB
Platform: Linux
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.19
.NET SDK: 7.0.119
Default Python: 3.10.12
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
HD Graphics 530 (rev 06):
Driver Version
Video Processor
System GPU info:
GPU 3D Usage 0%
GPU RAM Usage 0
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
Even setting logging to verbosity to trace, the 404 error on any module install attempt isn't triggering any log entries. Nonetheless, here's my trace log. I am able to remove modules and watch them disappear from the /modules directory, but installing any back is causing issues. Thanks again!
2024-06-02 07:22:17: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:22:17: ** System: Linux
2024-06-02 07:22:17: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:22:17: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:22:17: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:22:17: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:22:17: ** System RAM: 31 GiB
2024-06-02 07:22:17: ** Platform: Linux
2024-06-02 07:22:17: ** BuildConfig: Release
2024-06-02 07:22:17: ** Execution Env: Native
2024-06-02 07:22:17: ** Runtime Env: Production
2024-06-02 07:22:17: ** Runtimes installed:
2024-06-02 07:22:17: ** .NET runtime: 7.0.19
2024-06-02 07:22:17: ** .NET SDK: 7.0.119
2024-06-02 07:22:17: ** Default Python: 3.10.12
2024-06-02 07:22:17: ** Go: Not found
2024-06-02 07:22:17: ** NodeJS: Not found
2024-06-02 07:22:17: ** Rust: Not found
2024-06-02 07:22:17: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:22:17: Video adapter info:
2024-06-02 07:22:17: HD Graphics 530 (rev 06):
2024-06-02 07:22:17: Driver Version
2024-06-02 07:22:17: Video Processor
2024-06-02 07:22:17: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:22:17: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:22:17: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:22:17: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:22:17: EXTERNAL_MODULES_PATH =
2024-06-02 07:22:17: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:22:17: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:22:17: Data Dir = /etc/codeproject/ai
2024-06-02 07:22:17: ** Server version: 2.6.5
2024-06-02 07:22:17: ModuleRunner Start
2024-06-02 07:22:17: Starting Background AI Modules
2024-06-02 07:22:20: ** Setting up initial modules. Please be patient...
2024-06-02 07:22:20: ** Installing initial module FaceProcessing.
2024-06-02 07:22:20: Preparing to install module 'FaceProcessing'
2024-06-02 07:22:21: Downloading module 'FaceProcessing'
2024-06-02 07:22:21: Installing module 'FaceProcessing'
2024-06-02 07:22:21: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:22:21: FaceProcessing: Setting verbosity to quiet
2024-06-02 07:22:21: FaceProcessing: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m======================================================================[0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:22:21: FaceProcessing: [0;32m[49m======================================================================[0m
2024-06-02 07:22:21: FaceProcessing: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:22:21: FaceProcessing: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[42mGPU support [0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:22:22: FaceProcessing: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:22:22: FaceProcessing: [0;97m[104mProcessing module FaceProcessing 1.10.2 [0m
2024-06-02 07:22:22: FaceProcessing: [0;39m[49mInstalling Python 3.8[0m
2024-06-02 07:22:22: FaceProcessing: [0;92m[49mPython 3.8 is already installed[0m
2024-06-02 07:22:22: Current Version is 2.6.5
2024-06-02 07:22:22: Server: This is the latest version
2024-06-02 07:22:29: FaceProcessing: [0;97m[49mEnsuring PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:22:30: FaceProcessing: [0;97m[49mUpgrading PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:22:30: FaceProcessing: [0;97m[49mInstalling Virtual Environment tools for Linux...[0m
2024-06-02 07:22:31: FaceProcessing: [0;39m[49mSearching for python3-pip python3-setuptools python3.8...[0m[0;92m[49mAll good.[0m
2024-06-02 07:22:33: FaceProcessing: [0;97m[49mCreating Virtual Environment (Shared)...[0m [0;92m[49mdone[0m
2024-06-02 07:22:33: FaceProcessing: [0;97m[49mChecking for Python 3.8...[0m[0;37m[49m(Found Python 3.8.19) [0m[0;92m[49mAll good[0m
2024-06-02 07:22:35: FaceProcessing: [0;97m[49mUpgrading PIP in virtual environment...[0m [0;92m[49mdone[0m
2024-06-02 07:22:37: FaceProcessing: [0;97m[49mInstalling updated setuptools in venv...[0m [0;92m[49mdone[0m
2024-06-02 07:22:59: FaceProcessing: [0;97m[49mDownloading Face models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mMoving contents of models-face-pt.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mInstalling Python packages for Face Processing[0m
2024-06-02 07:22:59: FaceProcessing: [0;35m[49mInstalling GPU-enabled libraries: [0m[0;92m[49mIf available[0m
2024-06-02 07:22:59: FaceProcessing: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:23:01: FaceProcessing: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:23:01: FaceProcessing: [0;35m[49mPython packages will be specified by requirements.linux.txt[0m
2024-06-02 07:23:08: FaceProcessing: [0;97m[49m - Installing Pandas, a data analysis / data manipulation tool...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:18: FaceProcessing: [0;97m[49m - Installing CoreMLTools, for working with .mlmodel format models...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:23: FaceProcessing: [0;97m[49m - Installing OpenCV, the Open source Computer Vision library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:24: FaceProcessing: [0;97m[49m - Installing Pillow, a Python Image Library...[0m [0;91m[49m(❌ failed check) [0m[0;92m[49mdone[0m
2024-06-02 07:23:30: FaceProcessing: [0;97m[49m - Installing SciPy, a library for mathematics, science, and engineering...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:23:30: FaceProcessing: [0;97m[49m - Installing PyYAML, a library for reading configuration files...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:23:49: FaceProcessing: [0;97m[49m - Installing Torch, for Tensor computation and Deep neural networks...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:10: FaceProcessing: [0;97m[49m - Installing TorchVision, for Computer Vision based AI...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:22: FaceProcessing: [0;97m[49m - Installing Seaborn, a data visualization library based on matplotlib...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:22: FaceProcessing: [0;39m[49mInstalling Python packages for the CodeProject.AI Server SDK[0m
2024-06-02 07:24:22: FaceProcessing: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:24:24: FaceProcessing: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:24:24: FaceProcessing: [0;35m[49mPython packages will be specified by requirements.txt[0m
2024-06-02 07:24:24: FaceProcessing: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:24:27: FaceProcessing: [0;97m[49m - Installing Charset normalizer...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:30: FaceProcessing: [0;97m[49m - Installing aiohttp, the Async IO HTTP library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:32: FaceProcessing: [0;97m[49m - Installing aiofiles, the Async IO Files library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:34: FaceProcessing: [0;97m[49m - Installing py-cpuinfo to allow us to query CPU info...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:37: FaceProcessing: [0;97m[49m - Installing Requests, the HTTP library...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:24:37: FaceProcessing: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:24:42: FaceProcessing: Fusing layers...
2024-06-02 07:24:42: FaceProcessing: YOLOv5m summary: 316 layers, 21468630 parameters, 0 gradients
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mSelf test: [0m[0;92m[49mSelf-test passed[0m
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mModule setup time 00:02:24[0m
2024-06-02 07:24:46: FaceProcessing: [0;97m[42m Setup complete [0m
2024-06-02 07:24:46: FaceProcessing: [0;39m[49mTotal setup time 00:02:25[0m
2024-06-02 07:24:46: Module FaceProcessing installed successfully.
2024-06-02 07:24:46: Installer exited with code 0
2024-06-02 07:24:46: ** Installing initial module ObjectDetectionYOLOv5Net.
