CodeProject.AI Discussions

4-Apr-24 8:25

With object detection yolov5.net 1.10.1 i just update and i cant get it to use the gpu ( i have a P1000) i select it in the menu it restarts and go back to CPU (DirectML) is this a bug ?

What I have tried:

ReInstall object detection yolov5.net 1.10.1 , pc restart , reinstalling CPAI

modified 5-Apr-24 17:46pm.

Sean Ewington4-Apr-24 8:33

Sean Ewington

4-Apr-24 8:33

Thanks very much for your report. Could you please share your System Info tab from your CodeProject.AI Server dashboard?

Thanks,
Sean Ewington
CodeProject

Joey War4-Apr-24 9:34

Whats-App-Image-2024-04-04-at-19-47-27-4b5099a7 hosted at ImgBB — ImgBB[^]

4-Apr-24 9:34

Mike Lud4-Apr-24 9:40

Mike Lud

4-Apr-24 9:40

Sean

It looks like a code typo mine is showing CPU, I tested it and it is definitely using the GPU.

Matthew Dennis4-Apr-24 11:04

Matthew Dennis

4-Apr-24 11:04

Mike,
Could you please send my your System Info tab contents.

Thanks,

"Mistakes are prevented by Experience. Experience is gained by making mistakes."

Mike Lud4-Apr-24 11:21

Mike Lud

4-Apr-24 11:21

Both of my systems are showing CPU

Server version:   2.6.2
System:           Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs:             AMD Ryzen 9 5950X 16-Core Processor             (AMD)
                  1 CPU x 16 cores. 32 logical processors (x64)
GPU (Primary):    NVIDIA GeForce RTX 4090 (24 GiB) (NVIDIA) 
                  Driver: 551.86, CUDA: 12.4 (up to: 12.4), Compute: 8.9, cuDNN: 8.9
System RAM:       128 GiB
Platform:         Windows
BuildConfig:      Release
Execution Env:    Native
Runtime Env:      Production
Runtimes installed:
  .NET runtime:     7.0.17
  .NET SDK:         7.0.203
  Default Python:   3.11.0
  Go:               Not found
  NodeJS:           20.8.1
  Rust:             Not found
Video adapter info:
  NVIDIA GeForce RTX 4090:
    Driver Version     31.0.15.5186
    Video Processor    NVIDIA GeForce RTX 4090
System GPU info:
  GPU 3D Usage       1%
  GPU RAM Usage      6 GiB
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

Server version:   2.6.2
System:           Windows
Operating System: Windows (Microsoft Windows 10.0.19045)
CPUs:             AMD Ryzen 9 3950X 16-Core Processor             (AMD)
                  1 CPU x 16 cores. 32 logical processors (x64)
GPU (Primary):    NVIDIA GeForce RTX 3060 (12 GiB) (NVIDIA) 
                  Driver: 551.86, CUDA: 12.4 (up to: 12.4), Compute: 8.6, cuDNN: 8.9
System RAM:       64 GiB
Platform:         Windows
BuildConfig:      Release
Execution Env:    Native
Runtime Env:      Production
Runtimes installed:
  .NET runtime:     7.0.5
  .NET SDK:         Not found
  Default Python:   3.10.1
  Go:               Not found
  NodeJS:           Not found
  Rust:             Not found
Video adapter info:
  NVIDIA GeForce RTX 3060:
    Driver Version     31.0.15.5186
    Video Processor    NVIDIA GeForce RTX 3060
System GPU info:
  GPU 3D Usage       3%
  GPU RAM Usage      6.8 GiB
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

Matthew Dennis4-Apr-24 11:19

Matthew Dennis

4-Apr-24 11:19

Mike, you are correct, it must be a type. DirectML will not be displayed without whatever graphics driver installed on the Windows system being used.

"Mistakes are prevented by Experience. Experience is gained by making mistakes."

Joey War4-Apr-24 11:42

4-Apr-24 11:42

Does object detection yolov5.net is it normal to take 20% of a i7 6700 cpu even when it set to use GPU

Matthew Dennis4-Apr-24 11:50

Matthew Dennis

4-Apr-24 11:50

I have confirmed it is a typo in the code. Not the one you would expect, but it still causes the error.
I have fixed the code and it will be in the next release.

