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Excellent news!
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Thanks for your hard work.
So we can go to CUDA 12.1 ?
Can you show us what is absolutely necessary to install in CUDA because there is a lot of things.
Thank you again !
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If you're on CUDA 12.1 it should all just work (it does on my machine!)
cheers
Chris Maunder
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2.1.3 is broken.
Downloaded, prompted to uninstall previous veriosn. Did that. Installed 2.1.3, it started and now all I get it:
07:40:13:
07:40:13:Started Object Detection (YOLOv5 6.2) module
07:40:14:Server: This is the latest version
07:40:14:detect_adapter.py: Traceback (most recent call last):
07:40:14:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect_adapter.py", line 20, in
07:40:14:detect_adapter.py: from detect import init_detect, do_detection
07:40:14:detect_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 9, in
07:40:14:detect_adapter.py: from yolov5.models.common import DetectMultiBackend, AutoShape
07:40:14:detect_adapter.py: ModuleNotFoundError: No module named 'yolov5'
07:40:15:Module ObjectDetectionYolo has shutdown
07:40:15:detect_adapter.py: has exited
07:40:16:face.py: GPU in use: NVIDIA GeForce GTX 1650 SUPER
07:40:27:Connection id "0HMQ2EP77S13C", Request id "0HMQ2EP77S13C:00000001": An unhandled exception was thrown by the application.
It's running face detection in GPU mode but YOLO in CPU, which was previously GPU. But then just crashes...
🤷
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Well have it running now, looks like it tries to download something from China during install and that was being blocked by my filtering.
Anyhow, it's installed and running now but it's not detecting anything in BlueIris...
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Logs, looks like there's some errors during startup.
Install Modules
08:48:44:Connection id "0HMQ2FTR3VJBG", Request id "0HMQ2FTR3VJBG:00000001": An unhandled exception was thrown by the application.
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (48) must match the size of tensor b (60) at non-singleton dimension 2
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (15) must match the size of tensor b (12) at non-singleton dimension 2
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 75, in forward
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
08:49:00:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (24) must match the size of tensor b (30) at non-singleton dimension 2
08:49:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a80390) took 333ms
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Looking more, the errors repeat, not just at startup...
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What GPU are you using?
cheers
Chris Maunder
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Yes, ALPR and OCR both use paddlepaddle, an AI package developed by Baidu (Chinese version of Google). The Python packages for paddlepaddle are hosted in China.
cheers
Chris Maunder
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Can you please uninstall / reinstall the ObjectDetectionYolo module via the dashboard ('modules' tab)? The "No module named 'yolov5'" means the yolo python package didn't get installed properly.
cheers
Chris Maunder
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Hello, I'm using a 1650 Super.
I stopped BlueIris and went ahead and completely uninstalled AI (add/remove programs) and deleted the directories under Program Files and ProgramData.
After instilling I let the server run and it installed and ran:
Face Processing
Object Detection (YOLOv5 .NET)
Object Detection (YOLOv5 6.2)
All these were running using CUDA.
After it was done installing I started BlueIris and waited for it to settle and now The following are running (using CUDA):
Object Detection (YOLOv5 6.2)
YOLOv5 .NET is stopped as well as Face Processing but I have Face Processing disabled in BI atm.
It's hard for me to test completely atm as I'm away from home (can't walk in front of the camera and we don't live on a super active street) but BI is showing AI is active. Earlier when I was able to test it was sowing active as well, just not "finding" anything.
I saw an error just after installing but I don't think there has been once since...
11:40:44:YOLOv5_AUTOINSTALL = false
11:40:44:YOLOv5_VERBOSE = false
11:40:44:
11:40:44:Started Object Detection (YOLOv5 6.2) module
11:40:44:Installer exited with code 0
11:40:45:Module ObjectDetectionYolo started successfully.