2024-06-02 07:24:46: Preparing to install module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:46: Downloading module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:46: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:24:46:
2024-06-02 07:24:46: Attempting to start FaceProcessing with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:24:46: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr.../FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:24:46:
2024-06-02 07:24:46: ** Module 'Face Processing' 1.10.2 (ID: FaceProcessing)
2024-06-02 07:24:46: ** Valid: True
2024-06-02 07:24:46: ** Module Path: <root>/modules/FaceProcessing
2024-06-02 07:24:46: ** Module Location: Internal
2024-06-02 07:24:46: ** AutoStart: True
2024-06-02 07:24:46: ** Queue: faceprocessing_queue
2024-06-02 07:24:46: ** Runtime: python3.8
2024-06-02 07:24:46: ** Runtime Location: Shared
2024-06-02 07:24:46: ** FilePath: intelligencelayer/face.py
2024-06-02 07:24:46: ** Start pause: 3 sec
2024-06-02 07:24:46: ** Parallelism: 0
2024-06-02 07:24:46: ** LogVerbosity:
2024-06-02 07:24:46: ** Platforms: all,!jetson
2024-06-02 07:24:46: ** GPU Libraries: installed if available
2024-06-02 07:24:46: ** GPU: use if supported
2024-06-02 07:24:46: ** Accelerator:
2024-06-02 07:24:46: ** Half Precision: enable
2024-06-02 07:24:46: ** Environment Variables
2024-06-02 07:24:46: ** APPDIR = <root>/modules/FaceProcessing/intelligencelayer
2024-06-02 07:24:46: ** DATA_DIR = /etc/codeproject/ai
2024-06-02 07:24:46: ** MODE = MEDIUM
2024-06-02 07:24:46: ** MODELS_DIR = <root>/modules/FaceProcessing/assets
2024-06-02 07:24:46: ** PROFILE = desktop_gpu
2024-06-02 07:24:46: ** USE_CUDA = True
2024-06-02 07:24:46: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:24:46: ** YOLOv5_VERBOSE = false
2024-06-02 07:24:46:
2024-06-02 07:24:46: Started Face Processing module
2024-06-02 07:24:47: Installing module 'ObjectDetectionYOLOv5Net'
2024-06-02 07:24:47: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: Setting verbosity to quiet
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m======================================================================[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;32m[49m======================================================================[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;97m[42mGPU support [0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:47: ObjectDetectionYOLOv5Net: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:24:48: ObjectDetectionYOLOv5Net: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:24:48: ObjectDetectionYOLOv5Net: [0;97m[104mProcessing module ObjectDetectionYOLOv5Net 1.10.1 [0m
2024-06-02 07:24:49: Module FaceProcessing started successfully.
2024-06-02 07:24:51: face.py: Vision AI services setup: Retrieving environment variables...
2024-06-02 07:24:51: face.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer
2024-06-02 07:24:51: face.py: PROFILE: desktop_cpu
2024-06-02 07:24:51: face.py: USE_CUDA: False
2024-06-02 07:24:51: face.py: DATA_DIR: /etc/codeproject/ai
2024-06-02 07:24:51: face.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/assets
2024-06-02 07:24:51: face.py: MODE: MEDIUM
2024-06-02 07:24:51: face.py: Running init for Face Processing
2024-06-02 07:24:59: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading ObjectDetectionYOLOv5Net-CPU-1.10.1.zip...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:24:59: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of ObjectDetectionYOLOv5Net-CPU-1.10.1.zip to bin...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:15: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading YOLO ONNX models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:15: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of yolonet-models.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;97m[49mDownloading Custom YOLO ONNX models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;39m[49mMoving contents of yolonet-custom-models.zip to custom-models...[0m[0;92m[49mdone.[0m
2024-06-02 07:25:26: ObjectDetectionYOLOv5Net: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mSelf test: [0m[0;91m[49mSelf-test failed[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mModule setup time 00:00:40[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;97m[42m Setup complete [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5Net: [0;39m[49mTotal setup time 00:00:40[0m
2024-06-02 07:25:27: Module ObjectDetectionYOLOv5Net installed successfully.
2024-06-02 07:25:27: Installer exited with code 0
2024-06-02 07:25:27: ** Installing initial module ObjectDetectionYOLOv5-6.2.
2024-06-02 07:25:27: Preparing to install module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Downloading module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Module ObjectDetectionYOLOv5Net not configured to AutoStart.
2024-06-02 07:25:27: Installing module 'ObjectDetectionYOLOv5-6.2'
2024-06-02 07:25:27: Installer script at '/usr/bin/codeproject.ai-server-2.6.5/setup.sh'
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: Setting verbosity to quiet
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;36m[49m Installing CodeProject.AI Analysis Module [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m======================================================================[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m CodeProject.AI Installer [0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;32m[49m======================================================================[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;37m[49m1.02 TiB of 1.00 TiB available on linux[0m
2024-06-02 07:25:27: ObjectDetectionYOLOv5-6.2: [0;35m[49mInstalling xz-utils...[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[42mGeneral CodeProject.AI setup [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on runtimes folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on downloads folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on modules download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on models download folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[49mSetting permissions on persisted data folder...[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[42mGPU support [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mCUDA (NVIDIA) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mROCm (AMD) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mMPS (Apple) Present: [0m[0;33m[49mNo[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;37m[49mReading module settings[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;37m[49m.[0m[0;92m[49mdone[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;97m[104mProcessing module ObjectDetectionYOLOv5-6.2 1.9.1 [0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python 3.8[0m
2024-06-02 07:25:28: ObjectDetectionYOLOv5-6.2: [0;92m[49mPython 3.8 is already installed[0m
2024-06-02 07:25:35: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;97m[49mUpgrading PIP in base python install...[0m [0;92m[49mdone[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;92m[49mVirtual Environment already present[0m
2024-06-02 07:25:36: ObjectDetectionYOLOv5-6.2: [0;97m[49mChecking for Python 3.8...[0m[0;37m[49m(Found Python 3.8.19) [0m[0;92m[49mAll good[0m
2024-06-02 07:25:37: ObjectDetectionYOLOv5-6.2: [0;97m[49mUpgrading PIP in virtual environment...[0m [0;92m[49mdone[0m
2024-06-02 07:25:39: ObjectDetectionYOLOv5-6.2: [0;97m[49mInstalling updated setuptools in venv...[0m [0;92m[49mdone[0m
2024-06-02 07:25:48: ObjectDetectionYOLOv5-6.2: [0;97m[49mDownloading Standard YOLO models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:25:48: ObjectDetectionYOLOv5-6.2: [0;39m[49mMoving contents of models-yolo5-pt.zip to assets...[0m[0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;97m[49mDownloading Custom YOLO models...[0m[0;35m[49mExpanding...[0m [0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;39m[49mMoving contents of custom-models-yolo5-pt.zip to custom-models...[0m[0;92m[49mdone.[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python packages for Object Detection (YOLOv5 6.2)[0m
2024-06-02 07:26:00: ObjectDetectionYOLOv5-6.2: [0;35m[49mInstalling GPU-enabled libraries: [0m[0;92m[49mIf available[0m
2024-06-02 07:26:01: ObjectDetectionYOLOv5-6.2: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;35m[49mPython packages will be specified by requirements.linux.txt[0m
2024-06-02 07:26:03: Client request 'detect' in queue 'objectdetection_queue' (#reqid defdc9a8-ee88-4389-8e04-0ad75cd660da)