"Mistakes are prevented by Experience. Experience is gained by making mistakes."

Joey War4-Apr-24 22:36

YOLOv8 Fresh install on 2.6.2 -- TODO

4-Apr-24 22:36

Thank you

rdcrumbaker4-Apr-24 4:04

rdcrumbaker

4-Apr-24 4:04

What would this be?

08:59:27:
08:59:27:Started Object Detection (YOLOv8) module
09:00:19:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:00:19:Response rec'd from Object Detection (YOLOv8) command 'detect' (...8d4e22)

Everything installed successfully without error, but the YOLOv8 didn't automattically start, I had to start it.

Here is my SystemInfo:

Server version:   2.6.2
System:           Docker (Linux 5.10.102.1-microsoft-standard-WSL2 #1 SMP Wed Mar 2 00:30:59 UTC 2022)
Operating System: Linux (Ubuntu 22.04)
CPUs:             AMD Ryzen Threadripper 3960X 24-Core Processor (AMD)
                  1 CPU x 24 cores. 48 logical processors (x64)
GPU (Primary):    NVIDIA GeForce RTX 3070 (8 GiB) (NVIDIA) 
                  Driver: 551.23, CUDA: 12.4 (up to: 12.4), Compute: 8.6, cuDNN: 8.9.6
System RAM:       63 GiB
Platform:         Linux
BuildConfig:      Release
Execution Env:    Docker
Runtime Env:      Production
Runtimes installed:
  .NET runtime:     7.0.17
  .NET SDK:         Not found
  Default Python:   3.10.12
  Go:               Not found
  NodeJS:           Not found
  Rust:             Not found
Video adapter info:
System GPU info:
  GPU 3D Usage       25%
  GPU RAM Usage      7.5 GiB
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

modified 5-Apr-24 17:46pm.

Sean Ewington4-Apr-24 7:34

Sean Ewington

4-Apr-24 7:34

Thanks very much for your message. The YOLOv8 module isn't set to start automatically. What should happen is, once you start the module once, it should auto-start next time.

Thanks,
Sean Ewington
CodeProject

rdcrumbaker5-Apr-24 4:50

rdcrumbaker

5-Apr-24 4:50

OK, I get that it will restart on it's own.
However, what about these errors? This is a new install, uninstalled YOLOv8 and reinstalled it.

When it starts, I get the following (maybe I shouldn't be concerned about it...but maybe others are seeing it as well...or maybe you just need to know it)

Here is what I see - HINT: LOOK AT 9:45:19 timestamp :

09:44:20:Server: This is the latest version
09:44:21:
09:44:21:Module 'Object Detection (YOLOv8)' 1.4.2 (ID: ObjectDetectionYOLOv8)
09:44:21:Valid:         True
09:44:21:Module Path:   <root>/modules/ObjectDetectionYOLOv8
09:44:21:AutoStart:     True
09:44:21:Queue:         objectdetection_queue
09:44:21:Runtime:       python3.8
09:44:21:Runtime Loc:   Shared
09:44:21:FilePath:      detect_adapter.py
09:44:21:Start pause:   1 sec
09:44:21:Parallelism:   0
09:44:21:LogVerbosity:
09:44:21:Platforms:     all
09:44:21:GPU Libraries: installed if available
09:44:21:GPU Enabled:   enabled
09:44:21:Accelerator:
09:44:21:Half Precis.:  enable
09:44:21:Environment Variables
09:44:21:APPDIR            = <root>/modules/ObjectDetectionYOLOv8
09:44:21:CUSTOM_MODELS_DIR = <root>/modules/ObjectDetectionYOLOv8/custom-models
09:44:21:MODELS_DIR        = <root>/modules/ObjectDetectionYOLOv8/assets
09:44:21:MODEL_SIZE        = Medium
09:44:21:USE_CUDA          = True
09:44:21:YOLO_VERBOSE      = false
09:44:21:
09:44:21:Started Object Detection (YOLOv8) module
09:44:23:face.py: GPU in use: NVIDIA GeForce RTX 3070
09:45:19:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Response rec'd from Object Detection (YOLOv8) command 'detect' (...7832cb)
09:45:20:Response rec'd from Object Detection (YOLOv8) command 'detect' (...c4899c)
09:45:20:Response rec'd from Object Detection (YOLOv8) command 'detect' (...345625)
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:20:Object Detection (YOLOv8):  [AttributeError] : Traceback (most recent call last):
  File "/app/modules/ObjectDetectionYOLOv8/detect.py", line 147, in do_detection
    results            = detector.predict(img, imgsz=resolution, half=use_half_precision,
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/model.py", line 266, in predict
    self.predictor.setup_model(model=self.model, verbose=is_cli)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 341, in setup_model
    self.model = AutoBackend(
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 141, in __init__
    model = model.fuse(verbose=verbose) if fuse else model
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 176, in fuse
    delattr(m, "bn")  # remove batchnorm
  File "/app/modules/ObjectDetectionYOLOv8/bin/linux/python38/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1266, in __delattr__
    object.__delattr__(self, name)
AttributeError: bn
09:45:36:Response rec'd from Object Detection (YOLOv8) command 'detect' (...226f6d) ['Found chair, chair, tv']  took 13376ms