11:43:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'list-custom' (...db7036) took 2ms
11:43:11:Sending shutdown request to python/FaceProcessing
11:43:19:Module FaceProcessing has shutdown
11:43:19:face.py: has exited
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5dab75) took 1181ms
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (48) must match the size of tensor b (60) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0af8e8) took 4686ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...be144e) took 4756ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...646b54) took 1212ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...84d7ea) took 4732ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5b4f3c) took 4735ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): [RuntimeError] : Traceback (most recent call last):
File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYolo\detect.py", line 162, in do_detection
det = detector(img, size=640)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
y = self.model(x, augment=augment) # forward
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
return self._forward_once(x, profile, visualize) # single-scale inference, train
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
x = m(x) # run
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 74, in forward
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
RuntimeError: The size of tensor a (60) must match the size of tensor b (48) at non-singleton dimension 2
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...afb61c) took 274ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f0d2ea) took 308ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bf5017) took 318ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...617d4e) took 294ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1b2eca) took 527ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ffcb7d) took 252ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8f78fc) took 531ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d5dc0d) took 267ms
11:43:39:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e20448) took 252ms
11:43:39:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d95413) took 34ms
11:43:44:FaceProcessing went quietly
11:43:44:Sending shutdown request to python/ObjectDetectionYolo
11:43:49:detect_adapter.py: GPU compute capability is 7.5
11:43:49:detect_adapter.py: Using half-precision for the device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: GPU compute capability is 7.5
11:43:49:detect_adapter.py: Using half-precision for the device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:49:detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1650 SUPER'
11:43:50:Module ObjectDetectionYolo has shutdown
11:43:50:detect_adapter.py: has exited
11:44:17:ObjectDetectionYolo went quietly
11:44:17:
11:44:17:Module 'Object Detection (YOLOv5 6.2)' (ID: ObjectDetectionYolo)
11:44:17:AutoStart: True
11:44:17:Queue: objectdetection_queue
11:44:17:Platforms: all
11:44:17:GPU: Support enabled
11:44:17:Parallelism: 0
11:44:17:Accelerator:
11:44:17:Half Precis.: enable
11:44:17:Runtime: python37
11:44:17:Runtime Loc: Shared
11:44:17:FilePath: detect_adapter.py
11:44:17:Pre installed: False
11:44:17:Start pause: 1 sec
11:44:17:LogVerbosity:
11:44:17:Valid: True
11:44:17:Environment Variables
11:44:17:APPDIR = %CURRENT_MODULE_PATH%
11:44:17:CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%/custom-models
11:44:17:MODELS_DIR = %CURRENT_MODULE_PATH%/assets
11:44:17:MODEL_SIZE = Medium
11:44:17:USE_CUDA = True
11:44:17:YOLOv5_AUTOINSTALL = false
11:44:17:YOLOv5_VERBOSE = false
11:44:17:CPAI_MODULE_SUPPORT_GPU = True
11:44:17:
11:44:17:Started Object Detection (YOLOv5 6.2) module
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d1944d) took 3725ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...064d88) took 3735ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6b57d8) took 3755ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5ef1e7) took 3767ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b25837) took 3764ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fd8afa) took 3795ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ba2a54) took 536ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...25dd10) took 559ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6d6888) took 555ms
11:44:27:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...2735fd) took 583ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4b88b4) took 577ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4f12ba) took 601ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f28a2e) took 457ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...239311) took 490ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...772a83) took 491ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...30f837) took 508ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d46fb0) took 611ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e7fd2b) took 686ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...21db1d) took 348ms
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c8293a) took 380ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:28:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4e213d) took 384ms
11:44:28:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9b79a2) took 348ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6bb00e) took 515ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fb5101) took 406ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...127954) took 723ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b3ff0b) took 573ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7638bd) took 441ms
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...685bc9) took 138ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6ca581) took 134ms
11:44:29:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0afa87) took 138ms
11:45:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...724c81) took 352ms
11:45:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...4c8558) took 505ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e985cc) took 562ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...99cbcf) took 580ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...702bad) took 588ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d00071) took 578ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d566a0) took 598ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d76476) took 405ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...886224) took 447ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f3d2ff) took 481ms
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...57a183) took 483ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3242fd) took 536ms
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...84d708) took 567ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...7112e9) took 300ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...106b38) took 289ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...080cfc) took 281ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5bfc7a) took 289ms
11:45:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...97939a) took 286ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...20b7ef) took 256ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...29c334) took 191ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...917a96) took 184ms
11:45:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...3c236b) took 143ms
11:45:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e63329) took 400ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cd675e) took 232ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...43af6b) took 249ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...ba1941) took 428ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ffc8c3) took 270ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...853c2f) took 250ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fcda3e) took 268ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d58a3c) took 234ms
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...fa54f3) took 100ms
11:45:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e3f8ee) took 97ms
11:45:48:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...634750) took 348ms
11:45:48:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:45:48:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2af8ea) took 36ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...454fe7) took 257ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c56c4b) took 144ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e9a8bb) took 142ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e3c096) took 54ms
