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I saw that you put up 2.1.4 and tried to install that (closed BI first). I go this error:
Full log:
[355C:2DAC][2023-04-21T13:22:12]i001: Burn v3.11.2.4516, Windows v10.0 (Build 19044: Service Pack 0), path: C:\Users\Adam\AppData\Local\Temp\{8E8220FA-6D90-41C9-A3C6-95228629DB62}\.cr\CodeProject.AI.Server-2.1.4.exe
[355C:2DAC][2023-04-21T13:22:12]i009: Command Line: '-burn.clean.room=C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.Server-2.1.4.exe -burn.filehandle.attached=568 -burn.filehandle.self=684'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleOriginalSource' to value 'C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.Server-2.1.4.exe'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleOriginalSourceFolder' to value 'C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleLog' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212.log'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleName' to value 'CodeProject.AI Server'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting string variable 'WixBundleManufacturer' to value 'CodeProject'
[355C:1874][2023-04-21T13:22:12]i000: Setting numeric variable 'WixStdBALanguageId' to value 1033
[355C:1874][2023-04-21T13:22:12]i000: Setting version variable 'WixBundleFileVersion' to value '2.1.4.0'
[355C:2DAC][2023-04-21T13:22:12]i100: Detect begin, 2 packages
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.0 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting700Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.1 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting701Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.2 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting702Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting703Installed' to value 1
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.4 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting704Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i000: Registry key not found. Key = 'SOFTWARE\WOW6432Node\Microsoft\Updates\.NET\Microsoft ASP.NET Core 7.0.5 - Shared Framework (x64)'
[355C:2DAC][2023-04-21T13:22:12]i000: Setting numeric variable 'NetCoreHosting705Installed' to value 0
[355C:2DAC][2023-04-21T13:22:12]i102: Detected related bundle: {fdcf2cac-9761-450b-8636-5b1b91a09b3c}, type: Upgrade, scope: PerMachine, version: 2.1.3.0, operation: MajorUpgrade
[355C:2DAC][2023-04-21T13:22:12]i103: Detected related package: {3083037B-8E2C-4F9C-81A0-8FE695504DA1}, scope: PerMachine, version: 2.1.3.0, language: 0 operation: MajorUpgrade
[355C:2DAC][2023-04-21T13:22:12]i103: Detected related package: {3083037B-8E2C-4F9C-81A0-8FE695504DA1}, scope: PerMachine, version: 2.1.3.0, language: 0 operation: None
[355C:2DAC][2023-04-21T13:22:12]i101: Detected package: dotnet_hosting_7.0.3_win.exe, state: Absent, cached: Complete
[355C:2DAC][2023-04-21T13:22:12]i101: Detected package: CODEPROJECTAISERVER, state: Absent, cached: None
[355C:2DAC][2023-04-21T13:22:12]i199: Detect complete, result: 0x0
[355C:1874][2023-04-21T13:22:15]i000: Setting numeric variable 'EulaAcceptCheckbox' to value 1
[355C:2DAC][2023-04-21T13:22:15]i200: Plan begin, 2 packages, action: Install
[355C:2DAC][2023-04-21T13:22:15]w321: Skipping dependency registration on package with no dependency providers: dotnet_hosting_7.0.3_win.exe
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleLog_dotnet_hosting_7.0.3_win.exe' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_000_dotnet_hosting_7.0.3_win.exe.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleRollbackLog_dotnet_hosting_7.0.3_win.exe' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_000_dotnet_hosting_7.0.3_win.exe_rollback.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleRollbackLog_CODEPROJECTAISERVER' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_001_CODEPROJECTAISERVER_rollback.log'
[355C:2DAC][2023-04-21T13:22:15]i000: Setting string variable 'WixBundleLog_CODEPROJECTAISERVER' to value 'C:\Users\Adam\AppData\Local\Temp\CodeProject.AI_Server_20230421132212_001_CODEPROJECTAISERVER.log'
[355C:2DAC][2023-04-21T13:22:15]i201: Planned package: dotnet_hosting_7.0.3_win.exe, state: Absent, default requested: Present, ba requested: Present, execute: Install, rollback: Uninstall, cache: No, uncache: No, dependency: None
[355C:2DAC][2023-04-21T13:22:15]i201: Planned package: CODEPROJECTAISERVER, state: Absent, default requested: Present, ba requested: Present, execute: Install, rollback: Uninstall, cache: Yes, uncache: No, dependency: Register
[355C:2DAC][2023-04-21T13:22:15]i207: Planned related bundle: {fdcf2cac-9761-450b-8636-5b1b91a09b3c}, type: Upgrade, default requested: Absent, ba requested: Absent, execute: Uninstall, rollback: Install, dependency: None
[355C:2DAC][2023-04-21T13:22:15]i299: Plan complete, result: 0x0
[355C:2DAC][2023-04-21T13:22:15]i300: Apply begin
[355C:2DAC][2023-04-21T13:22:15]i010: Launching elevated engine process.