Sean Ewington5-Apr-24 5:32

Sean Ewington

5-Apr-24 5:32

Thank you kindly. We patched this issue once before, it looks like we have to patch it again.

Thanks,
Sean Ewington
CodeProject

Chris Maunder8-Apr-24 6:02

8-Apr-24 6:02

This is a threading issue with PyTorch. I've added a lock around the interpreter (really only needs to be around the fuse code, so there's scope to optimise this) which should help.

Out of interest, how many requests per second are you sending to CodeProject.AI?

cheers
Chris Maunder

rdcrumbaker8-Apr-24 6:05

rdcrumbaker

8-Apr-24 6:05

How do I get this information?

Yolo v8 will only use tiny or small on TPU -- Resolved

Eduard Băniceru8-Apr-24 22:43

Eduard Băniceru

8-Apr-24 22:43

I experience the same issue, YOLOv8 + ALPR on 2.6.2, when request count becomes fairly high. I have attached a log from Blue Iris showing requests and errors, as well as Event Viewer output.

Event Viewer:

Faulting application name: python.exe, version: 3.9.6150.1013, time stamp: 0x60d9eb23
Faulting module name: nvcuda64.dll, version: 31.0.15.5212, time stamp: 0x660c7129
Exception code: 0xc0000005
Fault offset: 0x00000000000bcdc0
Faulting process id: 0x0x6FE4
Faulting application start time: 0x0x1DA8A57F069CC87
Faulting application path: C:\Program Files\CodeProject\AI\runtimes\bin\windows\python39\python.exe
Faulting module path: C:\Windows\system32\DriverStore\FileRepository\nv_dispi.inf_amd64_268e85175aa9e991\nvcuda64.dll
Report Id: 38480e22-c755-469d-a9d9-0229903fe94c
Faulting package full name: 
Faulting package-relative application ID:

The real problem is... when it starts to behave like this (after "remove batchnorm" error), Cp.AI hardly recovers, there are crashes between 1-20 minutes, and in many cases YOLOv8 module stays down. I basically have to babysit CP.AI continuously in those cases.

Below, an excerpt from log with requests and timestamps (actually these were handled fine by CP.AI). All requests within a span of 3 seconds.

For what it's worth, the GPU is an RTX 3090.