2024-06-02 07:26:03: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pandas, a data analysis / data manipulation tool...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:04: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing CoreMLTools, for working with .mlmodel format models...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:05: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing OpenCV, the Open source Computer Vision library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:05: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:06: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing SciPy, a library for mathematics, science, and engineering...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:07: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing PyYAML, a library for reading configuration files...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:07: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Torch, for Tensor computation and Deep neural networks...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:08: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing TorchVision, for Computer Vision based AI...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:26:16: Client request 'detect' in queue 'objectdetection_queue' (#reqid a472c6a3-a230-46bb-b68b-cc12095941d9)
2024-06-02 07:26:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid 46857a83-cd48-4d28-bdc0-ce7b83d6ed52)
2024-06-02 07:26:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid 7af82754-343b-427f-badd-b1685e557ef5)
2024-06-02 07:27:10: Client request 'detect' in queue 'objectdetection_queue' (#reqid ee9b791b-568f-4486-957b-fca4aab392a4)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 41bc3ca4-d62f-4bff-9ad6-a11d9879ff87)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid bd85da5a-0c1a-4ba4-b2cd-cc6b60e5cbea)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 87ffce30-1d26-4581-add1-f8f70ca86130)
2024-06-02 07:27:11: Client request 'detect' in queue 'objectdetection_queue' (#reqid 16c8b2a3-df04-4ef1-abcd-78390c5c5b92)
2024-06-02 07:27:12: Client request 'detect' in queue 'objectdetection_queue' (#reqid a82a3c3b-b662-4c07-921f-ca2b079ac5d8)
2024-06-02 07:27:12: Client request 'detect' in queue 'objectdetection_queue' (#reqid 1e793dae-13a1-46e2-999f-2d7d637dbf96)
2024-06-02 07:27:13: Client request 'detect' in queue 'objectdetection_queue' (#reqid e784fe62-2547-4c11-8b3f-b6e87aea4f6b)
2024-06-02 07:27:13: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4c01c768-1cbd-4044-95a7-1775b8dc08b2)
2024-06-02 07:27:14: Client request 'detect' in queue 'objectdetection_queue' (#reqid b9dbd409-27e6-49c6-aebf-1b1dd8da38e7)
2024-06-02 07:27:14: Client request 'detect' in queue 'objectdetection_queue' (#reqid 46acd8a2-40e7-496b-80f7-5a7b0dbb4ad6)
2024-06-02 07:27:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 56dc363c-f0d8-4f35-8c84-0dee69b63034)
2024-06-02 07:27:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3a793ffe-1420-4ff7-951b-54b0f39f2455)
2024-06-02 07:27:21: Client request 'detect' in queue 'objectdetection_queue' (#reqid 62171111-a941-4902-bca6-9bdc3d35fb45)
2024-06-02 07:27:39: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Ultralytics YoloV5 package for object detection in images...[0m [0;35m[49m(✅ checked) [0m[0;92m[49mdone[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Seaborn, a data visualization library based on matplotlib...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;39m[49mInstalling Python packages for the CodeProject.AI Server SDK[0m
2024-06-02 07:27:40: ObjectDetectionYOLOv5-6.2: [0;39m[49mSearching for python3-pip...[0m[0;92m[49mAll good.[0m
2024-06-02 07:27:42: ObjectDetectionYOLOv5-6.2: [0;97m[49mEnsuring PIP compatibility...[0m [0;92m[49mdone[0m
2024-06-02 07:27:42: ObjectDetectionYOLOv5-6.2: [0;35m[49mPython packages will be specified by requirements.txt[0m
2024-06-02 07:27:43: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Pillow, a Python Image Library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:44: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Charset normalizer...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e)
2024-06-02 07:27:45: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing aiohttp, the Async IO HTTP library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3e85084a-851c-493c-937a-298430365ced)
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a)
2024-06-02 07:27:45: Client request 'detect' in queue 'objectdetection_queue' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817)
2024-06-02 07:27:46: Client request 'detect' in queue 'objectdetection_queue' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6)
2024-06-02 07:27:46: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing aiofiles, the Async IO Files library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:46: Client request 'detect' in queue 'objectdetection_queue' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9)
2024-06-02 07:27:47: Client request 'detect' in queue 'objectdetection_queue' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996)
2024-06-02 07:27:47: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing py-cpuinfo to allow us to query CPU info...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:47: Client request 'detect' in queue 'objectdetection_queue' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81)
2024-06-02 07:27:48: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881)
2024-06-02 07:27:48: ObjectDetectionYOLOv5-6.2: [0;97m[49m - Installing Requests, the HTTP library...[0m[0;92m[49mAlready installed[0m
2024-06-02 07:27:48: ObjectDetectionYOLOv5-6.2: [0;39m[49mScanning modulesettings for downloadable models...[0m[0;37m[49mNo models specified[0m
2024-06-02 07:27:48: Client request 'detect' in queue 'objectdetection_queue' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be)
2024-06-02 07:27:49: Client request 'detect' in queue 'objectdetection_queue' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136)
2024-06-02 07:27:49: Client request 'detect' in queue 'objectdetection_queue' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58)
2024-06-02 07:27:50: Client request 'detect' in queue 'objectdetection_queue' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c)
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: Fusing layers...
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:27:53: ObjectDetectionYOLOv5-6.2: Adding AutoShape...
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mSelf test: [0m[0;92m[49mSelf-test passed[0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mModule setup time 00:02:26[0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;97m[42m Setup complete [0m
2024-06-02 07:27:54: ObjectDetectionYOLOv5-6.2: [0;39m[49mTotal setup time 00:02:27[0m
2024-06-02 07:27:54: Module ObjectDetectionYOLOv5-6.2 installed successfully.
2024-06-02 07:27:54: Installer exited with code 0
2024-06-02 07:27:54: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:27:54:
2024-06-02 07:27:54: Attempting to start ObjectDetectionYOLOv5-6.2 with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:27:54: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr...jectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:27:54:
2024-06-02 07:27:54: ** Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
2024-06-02 07:27:54: ** Valid: True
2024-06-02 07:27:54: ** Module Path: <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:54: ** Module Location: Internal
2024-06-02 07:27:54: ** AutoStart: True
2024-06-02 07:27:54: ** Queue: objectdetection_queue
2024-06-02 07:27:54: ** Runtime: python3.8
2024-06-02 07:27:54: ** Runtime Location: Shared
2024-06-02 07:27:54: ** FilePath: detect_adapter.py
2024-06-02 07:27:54: ** Start pause: 1 sec
2024-06-02 07:27:54: ** Parallelism: 0
2024-06-02 07:27:54: ** LogVerbosity:
2024-06-02 07:27:54: ** Platforms: all,!raspberrypi,!jetson
2024-06-02 07:27:54: ** GPU Libraries: installed if available
2024-06-02 07:27:54: ** GPU: use if supported
2024-06-02 07:27:54: ** Accelerator:
2024-06-02 07:27:54: ** Half Precision: enable
2024-06-02 07:27:54: ** Environment Variables
2024-06-02 07:27:54: ** APPDIR = <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:54: ** CUSTOM_MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/custom-models
2024-06-02 07:27:54: ** MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:27:54: ** MODEL_SIZE = Medium
2024-06-02 07:27:54: ** USE_CUDA = True
2024-06-02 07:27:54: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:27:54: ** YOLOv5_VERBOSE = false
2024-06-02 07:27:54:
2024-06-02 07:27:54: Started Object Detection (YOLOv5 6.2) module
2024-06-02 07:27:55: Module ObjectDetectionYOLOv5-6.2 started successfully.