[355C:2DAC][2023-04-21T13:22:16]i011: Launched elevated engine process.
[355C:2DAC][2023-04-21T13:22:16]i012: Connected to elevated engine.
[2748:2894][2023-04-21T13:22:16]i358: Pausing automatic updates.
[2748:2894][2023-04-21T13:22:16]i359: Paused automatic updates.
[2748:2894][2023-04-21T13:22:16]i360: Creating a system restore point.
[2748:2894][2023-04-21T13:22:22]i361: Created a system restore point.
[2748:2894][2023-04-21T13:22:22]i370: Session begin, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, options: 0x7, disable resume: No
[2748:2894][2023-04-21T13:22:22]i000: Caching bundle from: 'C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\.be\CodeProject.AI.Server-2.1.4.exe' to: 'C:\ProgramData\Package Cache\{5096f3b1-3ad0-4196-ba43-e567978fb15d}\CodeProject.AI.Server-2.1.4.exe'
[2748:2894][2023-04-21T13:22:22]i320: Registering bundle dependency provider: {5096f3b1-3ad0-4196-ba43-e567978fb15d}, version: 2.1.4.0
[2748:2894][2023-04-21T13:22:22]i371: Updating session, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: Active, restart initiated: No, disable resume: No
[2748:235C][2023-04-21T13:22:23]i304: Verified existing payload: dotnet_hosting_7.0.3_win.exe at path: C:\ProgramData\Package Cache\799a2e153ab905add5a1c3ec06373e51753e8ed2\dotnet-hosting-7.0.3-win.exe.
[355C:26FC][2023-04-21T13:22:23]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:23]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 11BF669C0CFD7DFA18C90760686C7AEE62E69DD0
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:22:37]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:22:37]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:22:37]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[355C:26FC][2023-04-21T13:22:37]e349: Application requested retry of payload: CODEPROJECTAISERVER, encountered error: 0x80091007. Retrying...
[355C:26FC][2023-04-21T13:22:37]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:40]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 58098953CF49E6F4E47DC7772E40273001736F8D
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:22:53]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:22:53]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:22:53]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[355C:26FC][2023-04-21T13:22:53]e349: Application requested retry of payload: CODEPROJECTAISERVER, encountered error: 0x80091007. Retrying...
[355C:26FC][2023-04-21T13:22:53]w343: Prompt for source of package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, path: C:\Users\Adam\Downloads\CodeProject.AI.Server-2.1.4\CodeProject.AI.WebAPI.Installer-2.1.4.msi
[355C:26FC][2023-04-21T13:22:56]i338: Acquiring package: CODEPROJECTAISERVER, payload: CODEPROJECTAISERVER, download from: https://codeproject-ai.s3.ca-central-1.amazonaws.com/sense/installer/version-2.1.4/CodeProject.AI.WebAPI.Installer-2.1.4.msi
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Hash mismatch for path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, expected: 40B44F58D3BE42A35BEF6F998FD4A7403B29498C, actual: 58098953CF49E6F4E47DC7772E40273001736F8D
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Failed to verify hash of payload: CODEPROJECTAISERVER
[2748:235C][2023-04-21T13:23:06]e310: Failed to verify payload: CODEPROJECTAISERVER at path: C:\ProgramData\Package Cache\.unverified\CODEPROJECTAISERVER, error: 0x80091007. Deleting file.
[2748:235C][2023-04-21T13:23:06]e000: Error 0x80091007: Failed to cache payload: CODEPROJECTAISERVER
[355C:26FC][2023-04-21T13:23:06]e314: Failed to cache payload: CODEPROJECTAISERVER from working path: C:\Users\Adam\AppData\Local\Temp\{6284F5A5-C979-469A-8F0F-0E359737F092}\CODEPROJECTAISERVER, error: 0x80091007.
[2748:235C][2023-04-21T13:23:06]i351: Removing cached package: dotnet_hosting_7.0.3_win.exe, from path: C:\ProgramData\Package Cache\799a2e153ab905add5a1c3ec06373e51753e8ed2\
[355C:2DAC][2023-04-21T13:23:06]e000: Error 0x80091007: Failed while caching, aborting execution.