11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...18f7a0) ['Found potted plant, potted plant, potted plant...']  took 28ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...da8d5a) ['Found person, boat, potted plant...']  took 53ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...b4e42b) ['No objects found']  took 31ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...967f3a) ['Found potted plant, potted plant, potted plant...']  took 86ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...3543c2) ['Found person']  took 38ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...e079b9) ['No objects found']  took 35ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...751f74) ['No plates found']  took 45ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...f10bb7) ['Found boat, potted plant, potted plant...']  took 121ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...cb0ff0) ['No objects found']  took 39ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...9010b6) ['No objects found']  took 45ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...7f1e6d) ['No plates found']  took 57ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...59eeec) ['Found potted plant, potted plant, boat...']  took 187ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...31d4ae) ['Found person']  took 74ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...a78bee) ['No objects found']  took 76ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...a8a7d3) ['No plates found']  took 85ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...c0a06b) ['Found potted plant, potted plant, potted plant...']  took 244ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...f17d45) ['No objects found']  took 51ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...56efa0) ['No objects found']  took 39ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...3c1aaf) ['No plates found']  took 51ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...85eb35) ['No objects found']  took 33ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...34894d) ['No objects found']  took 28ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...8c583c) ['No plates found']  took 41ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...25192a) ['No objects found']  took 16ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...c6ea2f) ['No plates found']  took 27ms
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'detect' (...d12720) ['Found boat, potted plant, potted plant...']  took 11ms
11:39:15:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...24a0d6) ['Found person']  took 10ms
11:39:15:Object Detection (YOLOv8): Detecting using license-plate
11:39:15:Response rec'd from Object Detection (YOLOv8) command 'custom' (...a7ac68) ['No objects found']  took 10ms
11:39:15:Response rec'd from License Plate Reader command 'alpr' (...1d93f7) ['No plates found']  took 18ms
11:39:16:Response rec'd from Object Detection (YOLOv8) command 'detect' (...f738a4) ['Found person, potted plant, potted plant...']  took 17ms
11:39:16:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:16:Response rec'd from Object Detection (YOLOv8) command 'custom' (...b850fe) ['Found person']  took 12ms
11:39:16:Object Detection (YOLOv8): Detecting using license-plate
11:39:16:Response rec'd from Object Detection (YOLOv8) command 'custom' (...0bc07e) ['No objects found']  took 9ms
11:39:16:Response rec'd from License Plate Reader command 'alpr' (...4b2cb2) ['No plates found']  took 17ms
11:39:17:Response rec'd from Object Detection (YOLOv8) command 'detect' (...05f9ec) ['Found potted plant, boat, person...']  took 18ms
11:39:17:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:17:Response rec'd from Object Detection (YOLOv8) command 'custom' (...20adb8) ['Found person']  took 12ms
11:39:17:Object Detection (YOLOv8): Detecting using license-plate
11:39:17:Response rec'd from Object Detection (YOLOv8) command 'custom' (...5c0901) ['No objects found']  took 11ms
11:39:17:Response rec'd from License Plate Reader command 'alpr' (...023b91) ['No plates found']  took 19ms
11:39:18:Response rec'd from Object Detection (YOLOv8) command 'detect' (...f213b0) ['Found person, potted plant, potted plant...']  took 18ms
11:39:18:Object Detection (YOLOv8): Detecting using ipcam-general
11:39:18:Response rec'd from Object Detection (YOLOv8) command 'custom' (...c02e67) ['Found person']  took 15ms
11:39:18:Object Detection (YOLOv8): Detecting using license-plate
11:39:18:Response rec'd from Object Detection (YOLOv8) command 'custom' (...3e3aaf) ['No objects found']  took 13ms
11:39:18:Response rec'd from License Plate Reader command 'alpr' (...8d3f62) ['No plates found']  took 21ms

If you need more details or any information, please let me know.

cse12343-Apr-24 2:44

cse1234

3-Apr-24 2:44

Running 2.1.6 version of the Coral object detection which works fine using tiny or small object size, however when switching to medium or large the TPU is no longer found and it rolls back to CPU instead. Enclosed is the error output from the console. I have fully uninstalled / reinstalled both CP and the module with the same result.