2024-06-02 07:27:58: detect_adapter.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:27:58: detect_adapter.py: MODEL_SIZE: medium
2024-06-02 07:27:58: detect_adapter.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:27:58: detect_adapter.py: Running init for Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid defdc9a8-ee88-4389-8e04-0ad75cd660da)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a472c6a3-a230-46bb-b68b-cc12095941d9)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 7af82754-343b-427f-badd-b1685e557ef5)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 46857a83-cd48-4d28-bdc0-ce7b83d6ed52)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid ee9b791b-568f-4486-957b-fca4aab392a4)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 41bc3ca4-d62f-4bff-9ad6-a11d9879ff87)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 16c8b2a3-df04-4ef1-abcd-78390c5c5b92)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 87ffce30-1d26-4581-add1-f8f70ca86130)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 1e793dae-13a1-46e2-999f-2d7d637dbf96)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid e784fe62-2547-4c11-8b3f-b6e87aea4f6b)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 4c01c768-1cbd-4044-95a7-1775b8dc08b2)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid b9dbd409-27e6-49c6-aebf-1b1dd8da38e7)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 46acd8a2-40e7-496b-80f7-5a7b0dbb4ad6)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 56dc363c-f0d8-4f35-8c84-0dee69b63034)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3a793ffe-1420-4ff7-951b-54b0f39f2455)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 62171111-a941-4902-bca6-9bdc3d35fb45)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3e85084a-851c-493c-937a-298430365ced)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid bd85da5a-0c1a-4ba4-b2cd-cc6b60e5cbea)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a82a3c3b-b662-4c07-921f-ca2b079ac5d8)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996)
2024-06-02 07:27:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:58: detect_adapter.py: Fusing layers...
2024-06-02 07:27:58: detect_adapter.py: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:27:58: detect_adapter.py: Adding AutoShape...
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Model Path is /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets/yolov5m.pt in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid a2f76f8e-5736-4b8e-a4d3-dcc66979fc0e) ['Found car, car'] took 867ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid f0ca6f5b-320f-40e9-bfd6-f39214910817) ['Found car, car'] took 913ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3153611a-a27b-45aa-a356-56a67b57287a) ['Found car, car, car'] took 934ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3e85084a-851c-493c-937a-298430365ced) ['Found car, car'] took 967ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid f82715a1-9835-4d33-bc5f-122883206cc9) ['Found car, car'] took 633ms
2024-06-02 07:27:59: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 80619f34-eb34-472b-bd9d-5500ffa11b81) ['Found car'] took 676ms
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid b129ed66-a918-409e-9938-6d2bc5d1f996) ['Found car'] took 606ms
2024-06-02 07:27:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid c5cff0a7-0d6b-4341-9ea8-4af1fc5cd7e6) ['Found car, car'] took 649ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid c967f0a3-da52-40cb-97f8-fd58c86b51be) ['Found car'] took 673ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 65a0a094-cef8-40f7-b15f-41b2095f2136) ['Found car'] took 664ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 4348833e-9708-4b33-a3a9-ea1ef75d0881) ['Found car'] took 710ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 2f007ca9-4d6d-4719-9fb8-4693be21bf58) ['Found car'] took 710ms
2024-06-02 07:28:00: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 8dbdb91e-9116-4cd4-887c-a5c2bb8fac6c) ['Found car'] took 290ms
2024-06-02 07:28:11: Update ObjectDetectionYOLOv5-6.2. Setting AutoStart=false
2024-06-02 07:28:11: *** Stopping Object Detection (YOLOv5 6.2)
2024-06-02 07:28:11: Sending shutdown request to pt_main_thread/ObjectDetectionYOLOv5-6.2
2024-06-02 07:28:11: Client request 'Quit' in queue 'objectdetection_queue' (#reqid 889aace6-c64f-41ec-840b-f152ee0a9b71)
2024-06-02 07:28:11: Request 'Quit' dequeued from 'objectdetection_queue' (#reqid 889aace6-c64f-41ec-840b-f152ee0a9b71)
2024-06-02 07:28:11: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'Quit' in Object Detection (YOLOv5 6.2)
2024-06-02 07:28:14: Update FaceProcessing. Setting AutoStart=false
2024-06-02 07:28:14: *** Stopping Face Processing
2024-06-02 07:28:14: Sending shutdown request to pt_main_thread/FaceProcessing
2024-06-02 07:28:14: Client request 'Quit' in queue 'faceprocessing_queue' (#reqid b07211a2-25ba-4da9-85df-18d99d141738)
2024-06-02 07:28:14: Request 'Quit' dequeued from 'faceprocessing_queue' (#reqid b07211a2-25ba-4da9-85df-18d99d141738)
2024-06-02 07:28:14: Face Processing: Retrieved faceprocessing_queue command 'Quit' in Face Processing
2024-06-02 07:28:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653)
2024-06-02 07:28:15: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653)
2024-06-02 07:28:15: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 3717b77c-7e97-4d55-9fef-9df0b0faa653) ['Found car'] took 323ms
2024-06-02 07:28:16: detect_adapter.py: Object Detection (YOLOv5 6.2) started.
2024-06-02 07:28:16: detect_adapter.py: Inference processing will occur on device 'CPU'
2024-06-02 07:28:16: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:28:17: ** Module ObjectDetectionYOLOv5-6.2 has shutdown
2024-06-02 07:28:18: face.py: Face Processing started.
2024-06-02 07:28:19: ** Module FaceProcessing has shutdown
2024-06-02 07:28:34: Client request 'detect' in queue 'objectdetection_queue' (#reqid bf32f212-9f73-450e-8435-f85614498088)
2024-06-02 07:28:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid c46d7d95-5930-41cb-b7d1-7e035e0db5a6)
2024-06-02 07:28:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid dc9f51d1-d2f4-49b4-ac87-1db40808877d)
2024-06-02 07:28:44: ObjectDetectionYOLOv5-6.2 went quietly
2024-06-02 07:28:47: FaceProcessing went quietly
2024-06-02 07:28:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid 24c3a277-f4f6-4c57-8a95-c88fbcfd7d94)
2024-06-02 07:29:15: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4639be16-b91c-4c35-b72a-84730209ef39)
2024-06-02 07:29:20: Client request 'detect' in queue 'objectdetection_queue' (#reqid e1c2929a-8fc8-4cdc-9175-4bfddab9cf3c)
2024-06-02 07:29:50: ModuleRunner Stop
2024-06-02 07:29:50: ObjectDetectionYOLOv5-6.2 doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: ObjectDetectionYOLOv5Net doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: FaceProcessing doesn't appear in the Process list, so can't stop it.