[2748:2894][2023-04-21T13:23:06]i372: Session end, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: None, restart: None, disable resume: No
[2748:2894][2023-04-21T13:23:06]i330: Removed bundle dependency provider: {5096f3b1-3ad0-4196-ba43-e567978fb15d}
[2748:2894][2023-04-21T13:23:06]i352: Removing cached bundle: {5096f3b1-3ad0-4196-ba43-e567978fb15d}, from path: C:\ProgramData\Package Cache\{5096f3b1-3ad0-4196-ba43-e567978fb15d}\
[2748:2894][2023-04-21T13:23:06]i371: Updating session, registration key: SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{5096f3b1-3ad0-4196-ba43-e567978fb15d}, resume: None, restart initiated: No, disable resume: No
[355C:2DAC][2023-04-21T13:23:06]i399: Apply complete, result: 0x80091007, restart: None, ba requested restart: No
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Ok, a reboot and redownload of 2.1.4 and it installed. Currently showing that YOLOv5 6.2 is running, others stopped (I still have face processing off in BI). BI is showing that it's sending to AI, and AI look to be receiving but I can't say for sure until something crosses a camera or I get home.
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Apologies, should have looked at the logs. There is a RuntimeError error when it first starts...
CODEPROJECT
CodeProject.AI
Docs
Forums
The Code
CodeProject.AI Explorer
Server is Online
2.1.4-Beta
☀️
Your self contained AI server. Learn how to integrate with other programs or add your own AI module. Having problems? See our common solutions or ask a question. Blue Iris users: please read our Wyze cam setup guide and common issues pages.
Status
Server logs
System Info
Install Modules
13:34:13:Operating System: Windows (Microsoft Windows 10.0.19044)
13:34:13:CPUs: Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
13:34:13: 1 CPU x 6 cores. 12 logical processors (x64)
13:34:13:GPU: NVIDIA GeForce GTX 1650 SUPER (4 GiB) (NVidia)
13:34:13: Driver: 531.68 CUDA: 12.1 Compute: 7.5
13:34:13:System RAM: 32 GiB
13:34:13:Target: Windows
13:34:13:BuildConfig: Release
13:34:13:Execution Env: Native
13:34:13:Runtime Env: Production
13:34:13:.NET framework: .NET 7.0.3
13:34:13:App DataDir: C:\ProgramData\CodeProject\AI
13:34:13:Video adapter info:
13:34:13: NVIDIA GeForce GTX 1650 SUPER:
13:34:13: Driver Version 31.0.15.3168
13:34:13: Video Processor NVIDIA GeForce GTX 1650 SUPER
13:34:13: Intel(R) UHD Graphics 630:
13:34:13: Driver Version 30.0.101.1692
13:34:13: Video Processor Intel(R) UHD Graphics Family
13:34:13:ROOT_PATH = C:\Program Files\CodeProject\AI
13:34:13:RUNTIMES_PATH = C:\Program Files\CodeProject\AI\runtimes
13:34:13:PREINSTALLED_MODULES_PATH = C:\Program Files\CodeProject\AI\preinstalled-modules
13:34:13:MODULES_PATH = C:\Program Files\CodeProject\AI\modules
13:34:13:PYTHON_PATH = \bin\windows\%PYTHON_RUNTIME%\venv\scripts\Python
13:34:13:Data Dir = C:\ProgramData\CodeProject\AI
13:34:13:Server version: 2.1.4-Beta
13:34:16:
13:34:16:Module 'Object Detection (YOLOv5 6.2)' (ID: ObjectDetectionYolo)
13:34:16:AutoStart: True
13:34:16:Queue: objectdetection_queue
13:34:16:Platforms: all
13:34:16:GPU: Support enabled
13:34:16:Parallelism: 0
13:34:16:Accelerator:
13:34:16:Half Precis.: enable
13:34:16:Runtime: python37
13:34:16:Runtime Loc: Shared
13:34:16:FilePath: detect_adapter.py
13:34:16:Pre installed: False
13:34:16:Start pause: 1 sec
13:34:16:LogVerbosity:
13:34:16:Valid: True
13:34:16:Environment Variables
13:34:16:APPDIR = %CURRENT_MODULE_PATH%
13:34:16:CPAI_MODULE_SUPPORT_GPU = True
13:34:16:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
13:34:16:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
13:34:16:MODEL_SIZE = Medium
13:34:16:USE_CUDA = True
13:34:16:YOLOv5_AUTOINSTALL = false
13:34:16:YOLOv5_VERBOSE = false
13:34:16:
13:34:16:Started Object Detection (YOLOv5 6.2) module
13:34:18:Server: This is the latest version
13:36:58:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'list-custom' (...38f8e8) took 2ms
13:36:59:Sending shutdown request to python/ObjectDetectionYolo
13:37:09:Module ObjectDetectionYolo has shutdown
13:37:09:detect_adapter.py: has exited
13:37:32:ObjectDetectionYolo went quietly
13:37:32:
13:37:32:Module 'Object Detection (YOLOv5 6.2)' (ID: ObjectDetectionYolo)
13:37:32:AutoStart: True
13:37:32:Queue: objectdetection_queue
13:37:32:Platforms: all
13:37:32:GPU: Support enabled
13:37:32:Parallelism: 0
13:37:32:Accelerator:
13:37:32:Half Precis.: enable
13:37:32:Runtime: python37
13:37:32:Runtime Loc: Shared
13:37:32:FilePath: detect_adapter.py
13:37:32:Pre installed: False
13:37:32:Start pause: 1 sec
13:37:32:LogVerbosity:
13:37:32:Valid: True
13:37:32:Environment Variables
13:37:32:APPDIR = %CURRENT_MODULE_PATH%
13:37:32:CPAI_MODULE_SUPPORT_GPU = True
13:37:32:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
13:37:32:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
13:37:32:MODEL_SIZE = Medium
13:37:32:USE_CUDA = True
13:37:32:YOLOv5_AUTOINSTALL = false
13:37:32:YOLOv5_VERBOSE = false
13:37:32:
13:37:32:Started Object Detection (YOLOv5 6.2) module
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5bd029) took 6396ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b36819) took 6398ms
13:37:45:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
13:37:45:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
13:37:45:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...23f7f3) took 6436ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e0c4bc) took 6442ms
13:37:45:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b22b88) took 6441ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...73b70c) took 6443ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7df47a) took 242ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...33bf75) took 251ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ee97c5) took 265ms
13:37:45:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cc52a6) took 272ms
13:38:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'list-custom' (...0d5030) took 2ms
13:38:04:Sending shutdown request to python/ObjectDetectionYolo
13:38:13:detect_adapter.py: GPU compute capability is 7.5
13:38:13:detect_adapter.py: Using half-precision for the device 'NVIDIA GeForce GTX 1650 SUPER'
13:38:13:detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1650 SUPER'
13:38:13:Module ObjectDetectionYolo has shutdown
13:38:13:detect_adapter.py: has exited
13:38:37:ObjectDetectionYolo went quietly
13:38:37:
13:38:37:Module 'Object Detection (YOLOv5 6.2)' (ID: ObjectDetectionYolo)
13:38:37:AutoStart: True
13:38:37:Queue: objectdetection_queue
13:38:37:Platforms: all
13:38:37:GPU: Support enabled
13:38:37:Parallelism: 0
13:38:37:Accelerator:
13:38:37:Half Precis.: enable
13:38:37:Runtime: python37
13:38:37:Runtime Loc: Shared
13:38:37:FilePath: detect_adapter.py
13:38:37:Pre installed: False
13:38:37:Start pause: 1 sec
13:38:37:LogVerbosity:
13:38:37:Valid: True
13:38:37:Environment Variables
13:38:37:APPDIR = %CURRENT_MODULE_PATH%
13:38:37:CPAI_MODULE_SUPPORT_GPU = True
13:38:37:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
13:38:37:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
13:38:37:MODEL_SIZE = Medium