08:38:21:Module 'Object Detection (Coral)' 2.1.6 (ID: ObjectDetectionCoral)
08:38:21:Valid:         True
08:38:21:Module Path:   <root>\modules\ObjectDetectionCoral
08:38:21:AutoStart:     True
08:38:21:Queue:         objectdetection_queue
08:38:21:Runtime:       python3.9
08:38:21:Runtime Loc:   Local
08:38:21:FilePath:      objectdetection_coral_adapter.py
08:38:21:Pre installed: False
08:38:21:Start pause:   1 sec
08:38:21:Parallelism:   1
08:38:21:LogVerbosity:
08:38:21:Platforms:     all
08:38:21:GPU Libraries: installed if available
08:38:21:GPU Enabled:   enabled
08:38:21:Accelerator:
08:38:21:Half Precis.:  enable
08:38:21:Environment Variables
08:38:21:CPAI_CORAL_MODEL_NAME = YOLOv8
08:38:21:CPAI_CORAL_MULTI_TPU  = True
08:38:21:MODELS_DIR            = <root>\modules\ObjectDetectionCoral\assets
08:38:21:MODEL_SIZE            = medium
08:38:21:
08:38:21:Started Object Detection (Coral) module
08:38:24:objectdetection_coral_adapter.py: ERROR:root:TFLite file C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\assets\yolov5m-int8_edgetpu.tflite doesn't exist
08:38:24:objectdetection_coral_adapter.py: WARNING:root:Exception creating interpreter: [Errno 2] No such file or directory: 'C:\\Program Files\\CodeProject\\AI\\modules\\ObjectDetectionCoral\\assets\\yolov5m-int8_edgetpu.tflite'
08:38:24:objectdetection_coral_adapter.py: Exception ignored in: 
08:38:24:objectdetection_coral_adapter.py: Traceback (most recent call last):
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 352, in __del__
08:38:24:objectdetection_coral_adapter.py:     self.delete()
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 375, in delete
08:38:24:objectdetection_coral_adapter.py:     self._halt_interpreters(q_idx)
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 357, in _halt_interpreters
08:38:24:objectdetection_coral_adapter.py:     for i in self.interpreters[seg_idx]:
08:38:24:objectdetection_coral_adapter.py: IndexError: list index out of range
08:38:24:objectdetection_coral_adapter.py: WARNING:root:No Coral TPUs found or able to be initialized. Using CPU.
08:38:24:objectdetection_coral_adapter.py: ERROR:root:TFLite file C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\assets\yolov5m-int8.tflite doesn't exist
08:38:24:objectdetection_coral_adapter.py: WARNING:root:Unable to create interpreter for CPU using edgeTPU library: [Errno 2] No such file or directory: 'C:\\Program Files\\CodeProject\\AI\\modules\\ObjectDetectionCoral\\assets\\yolov5m-int8.tflite'
08:38:24:objectdetection_coral_adapter.py: Exception ignored in: 
08:38:24:objectdetection_coral_adapter.py: Traceback (most recent call last):
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 352, in __del__
08:38:24:objectdetection_coral_adapter.py:     self.delete()
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 375, in delete
08:38:24:objectdetection_coral_adapter.py:     self._halt_interpreters(q_idx)
08:38:24:objectdetection_coral_adapter.py:   File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\tpu_runner.py", line 357, in _halt_interpreters
08:38:24:objectdetection_coral_adapter.py:     for i in self.interpreters[seg_idx]:
08:38:24:objectdetection_coral_adapter.py: IndexError: list index out of range
08:38:29:objectdetection_coral_adapter.py: TPU detected
08:38:29:objectdetection_coral_adapter.py: Attempting multi-TPU initialisation
08:38:29:objectdetection_coral_adapter.py: Failed to init multi-TPU. Falling back to single TPU.
08:38:29:objectdetection_coral_adapter.py: Unable to find or initialise the Coral TPU. Falling back to CPU-only.
08:38:29:objectdetection_coral_adapter.py: Error creating interpreter: Could not open 'C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\assets\yolov5m-int8.tflite'.
08:38:29:objectdetection_coral_adapter.py: Using CPU

modified 5-Apr-24 17:46pm.

Re: Yolo v8 will only use tiny or small on TPU

Chris Maunder3-Apr-24 6:51

Re: Yolo v8 will only use tiny or small on TPU -- Resolved

3-Apr-24 6:51

Which version of CodeProject.AI server?

cheers
Chris Maunder

Member 162363773-Apr-24 17:39

Member 16236377

3-Apr-24 17:39

There's a bug in the current version that the YOLOv8 medium asset file name is incorrect. You can see from the error log that somehow it is pointing to a yolov5m-int8 asset.

ERROR:root:TFLite file C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\assets\yolov5m-int8_edgetpu.tflite doesn't exist

You have to manually correct it in the option.py file. The correct asset name should be yolov8m_416_640px.tflite

modified 5-Apr-24 17:47pm.

Re: Yolo v8 will only use tiny or small on TPU -- Resolved

Chris Maunder4-Apr-24 3:37

Re: Yolo v8 will only use tiny or small on TPU -- Resolved

4-Apr-24 3:37

This has been fixed in the latest.

cheers
Chris Maunder

modified 5-Apr-24 17:47pm.