2024-06-02 07:29:50: ModuleRunner Stopped
2024-06-02 07:29:51: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:29:51: ** System: Linux
2024-06-02 07:29:51: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:29:51: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:29:51: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:29:51: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:29:51: ** System RAM: 31 GiB
2024-06-02 07:29:51: ** Platform: Linux
2024-06-02 07:29:51: ** BuildConfig: Release
2024-06-02 07:29:51: ** Execution Env: Native
2024-06-02 07:29:51: ** Runtime Env: Production
2024-06-02 07:29:51: ** Runtimes installed:
2024-06-02 07:29:51: ** .NET runtime: 7.0.19
2024-06-02 07:29:51: ** .NET SDK: 7.0.119
2024-06-02 07:29:51: ** Default Python: 3.10.12
2024-06-02 07:29:51: ** Go: Not found
2024-06-02 07:29:51: ** NodeJS: Not found
2024-06-02 07:29:51: ** Rust: Not found
2024-06-02 07:29:51: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:29:51: Video adapter info:
2024-06-02 07:29:51: HD Graphics 530 (rev 06):
2024-06-02 07:29:51: Driver Version
2024-06-02 07:29:51: Video Processor
2024-06-02 07:29:51: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:29:51: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:29:51: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:29:51: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:29:51: EXTERNAL_MODULES_PATH =
2024-06-02 07:29:51: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:29:51: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:29:51: Data Dir = /etc/codeproject/ai
2024-06-02 07:29:51: ** Server version: 2.6.5
2024-06-02 07:29:51: ModuleRunner Start
2024-06-02 07:29:51: Starting Background AI Modules
2024-06-02 07:29:54: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:29:54:
2024-06-02 07:29:54: Attempting to start ObjectDetectionYOLOv5-6.2 with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:29:54: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr...jectDetectionYOLOv5-6.2/detect_adapter.py"
2024-06-02 07:29:54:
2024-06-02 07:29:54: ** Module 'Object Detection (YOLOv5 6.2)' 1.9.1 (ID: ObjectDetectionYOLOv5-6.2)
2024-06-02 07:29:54: ** Valid: True
2024-06-02 07:29:54: ** Module Path: <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:54: ** Module Location: Internal
2024-06-02 07:29:54: ** AutoStart: True
2024-06-02 07:29:54: ** Queue: objectdetection_queue
2024-06-02 07:29:54: ** Runtime: python3.8
2024-06-02 07:29:54: ** Runtime Location: Shared
2024-06-02 07:29:54: ** FilePath: detect_adapter.py
2024-06-02 07:29:54: ** Start pause: 1 sec
2024-06-02 07:29:54: ** Parallelism: 0
2024-06-02 07:29:54: ** LogVerbosity:
2024-06-02 07:29:54: ** Platforms: all,!raspberrypi,!jetson
2024-06-02 07:29:54: ** GPU Libraries: installed if available
2024-06-02 07:29:54: ** GPU: use if supported
2024-06-02 07:29:54: ** Accelerator:
2024-06-02 07:29:54: ** Half Precision: enable
2024-06-02 07:29:54: ** Environment Variables
2024-06-02 07:29:54: ** APPDIR = <root>/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:54: ** CUSTOM_MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/custom-models
2024-06-02 07:29:54: ** MODELS_DIR = <root>/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:29:54: ** MODEL_SIZE = Medium
2024-06-02 07:29:54: ** USE_CUDA = True
2024-06-02 07:29:54: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:29:54: ** YOLOv5_VERBOSE = false
2024-06-02 07:29:54:
2024-06-02 07:29:54: Started Object Detection (YOLOv5 6.2) module
2024-06-02 07:29:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1)
2024-06-02 07:29:55: Running module using: /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3
2024-06-02 07:29:55:
2024-06-02 07:29:55: Attempting to start FaceProcessing with /usr/bin/codeproject.ai-server-2.6.5/runtimes/bin/linux/python38/venv/bin/python3 "/usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:29:55: Starting /usr...untimes/bin/linux/python38/venv/bin/python3 "/usr.../FaceProcessing/intelligencelayer/face.py"
2024-06-02 07:29:55:
2024-06-02 07:29:55: ** Module 'Face Processing' 1.10.2 (ID: FaceProcessing)
2024-06-02 07:29:55: ** Valid: True
2024-06-02 07:29:55: ** Module Path: <root>/modules/FaceProcessing
2024-06-02 07:29:55: ** Module Location: Internal
2024-06-02 07:29:55: ** AutoStart: True
2024-06-02 07:29:55: ** Queue: faceprocessing_queue
2024-06-02 07:29:55: ** Runtime: python3.8
2024-06-02 07:29:55: ** Runtime Location: Shared
2024-06-02 07:29:55: ** FilePath: intelligencelayer/face.py
2024-06-02 07:29:55: ** Start pause: 3 sec
2024-06-02 07:29:55: ** Parallelism: 0
2024-06-02 07:29:55: ** LogVerbosity:
2024-06-02 07:29:55: ** Platforms: all,!jetson
2024-06-02 07:29:55: ** GPU Libraries: installed if available
2024-06-02 07:29:55: ** GPU: use if supported
2024-06-02 07:29:55: ** Accelerator:
2024-06-02 07:29:55: ** Half Precision: enable
2024-06-02 07:29:55: ** Environment Variables
2024-06-02 07:29:55: ** APPDIR = <root>/modules/FaceProcessing/intelligencelayer
2024-06-02 07:29:55: ** DATA_DIR = /etc/codeproject/ai
2024-06-02 07:29:55: ** MODE = MEDIUM
2024-06-02 07:29:55: ** MODELS_DIR = <root>/modules/FaceProcessing/assets
2024-06-02 07:29:55: ** PROFILE = desktop_gpu
2024-06-02 07:29:55: ** USE_CUDA = True
2024-06-02 07:29:55: ** YOLOv5_AUTOINSTALL = false
2024-06-02 07:29:55: ** YOLOv5_VERBOSE = false
2024-06-02 07:29:55:
2024-06-02 07:29:55: Started Face Processing module
2024-06-02 07:29:56: Current Version is 2.6.5
2024-06-02 07:29:56: Server: This is the latest version
2024-06-02 07:29:58: detect_adapter.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2
2024-06-02 07:29:58: detect_adapter.py: MODEL_SIZE: medium
2024-06-02 07:29:58: detect_adapter.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets
2024-06-02 07:29:58: detect_adapter.py: Running init for Object Detection (YOLOv5 6.2)
2024-06-02 07:29:58: Request 'detect' dequeued from 'objectdetection_queue' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1)
2024-06-02 07:29:58: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'detect' in Object Detection (YOLOv5 6.2)
2024-06-02 07:29:58: detect_adapter.py: Fusing layers...
2024-06-02 07:29:59: detect_adapter.py: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
2024-06-02 07:29:59: detect_adapter.py: Adding AutoShape...
2024-06-02 07:29:59: Object Detection (YOLOv5 6.2): Model Path is /usr/bin/codeproject.ai-server-2.6.5/modules/ObjectDetectionYOLOv5-6.2/assets/yolov5m.pt in Object Detection (YOLOv5 6.2)
2024-06-02 07:29:59: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid a13a2c89-c0b5-4df9-9523-7493c60f53c1) ['Found car'] took 525ms
2024-06-02 07:29:59: face.py: Vision AI services setup: Retrieving environment variables...
2024-06-02 07:29:59: face.py: APPDIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/intelligencelayer
2024-06-02 07:29:59: face.py: PROFILE: desktop_cpu
2024-06-02 07:29:59: face.py: USE_CUDA: False
2024-06-02 07:29:59: face.py: DATA_DIR: /etc/codeproject/ai
2024-06-02 07:29:59: face.py: MODELS_DIR: /usr/bin/codeproject.ai-server-2.6.5/modules/FaceProcessing/assets
2024-06-02 07:29:59: face.py: MODE: MEDIUM
2024-06-02 07:29:59: face.py: Running init for Face Processing
2024-06-02 07:30:30: Update ObjectDetectionYOLOv5-6.2. Setting AutoStart=false
2024-06-02 07:30:30: *** Stopping Object Detection (YOLOv5 6.2)
2024-06-02 07:30:30: Sending shutdown request to pt_main_thread/ObjectDetectionYOLOv5-6.2
2024-06-02 07:30:30: Client request 'Quit' in queue 'objectdetection_queue' (#reqid 18a3c4ac-f272-4eab-b10b-5b302eab88d7)
2024-06-02 07:30:30: Request 'Quit' dequeued from 'objectdetection_queue' (#reqid 18a3c4ac-f272-4eab-b10b-5b302eab88d7)
2024-06-02 07:30:30: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command 'Quit' in Object Detection (YOLOv5 6.2)
2024-06-02 07:30:35: Client request 'detect' in queue 'objectdetection_queue' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e)
2024-06-02 07:30:35: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e)
2024-06-02 07:30:36: Client request 'detect' in queue 'objectdetection_queue' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98)
2024-06-02 07:30:36: Request 'detect' dequeued from 'objectdetection_queue' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98)
2024-06-02 07:30:36: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 9e3b2868-6162-4504-895c-3a2addd3044e) ['Found dining table, bench, potted plant...'] took 270ms
2024-06-02 07:30:36: Response rec'd from Object Detection (YOLOv5 6.2) command 'detect' (#reqid 95f73b00-7431-4156-9e76-c6cc319c9b98) ['No objects found'] took 271ms
2024-06-02 07:30:46: detect_adapter.py: Object Detection (YOLOv5 6.2) started.