13:38:37:USE_CUDA = True
13:38:37:YOLOv5_AUTOINSTALL = false
13:38:37:YOLOv5_VERBOSE = false
13:38:37:
13:38:37:Started Object Detection (YOLOv5 6.2) module
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3e6707) took 3583ms
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c2e49a) took 3579ms
13:38:46:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (15) must match the size of tensor b (12) at non-singleton dimension 2
13:38:46:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (15) must match the size of tensor b (12) at non-singleton dimension 2
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4af48c) took 3579ms
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...9e4384) took 3594ms
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a3a104) took 3591ms
13:38:46:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...18e6bf) took 3590ms
13:38:47:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7864e4) took 293ms
13:38:47:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c61cce) took 307ms
13:38:47:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...495b4c) took 301ms
13:38:47:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ae686a) took 308ms
13:39:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d4fd01) took 363ms
13:39:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:39:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f562df) took 249ms
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c25c0a) took 355ms
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...da3236) took 369ms
13:39:17:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:39:17:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b72605) took 128ms
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2247f1) took 105ms
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5601ef) took 113ms
13:39:17:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:39:17:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f1641c) took 81ms
13:39:18:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...282e11) took 117ms
13:39:18:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:39:18:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...40e5bd) took 64ms
13:40:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5e73ce) took 327ms
13:40:00:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4bb18f) took 136ms
13:40:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...309b0c) took 133ms
13:40:00:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9d15a9) took 61ms
13:40:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...99e6a8) took 98ms
13:40:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...271b47) took 55ms
13:40:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...44341c) took 97ms
13:40:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ab6e91) took 49ms
13:40:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...856965) took 111ms
13:40:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...060730) took 74ms
13:40:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...92386f) took 107ms
13:40:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2c0059) took 62ms
13:40:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0d5efc) took 129ms
13:40:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...52632e) took 84ms
13:40:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...537695) took 130ms
13:40:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ad2394) took 56ms
13:40:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f12b95) took 385ms
13:40:25:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...081725) took 474ms
13:40:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...03b229) took 169ms
13:40:25:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...64a0ec) took 85ms
13:40:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f8316e) took 125ms
13:40:26:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:26:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...344cf8) took 76ms
13:40:26:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6990d9) took 117ms
13:40:26:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:26:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...561e0b) took 77ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...543103) took 127ms
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...aa2138) took 247ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...04291d) took 430ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3577a6) took 435ms
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bedfbd) took 512ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6b29e8) took 347ms
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f4e09a) took 348ms
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...9f8461) took 377ms
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7ae9a6) took 298ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5fe91e) took 236ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a13fd2) took 250ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ae7bba) took 178ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...314093) took 198ms
13:40:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...c7c1fa) took 179ms
13:41:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...424f19) took 285ms
13:41:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f3f770) took 145ms
13:41:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...73bbd5) took 161ms
13:41:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6049b5) took 57ms
13:41:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...2d8a03) took 96ms
13:41:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...58e0de) took 56ms
13:41:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c3c899) took 98ms
13:41:04:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ffa47c) took 55ms
13:41:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6188f4) took 339ms
13:41:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7081ce) took 145ms
13:41:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f63485) took 144ms
13:41:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b9624a) took 56ms
13:41:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...dc93d0) took 107ms
13:41:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d7f95e) took 62ms
13:41:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cdcf70) took 100ms
13:41:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0a806a) took 56ms
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ef107d) took 360ms
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d5cf40) took 375ms
13:41:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...934da2) took 188ms
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7f2209) took 204ms
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5ffa2a) took 184ms
13:41:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2edbb0) took 72ms
13:41:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a21a31) took 111ms
13:41:34:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:41:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...676193) took 66ms