Member 162363774-Apr-24 8:31

Member 16236377

4-Apr-24 8:31

Coral version 2.2.0 is pointing to yolov8m-int8.tflite, which is still causing error. It should be yolov8m__416_640px.tflite.

modified 5-Apr-24 17:47pm.

Re: Yolo v8 will only use tiny or small on TPU -- Resolved

cse12344-Apr-24 13:52

cse1234

4-Apr-24 13:52

Thank you !

modified 5-Apr-24 17:47pm.

ALPR Requirement -- Suggestion/Question

Member 158762412-Apr-24 22:37

Member 15876241

2-Apr-24 22:37

Hi Chris,

I have a question/suggestion. As I've been manually installing the dependencies myself, I encountered an issue when trying to install the "requirements.windows.cuda11_8.txt" for ALPR. I received the following error:

(venv) C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python39\venv\Scripts>cd C:\Users\User\Desktop\CodeProjectAI Files

(venv) C:\Users\User\Desktop\CodeProjectAI Files>pip download -r requirements.windows.cuda11_8.txt
Looking in indexes: https://mirror.baidu.com/pypi/simple
Collecting paddlepaddle-gpu==2.6.0 (from -r requirements.windows.cuda11_8.txt (line 5))
  Using cached https://mirror.baidu.com/pypi/packages/37/9f/69921f0e4a5ef25291c77c16775457075559b0f01f7ebcdc1ea66abf2451/paddlepaddle_gpu-2.6.0-cp39-cp39-win_amd64.whl (476.3 MB)
Collecting paddleocr==2.7.0.3 (from -r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/8f/d0/1a2f9430f61781beb16556182baa938e8f93c8b46c27ad5865a5655fae05/paddleocr-2.7.0.3-py3-none-any.whl (465 kB)
     ---------------------------------------- 465.7/465.7 kB 728.7 kB/s eta 0:00:00
Collecting imutils (from -r requirements.windows.cuda11_8.txt (line 10))
  Downloading https://mirror.baidu.com/pypi/packages/3f/d3/ecb4d108f6c1041d24842a345ee0123cd7f366ba75cf122601e856d42ba2/imutils-0.5.4.tar.gz (17 kB)
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Installing backend dependencies ... done
  Preparing metadata (pyproject.toml) ... done
Collecting Pillow<10.0.0 (from -r requirements.windows.cuda11_8.txt (line 11))
  Using cached https://mirror.baidu.com/pypi/packages/69/72/48cc52bff8731cf72bc4101e34dc44807a410c171f921afb582a511da50e/Pillow-9.5.0-cp39-cp39-win_amd64.whl (2.5 MB)
Collecting opencv-python (from -r requirements.windows.cuda11_8.txt (line 12))
  Downloading https://mirror.baidu.com/pypi/packages/c7/ec/9dabb6a9abfdebb3c45b0cc52dec901caafef2b2c7e7d6a839ed86d81e91/opencv_python-4.9.0.80-cp37-abi3-win_amd64.whl (38.6 MB)
     ---------------------------------------- 38.6/38.6 MB 5.8 MB/s eta 0:00:00
Collecting numpy (from -r requirements.windows.cuda11_8.txt (line 13))
  Downloading https://mirror.baidu.com/pypi/packages/b5/42/054082bd8220bbf6f297f982f0a8f5479fcbc55c8b511d928df07b965869/numpy-1.26.4-cp39-cp39-win_amd64.whl (15.8 MB)
     ---------------------------------------- 15.8/15.8 MB 3.8 MB/s eta 0:00:00
Collecting httpx (from paddlepaddle-gpu==2.6.0->-r requirements.windows.cuda11_8.txt (line 5))
  Downloading https://mirror.baidu.com/pypi/packages/41/7b/ddacf6dcebb42466abd03f368782142baa82e08fc0c1f8eaa05b4bae87d5/httpx-0.27.0-py3-none-any.whl (75 kB)
     ---------------------------------------- 75.6/75.6 kB 1.4 MB/s eta 0:00:00
Collecting decorator (from paddlepaddle-gpu==2.6.0->-r requirements.windows.cuda11_8.txt (line 5))