2024-06-02 07:30:46: detect_adapter.py: Inference processing will occur on device 'CPU'
2024-06-02 07:30:46: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:30:46: detect_adapter.py: Retrieved objectdetection_queue command 'detect'
2024-06-02 07:30:47: ** Module ObjectDetectionYOLOv5-6.2 has shutdown
2024-06-02 07:30:54: Client request 'detect' in queue 'objectdetection_queue' (#reqid c0d031fc-a881-40a9-ace4-74d071d64885)
2024-06-02 07:30:55: Update FaceProcessing. Setting AutoStart=false
2024-06-02 07:30:55: *** Stopping Face Processing
2024-06-02 07:30:55: Sending shutdown request to pt_main_thread/FaceProcessing
2024-06-02 07:30:55: Client request 'Quit' in queue 'faceprocessing_queue' (#reqid f3d8081d-8370-4cd0-8cd0-19d90dd9f5fe)
2024-06-02 07:30:55: Request 'Quit' dequeued from 'faceprocessing_queue' (#reqid f3d8081d-8370-4cd0-8cd0-19d90dd9f5fe)
2024-06-02 07:30:55: Face Processing: Retrieved faceprocessing_queue command 'Quit' in Face Processing
2024-06-02 07:31:02: face.py: Face Processing started.
2024-06-02 07:31:03: ** Module FaceProcessing has shutdown
2024-06-02 07:31:03: ObjectDetectionYOLOv5-6.2 went quietly
2024-06-02 07:31:11: ObjectDetectionYOLOv5Net doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:16: Client request 'detect' in queue 'objectdetection_queue' (#reqid 4a315cf3-ea72-48aa-b095-5a9618cfe9c7)
2024-06-02 07:31:18: ObjectDetectionYOLOv5-6.2 doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:19: Client request 'detect' in queue 'objectdetection_queue' (#reqid 15c2fe28-2ed0-4b61-a879-60f429d5a499)
2024-06-02 07:31:28: FaceProcessing went quietly
2024-06-02 07:31:34: FaceProcessing doesn't appear in the Process list, so can't stop it.
2024-06-02 07:31:37: Client request 'detect' in queue 'objectdetection_queue' (#reqid e2257dcd-5bd4-42b2-847e-036be206b948)
2024-06-02 07:31:43: Client request 'detect' in queue 'objectdetection_queue' (#reqid f478e51b-168c-4059-bd42-cd8d5bb51f8b)
2024-06-02 07:31:53: Client request 'detect' in queue 'objectdetection_queue' (#reqid 9870d00f-2ea1-4459-bf57-62c1f7a2e225)
2024-06-02 07:31:58: Client request 'detect' in queue 'objectdetection_queue' (#reqid cc510725-9cd5-44d7-96d6-a28f9aecb9bd)
2024-06-02 07:32:28: ModuleRunner Stop
2024-06-02 07:32:28: ModuleRunner Stopped
2024-06-02 07:32:28: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:32:28: ** System: Linux
2024-06-02 07:32:28: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:32:28: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:32:28: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:32:28: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:32:28: ** System RAM: 31 GiB
2024-06-02 07:32:28: ** Platform: Linux
2024-06-02 07:32:28: ** BuildConfig: Release
2024-06-02 07:32:28: ** Execution Env: Native
2024-06-02 07:32:28: ** Runtime Env: Production
2024-06-02 07:32:28: ** Runtimes installed:
2024-06-02 07:32:28: ** .NET runtime: 7.0.19
2024-06-02 07:32:28: ** .NET SDK: 7.0.119
2024-06-02 07:32:28: ** Default Python: 3.10.12
2024-06-02 07:32:28: ** Go: Not found
2024-06-02 07:32:28: ** NodeJS: Not found
2024-06-02 07:32:28: ** Rust: Not found
2024-06-02 07:32:28: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:32:28: Video adapter info:
2024-06-02 07:32:28: HD Graphics 530 (rev 06):
2024-06-02 07:32:28: Driver Version
2024-06-02 07:32:28: Video Processor
2024-06-02 07:32:28: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:32:28: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:32:28: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:32:28: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:32:28: EXTERNAL_MODULES_PATH =
2024-06-02 07:32:28: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:32:28: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:32:28: Data Dir = /etc/codeproject/ai
2024-06-02 07:32:28: ** Server version: 2.6.5
2024-06-02 07:32:28: ModuleRunner Start
2024-06-02 07:32:28: Starting Background AI Modules
2024-06-02 07:32:34: Current Version is 2.6.5
2024-06-02 07:32:34: Server: This is the latest version
2024-06-02 07:33:32: ModuleRunner Stop
2024-06-02 07:33:32: ModuleRunner Stopped
2024-06-02 07:38:03: Settings file: /usr/bin/codeproject.ai-server-2.6.5/server/installmodules.json exists: False
2024-06-02 07:38:03: ** System: Linux
2024-06-02 07:38:03: ** Operating System: Linux (Ubuntu 22.04)
2024-06-02 07:38:03: ** CPUs: Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz (Intel)
2024-06-02 07:38:03: ** 1 CPU x 4 cores. 8 logical processors (x64)
2024-06-02 07:38:03: ** GPU (Primary): HD Graphics 530 (rev 06) (Intel Corporation)
2024-06-02 07:38:03: ** System RAM: 31 GiB
2024-06-02 07:38:03: ** Platform: Linux
2024-06-02 07:38:03: ** BuildConfig: Release
2024-06-02 07:38:03: ** Execution Env: Native
2024-06-02 07:38:03: ** Runtime Env: Production
2024-06-02 07:38:03: ** Runtimes installed:
2024-06-02 07:38:03: ** .NET runtime: 7.0.19
2024-06-02 07:38:03: ** .NET SDK: 7.0.119
2024-06-02 07:38:03: ** Default Python: 3.10.12
2024-06-02 07:38:03: ** Go: Not found
2024-06-02 07:38:03: ** NodeJS: Not found
2024-06-02 07:38:03: ** Rust: Not found
2024-06-02 07:38:03: ** App DataDir: /etc/codeproject/ai
2024-06-02 07:38:03: Video adapter info:
2024-06-02 07:38:03: HD Graphics 530 (rev 06):
2024-06-02 07:38:03: Driver Version
2024-06-02 07:38:03: Video Processor
2024-06-02 07:38:03: *** STARTING CODEPROJECT.AI SERVER
2024-06-02 07:38:03: RUNTIMES_PATH = /usr/bin/codeproject.ai-server-2.6.5/runtimes
2024-06-02 07:38:03: PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/preinstalled-modules
2024-06-02 07:38:03: DEMO_MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/src/demos/modules
2024-06-02 07:38:03: EXTERNAL_MODULES_PATH =
2024-06-02 07:38:03: MODULES_PATH = /usr/bin/codeproject.ai-server-2.6.5/modules
2024-06-02 07:38:03: PYTHON_PATH = /bin/linux/%PYTHON_NAME%/venv/bin/python3
2024-06-02 07:38:03: Data Dir = /etc/codeproject/ai
2024-06-02 07:38:04: ** Server version: 2.6.5
2024-06-02 07:38:04: ModuleRunner Start
2024-06-02 07:38:04: Starting Background AI Modules
2024-06-02 07:38:09: Current Version is 2.6.5
2024-06-02 07:38:09: Server: This is the latest version
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This was due to the docker container I had been testing but quit due to error 500's. I rebooted the host and it started up the CPAI docker container w/ host networking like it was supposed to. Deleting the container immediately resolved the 404 issues. I had 32168 on one instance and 32169 on another - only reason I think everything was acting "ok".