13:42:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b6dd24) took 380ms
13:42:00:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e50824) took 56ms
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b73874) took 307ms
13:42:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0210fc) took 426ms
13:42:27:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (60) must match the size of tensor b (64) at non-singleton dimension 2
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...aac1d9) took 425ms
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0cf342) took 418ms
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c39cd8) took 444ms
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bc36cd) took 475ms
13:42:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a0d820) took 454ms
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...89b099) took 154ms
13:42:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...714da7) took 158ms
13:42:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1ca0b2) took 153ms
13:42:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d5eee7) took 83ms
13:42:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...90c337) took 94ms
13:42:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...279fa9) took 44ms
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...dec87c) took 365ms
13:42:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d7a398) took 80ms
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...da33e4) took 122ms
13:42:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5daace) took 67ms
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...25e60a) took 108ms
13:42:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4720d3) took 83ms
13:42:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...249cd0) took 115ms
13:42:43:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:42:43:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...dedf96) took 72ms
13:43:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e3f530) took 251ms
13:43:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:43:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...109580) took 60ms
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...616e0e) took 430ms
13:43:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3b96d2) took 171ms
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...c9af7e) took 162ms
13:43:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...51aa2d) took 72ms
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...384a8d) took 113ms
13:43:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:43:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...857934) took 66ms
13:43:52:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...44afda) took 108ms
13:43:52:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:43:52:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2c5deb) took 67ms
13:44:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b9c581) took 116ms
13:44:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...15e254) took 68ms
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...48fd6a) took 296ms
13:44:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6e72ed) took 372ms
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...55438d) took 390ms
13:44:27:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (32) must match the size of tensor b (24) at non-singleton dimension 2
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d110a2) took 390ms
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...865bdd) took 371ms
13:44:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...15c0df) took 381ms
13:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5ce6a0) took 124ms
13:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1315fe) took 105ms
13:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f4cf6f) took 101ms
13:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...618be2) took 101ms
13:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7d0a97) took 60ms
13:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6e3f27) took 95ms
13:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1bb490) took 46ms
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ccc4d8) took 429ms
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...079f6e) took 484ms
13:44:59:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:59:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fb1ed3) took 241ms
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bad829) took 161ms
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0f103e) took 191ms
13:44:59:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4d3762) took 66ms
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f36975) took 109ms
13:44:59:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:44:59:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...666c06) took 66ms
13:45:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e68f6d) took 279ms
13:45:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:45:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...295996) took 70ms
13:46:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...de4492) took 267ms
13:46:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fba059) took 61ms
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c83924) took 467ms
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f410cb) took 499ms
13:46:07:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:07:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f63fc9) took 204ms
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...64efcb) took 198ms
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7a71cd) took 179ms
13:46:07:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:07:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...008559) took 88ms
13:46:08:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5a75aa) took 109ms
13:46:08:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:08:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...478099) took 65ms
13:46:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...1b07d8) took 387ms
13:46:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...82401b) took 386ms
13:46:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ced073) took 176ms
13:46:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2ac797) took 181ms
13:46:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...205635) took 190ms
13:46:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5cb00c) took 87ms
13:46:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bd1a96) took 111ms
13:46:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2c3e70) took 66ms
13:46:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d08579) took 471ms
13:46:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...64e2b7) took 428ms
13:46:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...07c80b) took 92ms
13:46:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b28187) took 94ms
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6c89e3) took 94ms
13:46:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a7ea69) took 56ms