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7ad4f4) took 111ms
11:46:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e00f0f) took 65ms
11:46:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7aaff3) took 98ms
11:46:04:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:04:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...b9406d) took 50ms
11:46:09:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e2d328) took 343ms
11:46:09:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:09:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...291f8d) took 68ms
11:46:11:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fed145) took 356ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ec1cdb) took 731ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5a427a) took 454ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...cfc7d8) took 466ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3c34b9) took 499ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...5f4453) took 559ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3a1da2) took 642ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d4b51f) took 331ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...891469) took 350ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...f0888e) took 412ms
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...8f11d3) took 432ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...cfb66c) took 417ms
11:46:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...77ac46) took 386ms
11:46:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...052dc6) took 251ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...024dfa) took 237ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bac8f3) took 231ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...98d4c3) took 216ms
11:46:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a85c01) took 155ms
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4d9b2f) took 345ms
11:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...31019a) took 54ms
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...580272) took 99ms
11:47:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...531e50) took 52ms
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d3a1a4) took 98ms
11:47:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bcd124) took 50ms
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3c17fc) took 96ms
11:47:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...96f86e) took 53ms
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...22e956) took 302ms
11:47:12:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7f12f7) took 411ms
11:47:12:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...10aed6) took 424ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...2c6f4a) took 450ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...57b386) took 479ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3e4c7d) took 588ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4dae33) took 542ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ba9a57) took 403ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...3a847f) took 409ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...bfaeff) took 391ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9e04a0) took 371ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...07f6c7) took 452ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...73cfdb) took 316ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ddb4e3) took 343ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8e9b6e) took 331ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e4d89c) took 317ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0e2502) took 310ms
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1fd6ff) took 142ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8a97f2) took 136ms
11:47:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...27c58e) took 128ms
11:47:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...a73161) took 308ms
11:47:33:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:33:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...dcacd7) took 72ms
11:47:34:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fafc8b) took 143ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...b2a41f) took 164ms
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1cca67) took 83ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a0c1fa) took 79ms
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...dd8c29) took 94ms
11:47:35:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:35:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...eb6eda) took 50ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...fc74e3) took 152ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...841564) took 162ms
11:47:36:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:36:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2b3719) took 80ms
11:47:36:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...08816e) took 73ms
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...0e56ad) took 408ms
11:48:02:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ebbc86) took 143ms
11:48:02:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...5d1a72) took 146ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...9d3296) took 60ms
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...bbc82b) took 110ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e48eab) took 148ms
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...85281a) took 112ms
11:48:03:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:03:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...8524ea) took 54ms
11:48:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e1a8d0) took 370ms
11:48:10:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:10:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...1596b7) took 66ms
11:48:13:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...e75682) took 296ms
11:48:13:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...453bd4) took 721ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...d0c286) took 531ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...6ed06c) took 543ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...336fb6) took 558ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...61e6d8) took 656ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...c92283) took 715ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...4739df) took 447ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...184d1e) took 462ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...7863ff) took 472ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...9d526c) took 505ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'detect' (...ef0cc1) took 463ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...f330cd) took 347ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...0a82f0) took 273ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...d6ff0e) took 319ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...6542b3) took 268ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...e7e753) took 264ms
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Detecting using ipcam-combined
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...2e5e9b) took 277ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...652fac) took 233ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...43f0ce) took 197ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...00cf84) took 184ms
11:48:14:Object Detection (YOLOv5 6.2): Queue request for Object Detection (YOLOv5 6.2) command 'custom' (...a5ebf6) took 181ms
Server version: 2.1.3-Beta
Operating System: Windows (Microsoft Windows 10.0.19044)
CPUs: Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
1 CPU x 6 cores. 12 logical processors (x64)
GPU: NVIDIA GeForce GTX 1650 SUPER (4 GiB) (NVidia)
Driver: 531.68 CUDA: 12.1 Compute: 7.5
System RAM: 32 GiB
Target: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
.NET framework: .NET 7.0.3
System GPU info:
GPU 3D Usage 5%
GPU RAM Usage 487 MiB
Video adapter info:
NVIDIA GeForce GTX 1650 SUPER:
Driver Version 31.0.15.3168
Video Processor NVIDIA GeForce GTX 1650 SUPER
Microsoft Remote Display Adapter:
Driver Version 10.0.19041.2075
Video Processor
Intel(R) UHD Graphics 630:
Driver Version 30.0.101.1692
Video Processor Intel(R) UHD Graphics Family
Global Environment variables:
CPAI_APPROOTPATH = C:\Program Files\CodeProject\AI
CPAI_PORT = 32168
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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
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2.1.4-Beta
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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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