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Q1. Can this be run on Windows 7 SP1? If unable that's too bad. (many others like "LocalAI" never answer this question)
Q2. What is the minimum reqirement to use this for text generation/chat? How much memory do I need and/or GPU?
Q3. Can I use this without internet (offline); does this really work without it? I'm planning to download the installer and install offline.
Q4. Does your AI can process non-English language? Can I teach it based on my text data?
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1. Probably not. [.NET 7 is not supported in Windows 7](https://github.com/dotnet/core/issues/7556). Having said that, recompiling everything in .NET 6 should work, but you'd have to ensure WMIC and Powershell were installed too.
Windows 7 is simply too old for us to be supporting, but technically the code *should* be fine.
2. What is the minimum requirement to use this for text generation/chat? How much memory do I need and/or GPU?
It all works on CPUs, it's just slow. The more RAM the better. I run 16Gb systems on all my machines (except RPi/Jetson) and generative AI works fine on these. Even 8Gb should be good, but I would no go lower.
3. Installation needs to happen online so it can download the libraries needed for your particular Hardware / OS combo. Once it's installed it's fully offline.
4. Does your AI can process non-English language? Can I teach it based on my text data?
Whatever GGUF format LLama model you can find will work. Training yourself is a task beyond what we can help you with
cheers
Chris Maunder
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My primary host is running UnRaid 6.12.9 with a CPAI docker container and a Windows VM running BlueIris. I have another Linux Mint machine on the network running CPAI with no docker container. Both instances of CPAI can see each other, sort of.
If I set Blue Iris to target the remote Linux machine, everything works fine, excess requests get passed back to the Unraid machine, processed, sent back. Everything is happy.
But if I set Blue Iris to target the docker running on the same machine as itself, it still sees the other Mint machine and tries to send overflow to it, but times out with no response.
The status of the Unraid server from the Mint remote wavers from active true to active false every few seconds.
I just upgraded to CPAI 2.6.5 but had the same behaviour under 2.6.2. UDP ports are open to the docker container.
I want to keep the docker on the Unraid as the primary instance because the remote mint machine is used frequently and is prone to going down for various reasons, and blue iris is unable to automatically switch servers.
From the Unraid Server:
Current Server mesh status
UnraidServer
Hostname: 172.17.0.8
System: Docker (Linux) Tesla P4
Platform: Docker
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
mintMachine
Routes Available: (16366 processed)
vision/custom 43.7ms (avg process time), 15756 processed
vision/custom/list 0ms (avg process time), 0 processed
vision/detection 0ms (avg process time), 0 processed
vision/face 20ms (avg process time), 610 processed
vision/face/match 0ms (avg process time), 0 processed
Remote Servers in mesh: 1
mintMachine
Hostname: mintMachine
System: Linux (Linux) NVIDIA GeForce GTX 1660 Ti with Max-Q Design
Platform: Linux
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
UnraidServer
Routes Available: (3 processed)
vision/custom 3000ms (avg round trip), 2 requests forwarded
vision/custom/list 0ms (avg round trip), 0 requests forwarded
vision/detection 0ms (avg round trip), 0 requests forwarded
vision/face 0ms (avg round trip), 1 requests forwarded
vision/face/match 0ms (avg round trip), 0 requests forwarded
From the Linux Mint remote machine:
Current Server mesh status
mintMachine
Hostname: mintMachine
System: Linux (Linux) NVIDIA GeForce GTX 1660 Ti with Max-Q Design
Platform: Linux
Active: true
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
UnraidServer
Routes Available: (0 processed)
vision/custom 0ms (avg process time), 0 processed
vision/custom/list 0ms (avg process time), 0 processed
vision/detection 0ms (avg process time), 0 processed
vision/face 0ms (avg process time), 0 processed
vision/face/match 0ms (avg process time), 0 processed
Remote Servers in mesh: 1
UnraidServer
Hostname: 192.168.1.101
System: Docker (Linux) Tesla P4
Platform: Docker
Active: false
Forwarding Requests: true
Accepting Requests: true
Visible Servers:
mintMachine
Routes Available: (0 processed)
vision/custom 0ms (avg round trip), 0 requests forwarded
vision/custom/list 0ms (avg round trip), 0 requests forwarded
vision/detection 0ms (avg round trip), 0 requests forwarded
vision/face 0ms (avg round trip), 0 requests forwarded
vision/face/match 0ms (avg round trip), 0 requests forwarded
modified 31-May-24 14:55pm.
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I think I might have got this licked.
I added the IP address of the Mint remote machine to the known mesh servers in appdata/codeprojectai/data/serversettings.json on the Unraid server
"KnownMeshHostnames": [ "192.168.1.103" ],
I already had it in the appsettings.json on the Mint machine pointing it at the Unraid server, so not sure if you need both pointing at each other, but it seems to be working.
Hopefully this helps out someone having the same issues as me!
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Actually I'm still having some issues.
I haven't been able narrow down exactly when it happens, but it seems like after either end reboots the mesh is broken and it starts trying to look for the hostname instead of the IP address, which for whatever reason doesn't make it through the docker network interface, so you have to disable the mesh on the satellite, reboot the docker, then restart the mesh on the satellite again. Nothing relevant really comes up in the logs to give any insight on why this is happening.
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I am attempting to run image codeproject/ai-server:cuda12_2 (current) under Docker running on Fedora 39. The server has abundant resources with 256 GB of RAM. As far as I know, Docker is not imposing memory limits. When I start the container, codeproject.ai starts normally and without errors. However, it crashes after 5 or 6 minutes with "out of memory","codeproject excited with code 139." The system log shows "systemd-coredump[1460173]: Process 1451539 (CodeProject.AI.) of user 0 dumped core.#012#012Stack trace of thread 882:#012#0 0x00007fbf944bc898 n/a (/usr/lib/x86_64-linux-gnu/libc.so.6 + 0x28898)#012#1 0x00007fafd2a00640 n/a (n/a + 0x0)#012ELF object binary architecture: AMD x86-64."
The container crashes whether or not it has been accessed, and whether or not it has claimed GPU resources. As long as it is running, it readily accepts images and performs comparisons, using about 1GB of GPU memory and around 3 GB of RAM. However, it still crashes.
I have searched and can't find anyone else with this problem, suggesting that it is something in my environment, but I can't figure out what it could be. I would appreciate any ideas.
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Thanks very much for your report. Could you please share your System Info tab from your CodeProject.AI Server dashboard?
Thanks,
Sean Ewington
CodeProject
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Server version: 2.6.5
System: Docker (ai-server)
Operating System: Linux (Ubuntu 22.04)
CPUs: AMD EPYC 7262 8-Core Processor (AMD)
2 CPUs x 8 cores. 16 logical processors (x64)
GPU (Primary): NVIDIA GeForce RTX 4060 (8 GiB) (NVIDIA)
Driver: 550.78, CUDA: 12.4 (up to: 12.4), Compute: 8.9, cuDNN: 8.9.6
System RAM: 252 GiB
Platform: Linux
BuildConfig: Release
Execution Env: Docker
Runtime Env: Production
Runtimes installed:
.NET runtime: 7.0.19
.NET SDK: Not found
Default Python: 3.10.12
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
System GPU info:
GPU 3D Usage 2%
GPU RAM Usage 1.9 GiB
Global Environment variables:
CPAI_APPROOTPATH = <root>
CPAI_PORT = 32168
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This one's beyond my pay grade. If you've configured Docker to have this much RAM it should be lavishing thanks on you, not core dumping. That's just inconsiderate.