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0851e8) took 164ms
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cb6cbd) took 158ms
13:46:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...88d360) took 84ms
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7db6f6) took 63ms
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...294d71) took 100ms
13:46:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...c64b34) took 76ms
13:46:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c3fcd2) took 88ms
13:46:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:46:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e478bc) took 45ms
13:47:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3d3282) took 343ms
13:47:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f80b32) took 64ms
13:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c3f9fa) took 107ms
13:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9d3709) took 63ms
13:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f67e21) took 95ms
13:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6b0f62) took 51ms
13:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0c2d96) took 97ms
13:47:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a8b6c4) took 55ms
13:47:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...28c2fe) took 312ms
13:47:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5ffd10) took 72ms
13:47:15:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...8ce407) took 127ms
13:47:15:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...632fed) took 113ms
13:47:15:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:15:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8a4c06) took 67ms
13:47:16:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:16:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f51cd5) took 67ms
13:47:16:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...87b1a5) took 111ms
13:47:16:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:16:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7c8309) took 68ms
13:47:16:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...baf97f) took 108ms
13:47:16:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:47:16:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...024ba5) took 77ms
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bbf2c8) took 489ms
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4fb89f) took 506ms
13:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b470a8) took 85ms
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...800fbc) took 93ms
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fcd31a) took 94ms
13:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1c271a) took 49ms
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cd05eb) took 95ms
13:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d7d85f) took 58ms
13:48:24:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0f1cd1) took 314ms
13:48:24:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:24:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0614c9) took 158ms
13:48:24:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ee1ef3) took 163ms
13:48:24:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:24:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7f5b16) took 67ms
13:48:24:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...8ce752) took 112ms
13:48:25:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...79e0b7) took 68ms
13:48:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ecd708) took 117ms
13:48:25:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:25:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d4f7f2) took 89ms
13:48:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...010a59) took 210ms
13:48:27:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d9ea51) took 53ms
13:48:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...01850c) took 117ms
13:48:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...dd16f3) took 142ms
13:48:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ca9b85) took 120ms
13:48:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...00a7c7) took 65ms
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...64eeb3) took 102ms
13:48:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...554c9a) took 124ms
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...29386b) took 144ms
13:48:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...886b67) took 68ms
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ee2154) took 99ms
13:48:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...3af9c1) took 53ms
13:48:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...208b5e) took 89ms
13:48:30:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:48:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0fb209) took 52ms
13:49:15:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...195262) took 310ms
13:49:15:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:49:15:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b16ad8) took 59ms
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d36847) took 330ms
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e97684) took 370ms
13:49:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:49:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...986db1) took 147ms
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d6162e) took 74ms
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b9b71a) took 117ms
13:49:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:49:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9d5ae3) took 66ms
13:49:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a43d2c) took 108ms
13:49:34:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:49:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...774a27) took 69ms
13:50:00:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e89cc2) took 262ms
13:50:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8203f2) took 55ms
13:50:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...50e85d) took 106ms
13:50:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a5f949) took 52ms
13:50:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0a5368) took 96ms
13:50:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9c4f28) took 56ms
13:50:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...28cf29) took 95ms
13:50:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8ec6ed) took 54ms
13:50:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...790bf3) took 187ms
13:50:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e343ef) took 128ms
13:50:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...495094) took 134ms
13:50:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...931722) took 58ms
13:50:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...1dfe31) took 103ms
13:50:04:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1a10ee) took 55ms
13:50:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...be1586) took 96ms
13:50:04:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...64ca3d) took 60ms
13:50:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...aabb5d) took 383ms
13:50:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b43a93) took 57ms
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...151bcc) took 131ms
13:50:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0912e4) took 146ms
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b8ab77) took 154ms
13:50:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fea76d) took 61ms
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d89f24) took 95ms
13:50:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...60718c) took 59ms
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7e836d) took 204ms
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...525a0b) took 173ms
13:50:30:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...145614) took 55ms
13:50:30:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...c9ca13) took 59ms
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5f8345) took 90ms
13:50:30:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:30:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...90d018) took 49ms
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...42d67e) took 389ms
13:50:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...80bdb2) took 466ms
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...753d8e) took 160ms
13:50:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...64583a) took 77ms
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...691870) took 116ms
13:50:42:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:42:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...013d4f) took 77ms
13:50:43:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...330715) took 112ms
13:50:43:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:50:43:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...56ab1c) took 64ms
13:51:50:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...535f77) took 328ms
13:51:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...644d66) took 160ms
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...056ab4) took 158ms
13:51:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4f97c2) took 68ms
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d300ac) took 119ms
13:51:51:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4a3b44) took 67ms
13:51:51:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...26f025) took 114ms
13:51:52:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:51:52:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...84439d) took 63ms
13:52:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bac647) took 255ms
13:52:01:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:52:01:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...20baf7) took 55ms
13:52:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...8c2cc7) took 332ms
13:52:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
13:52:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...42e1f5) took 62ms
Logging level
Info
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Bonjour,
Je n'ai pas encore installé le serveur. Je ne sais pas s'il peut répondre à ma problématique :
Je dois reconnaitre le contour précis de spores de champignons à partir d'images capturées par un microscope (ci-joint une image). De telles images comportent généralement beaucoup de spores mais nous nous intéressons seulement quelques unes répondant à des critères de positionnement.
Comment CodeProject.AI Server peut-il m'aider ?
Merci de votre réponse.
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I'll respond in English first, then try my hand at French. I'm very, rusty.
To perform any detection of anything - be it mushroom spores or anything else - you will need to train a model that can do that. There are a number of datasets you can use to build a model at Roboflow, and you can export the model in YOLOv5 format, which our Object Detector (YOLO 6.2) can process. See the docs at Roboflow. To use the model just drop the model (a PyTorch .pt file) in the custom-models folder of ObjectDetectionYolo and use the custom model API
Pour effectuer une détection de quelque chose que ce soit - que ce soit des spores de champignons ou autre chose - vous devrez entraîner un modèle capable de le faire. Il existe plusieurs ensembles de données que vous pouvez utiliser pour construire un modèle sur Roboflow, et vous pouvez exporter le modèle au format YOLOv5, que notre détecteur d'objets (YOLO 6.2) peut traiter. Consultez la documentation sur Roboflow. Pour utiliser le modèle, il suffit de déposer le modèle (un fichier .pt PyTorch) dans le dossier "custom-models" d'ObjectDetectionYolo et d'utiliser l'API custom model.
cheers
Chris Maunder
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Thanks Chris, I'll follow Roboflow's lead.
Your French is perfect!
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Hi,
In the last 24-48hrs I've started to notice an issue with my BI / CP installation (only installed a few days ago).
CPU usage has gone from 5% and a few hundred mb of memory to peaks of up to 85% CPU and 7.33GB memory.
These peaks correspond with object analysis. You can hear the pc fans surge alongside the cpu spike and see object detection in progress inside the console window. Prior to this, I believe I was on the earlier build so it could be down to the newer build.
The system is strong for a BI build consisting of:
Intel i5-11400
16Gb DDR4 Corsair Memory
Samsung 870 EVO SSD
WD Purple Hard Drive (footage)
AI is installed onto the SSD.
Here's a screenshot of the console view:
Code-Project-AI-CPU-Surging hosted at ImgBB — ImgBB[^]
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Thanks very much for your message. Could I please see your Triggers -> Artificial Intelligence settings?
Thanks,
Sean Ewington
CodeProject
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Triggers (using Trip Wires in the camera).
Triggers hosted at ImgBB — ImgBB[^]
AI Settings:
AI-Settings hosted at ImgBB — ImgBB[^]
According to the AI Dashboard, I'm using Yolov5 6.2 CPU. (I have integrated graphics only on the Intel i5-11400).
Object detection is around 170ms according to the dashboard.
BTW limiting detection to persons, trucks, cars, bicycle, cat and fox.
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I'm looking to set up the AI server with Raspberry Pi and NCS2. Is it supported and if it is, is openVino required?
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It's not supported by any of our modules at the moment.
Anyone out there care to write a module that supports it?
cheers
Chris Maunder
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How do you install Object Detection (YOLOv5 .NET) in CodeProject 2.1.1
Thank you,
Rick
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You need to go to the Explorer link (http://localhost:32168/[^]) then click on Install Modules next click on Install, mine shows Uninstall because it installed already. Make sure you only have one Object Detection module running so disable whatever Object Detection module you have running before starting the Object Detection (YOLOv5 .NET) module.