I did see mention of hosting system core dumps when a Docker container hit it's assigned RAM max, but that doesn't seem to be the case here.
I wonder if it's not an out-of-memory issue, but rather a memory access / memory corruption issue?
cheers
Chris Maunder
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Thanks for thinking about this. I also think it's a memory access issue, but why isn't everybody using this Docker container getting it? Docker provides such a consistent environment that it's really hard to figure out why it's only my Docker container that doesn't work. The amount of system resources is probably the biggest variable not controlled by the container, but as you point out, there is no shortage. I have watched the memory consumption using "docker stats" once a second, and the memory consumption does not gradually increase over the 5-10 minute lifetime of the container as you might expect it to with a memory leak.
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Well, turns out it's probably a memory issue and not a memory access issue. Based on a whim and partly on a "docker out of memory" thread unrelated to ai-server, I limited the file handles in the docker-compose file as follows:
ulimits:
nofile:
soft: 65536
hard: 65536
and that appears to have resolved or at least mitigated the issue. To be clear, the number of files was unlimited prior to my change. The ai-server has been up more than 4 hours, which is 3 hours 50 minutes longer than it has ever run before. It is happily matching faces using only 3.1 GB of RAM. I have not yet tried to prove that the number of file handles increases until it consumes all of the memory, but I'm wondering if ai-server spends its free time grabbing file handles as fast as it can when they are unlimited.
It's still very curious that nobody else has reported this. Maybe it has to do with Fedora, but it seems to me that Docker running under Fedora should look the same as Docker running under any other distribution from inside the container.
I have some time to do further troubleshooting in the next few days.
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I've got some answers.
Codeproject.ai-server does, in fact, continuously open new file handles at the rate of about 120/minute on my system, up to the limit if one exists. If there is no limit, it keeps going until it consumes all system memory. The reason Fedora is different (I think) is because Fedora made a decision not to impose limits on Docker itself due to the overhead of enforcing those limits, and suggests that limits be established on individual containers using cgroups instead. This "out of memory" error would inevitably occur on any distribution not enforcing file limits on docker by default. That may only be Fedora and Redhat at this time.
I reduced the file open limit to 1024 on ai-server and observed it for a while. It gets up to the limit, then bounces back down to about 440 files and starts over. It doesn't crash. The file handle that increases is a FIFO.
This is definitely a bug that needs to be addressed.
modified 3 days ago.
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We had an issue that eventually lead to many file handles / watchers being set at startup. There's a check for this at startup and a warning issued, but as to it creating a bucket load more each second, that's bizarre. It would be handy to know which process is adding the handles: a module or the server itself.
Thanks,
Sean Ewington
CodeProject
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Quote: futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=1671, si_uid=0, si_status=0, si_utime=0, si_stime=0} ---
write(62, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 202
futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=1675, si_uid=0, si_status=0, si_utime=0, si_stime=0} ---
write(62, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 202
futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=1677, si_uid=0, si_status=0, si_utime=0, si_stime=0} ---
write(62, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 202
futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=1680, si_uid=0, si_status=0, si_utime=0, si_stime=0} ---
write(62, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 202
futex(0x55d234f6aba4, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=1682, si_uid=0, si_status=0, si_utime=0, si_stime=0} ---
write(62, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 202
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Could you do me a favour please? The process id is given by si_pid (eg si_pid=1671). Can you do this for a process Id you've recently spotted?
- Identify the Process with PID 1671:
ps -p 1671 -o comm=
It should spit out the app name
- Identify the Parent Process:
ps -p 1671 -o ppid=
eg output will be '1234'
- Identify the Parent Process Name:
ps -p 1234 -o comm=
It should spit out the parent app name
- List Open Files for Parent Process:
lsof -p 1234
cheers
Chris Maunder
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Chris, I already tried to figure out what was starting all those processes, but they don't last long enough. I have never seen one of the additional processes even with a ps aux. However, there may be another way to answer the question. I had already turned off all of the modules except Face Processing, so I turned that one off too. With no modules active, the FIFO file handles continue to accumulate. For what it's worth, lsof attributes all of the FIFOs to CodeProject.
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I am more than happy to help troubleshoot in any way that I can. I suspect that any server, though, running from the same Docker image, is doing the same thing. I created a completely independent RPI instance using an RPI 4 with 8GB RAM and newly downloaded image (Linux pi8-rpi 6.6.31+rpt-rpi-v8 #1 SMP PREEMPT Debian 1:6.6.31-1+rpt1 (2024-05-29) aarch64 GNU/Linux). I added Docker and downloaded codeproject/ai-server:rpi64 then set up the docker-compose file exactly like the example on your site. In other words, it is completely vanilla.
The open files limit (by default) is 1048576. The CodeProject.AI.Server.dll process is doing exactly the same thing it does in my Fedora environments and at about the same rate:
Quote: futex(0x55a20d65b8, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, FUTEX_BITSET_MATCH_ANY) = ? ERESTARTSYS (To be restarted if SA_RESTART is set)
--- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=237742, si_uid=0, si_status=0, si_utime=0, si_stime=2} ---
write(64, "\21", 1) = 1
rt_sigreturn({mask=[]}) = 367791007160
The number of FIFO file handles increases until it hits the limit, then drops back to around 800 (probably less because I'm probably not seeing the lowest number).
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It does make sense that it would be the server, but thanks for confirming that.
Do you have the Explorer and/or dashboard open when you're seeing file handles grow? If so, and if you close both, do the file handles stabilise?
My guess is it's TCP/IP connections. The question is: where?
cheers
Chris Maunder
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Whether the dashboard is open has no effect on the generation of the file handles. In fact, neither does activity. The number of file handles grows at the same rate on a newly started server with no clients and no GUI connection. On a system with no ulimit set, a server will crash when memory runs out even if it has no interaction at all with the outside world. I can't absolutely confirm this, but the growth seems to be exponential rather than linear, or at least inconsistent, with a huge increase just before the host OS shuts it down.
I would add one more thing because I think it is related. There are several issues on this site related to ai-server becoming unresponsive. I have seen the same thing, and when it happens, the server stops spewing out new processes and FIFO file handles. It isn't an inevitable consequence of uptime, and I have not been able to figure out what, if anything, is triggering it.
modified yesterday.
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I'm running the 12_2 CUDA Docker version...
This is what I see:
I also tried the version 11 Cuda Docker as well.
Is it just me or did this change?
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Hi all. I am a long term Windows and BlueIris user but a novice with linux etc.
In an effort to use the mesh capabilities of CodeProject.AI on BlueIris, I have managed to get Mendel running on a Google Coral Dev Board and now want to install CodeProject.ai to the dev board - and am struggling so would really appreciate assistance, please.
I couldn't find any specific guidance for this board so am following the general installation guide
sudo apt install dotnet-sdk-7.0 appears to be failing with this output:
mendel@coy-apple:~$ sudo apt install dotnet-sdk-7.0
Reading package lists... Done
Building dependency tree... Done
E: Unable to locate package dotnet-sdk-7.0
E: Couldn't find any package by glob 'dotnet-sdk-7.0'
E: Couldn't find any package by regex 'dotnet-sdk-7.0'
mendel@coy-apple:~$
What am I doing wrong, please?
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