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It should be installed by default.
When the server is first launched, it checks to see if you've installed v2.1 or above. If you have, then you have the YOLO .NET installed in the correct place (unless you removed it). If you are upgrading from < 2.1 then the server, on first launch, will automatically download and install YOLOv5 (Python and .NET) and Face Processing. The server starts as soon as the Windows installer has finished, or as soon as you start a Docker container.
We have an issue (addressed in 2.1.3) where the server was not always able to connect to port 32168, and so the dashboard would not be showing that the modules were being installed. Installation would happen, but it could take some time and it would appear nothing was going on. If you check C:\Program Files\CodeProject\AI\modules you should see the folder ObjectDetectionNet.
New server release out today
cheers
Chris Maunder
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Thank you for all the replies. Bob helped me and it is now installed however now I am getting AI: error 500 messages on everything.
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keeps saying PIL not found
docker desktop on windows
2.1.1 but it does happen with 2.1 was well (arm.rpi,cpu)
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Did you download and install the TFLite module, or are you running the Arm64 / Raspberry Pi docker image?
Did you map the modules directory in the Docker container to a windows folder, or just keeping everything running inside the container? Either way, if you can get to the /modules/ObjectDetectionTFLite folder, can you let me know what the install.log file contains?
Sounds like the python packages didn't install properly. You may want to try uninstalling / reinstalling that module.
cheers
Chris Maunder
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Yep I get the same error. I'm running docker on linux (AMD64). It seems the packages are not installing properly. The last thing in the install.log is something like "timeout installing linux-requirments.txt". The container then crashes. Once started again, you get the PIL error if you try to enable the TF module from the gui.
Sorry I dont have the full log as I had to uninstall the module.
Hope this helps.
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I'm made an update to the supported platforms for the TFLite module to restrict it to Raspberry Pi's only for now.
cheers
Chris Maunder
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Question is in the subject line.
If it does support Coral - will install guides be updated soon to explain configuration of Docker install?
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Yes and Yes (click on the Raspberry Pi tab)
cheers
Chris Maunder
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So only supported on the Pi and only with USB Coral?
Any outlook on more general release, amd64 and pci-based Coral? Will it support both TPUs if you have a dual pci Coral?
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Be careful of the dual versions - from memory they don't support Windows. Fine if you're not a Windows user, not so fine if you are.
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Got it and understood. But I am on Linux and have been using the dual PCIe Coral with another project for quite a while - a project that I would dearly love to replace with the more open approach offered by Codeproject.ai.
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[Update]: We've worked out where the issue is with Docker, GPU and YOLO models. We don't know what it's happening but it's related to the way the YOLO code loads models and handles where and how the model gets pushed to the GPU. Things are breaking, we're not sure why, we think it's a YOLO issue. If we remove cuDNN then things work, but the .NET Object Detector no longer uses the GPU.
Our workaround is we'll provide a GPU image with cuDNN as default, and a non-cuDNN equipped image for those (like myself) who experience the issue.
The server is sometimes refusing to listen. It runs, but it's like a teenager with its headphones on. We have a fix for that.
We were really hoping old modules would Just Work, and some do but many require you to update them via the dashboard. This is inconvenient, so we apologise for this.
The installer has an issue similar to what we had with 1.6.9 where it requires you to uninstall the old before installing the new. You don't have to, but if you don't you need to manually start the service. It's all to do with us moving from a bootstrap-and-sub-installer model to a single installer model, and the way Windows installer handles post-install events. The uninstaller gets the last laugh and stops the service that we just started with the new installer. It's a bit mind bending as to why, but then again, the entirety of WiX is mind mending in my view.
Matthew is doing final smoke-tests of the Windows installer, and I'm trying to build new images to push to Docker hub, except it seems security.ubuntu.com is down and we can't pull base images.
Life is never boring. Tomorrow is a new day.
We have a couple of reports of issues in 2.1.1 that meant we've moved back to 2.0.8 as the latest stable version.
Our docker images are 2.1.0, and these are stable except for GPU which is showing issues. Please use
docker pull codeproject/ai-server:gpu-2.0.8
for Docker GPU.
If you see issues, anywhere, please ensure you tell us:
1. The version you're on
2. The environment (Docker, Windows, or running in development via VS Code)
3. Your hardware (CPU, or if GPU, the card name)
Sorry for the messiness here. Lots of moving parts but we'll hunt down the bugs and squash them one by one
cheers
Chris Maunder
modified 18-Apr-23 21:55pm.
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