  Downloading https://mirror.baidu.com/pypi/packages/d5/50/83c593b07763e1161326b3b8c6686f0f4b0f24d5526546bee538c89837d6/decorator-5.1.1-py3-none-any.whl (9.1 kB)
Collecting astor (from paddlepaddle-gpu==2.6.0->-r requirements.windows.cuda11_8.txt (line 5))
  Downloading https://mirror.baidu.com/pypi/packages/c3/88/97eef84f48fa04fbd6750e62dcceafba6c63c81b7ac1420856c8dcc0a3f9/astor-0.8.1-py2.py3-none-any.whl (27 kB)
Collecting opt-einsum==3.3.0 (from paddlepaddle-gpu==2.6.0->-r requirements.windows.cuda11_8.txt (line 5))
  Downloading https://mirror.baidu.com/pypi/packages/bc/19/404708a7e54ad2798907210462fd950c3442ea51acc8790f3da48d2bee8b/opt_einsum-3.3.0-py3-none-any.whl (65 kB)
     ---------------------------------------- 65.5/65.5 kB 1.8 MB/s eta 0:00:00
Collecting protobuf<=3.20.2,>=3.1.0 (from paddlepaddle-gpu==2.6.0->-r requirements.windows.cuda11_8.txt (line 5))
  Downloading https://mirror.baidu.com/pypi/packages/95/ec/410f21dd62810df692ced49ce7c7777c8d2ad239fdd26fcd72d5c5f42b7e/protobuf-3.20.2-cp39-cp39-win_amd64.whl (904 kB)
     ---------------------------------------- 904.2/904.2 kB 6.3 MB/s eta 0:00:00
Collecting shapely (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/45/1c/bf88b078e6e148ecb4d8e334ab94e01df383ead09d17e6c60fb90b7bbc01/shapely-2.0.3-cp39-cp39-win_amd64.whl (1.4 MB)
     ---------------------------------------- 1.4/1.4 MB 7.6 MB/s eta 0:00:00
Collecting scikit-image (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/3d/97/a09a526eee08683922ca2e37c69742ffdcc879ee40bfe29d3e3d55e821c0/scikit_image-0.22.0-cp39-cp39-win_amd64.whl (24.5 MB)
     ---------------------------------------- 24.5/24.5 MB 3.5 MB/s eta 0:00:00
Collecting imgaug (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/66/b1/af3142c4a85cba6da9f4ebb5ff4e21e2616309552caca5e8acefe9840622/imgaug-0.4.0-py2.py3-none-any.whl (948 kB)
     ---------------------------------------- 948.0/948.0 kB 2.2 MB/s eta 0:00:00
Collecting pyclipper (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/97/d7/78140d011dbe7887a8205222e0ddfc0fc60a2b6223202b4504de2ebda3e1/pyclipper-1.3.0.post5-cp39-cp39-win_amd64.whl (108 kB)
     ---------------------------------------- 108.6/108.6 kB 2.1 MB/s eta 0:00:00
Collecting lmdb (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/ff/59/6b14c0d05a5366a558dbde51339062d77aa9f9af132a478860609ba69943/lmdb-1.4.1-cp39-cp39-win_amd64.whl (105 kB)
     ---------------------------------------- 105.9/105.9 kB 2.0 MB/s eta 0:00:00
Collecting tqdm (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/2a/14/e75e52d521442e2fcc9f1df3c5e456aead034203d4797867980de558ab34/tqdm-4.66.2-py3-none-any.whl (78 kB)
     ---------------------------------------- 78.3/78.3 kB 2.2 MB/s eta 0:00:00
Collecting visualdl (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/ea/b5/37726c750a4f4598660998327c3566b2d2ed5a1a5f44e9f0dde875602447/visualdl-2.5.3-py3-none-any.whl (6.3 MB)
     ---------------------------------------- 6.3/6.3 MB 7.1 MB/s eta 0:00:00
Collecting rapidfuzz (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/29/60/186c0af8fa54df1e3ff68cfc503692382a91b31b1e85df811eb7e79fb7ef/rapidfuzz-3.7.0-cp39-cp39-win_amd64.whl (1.6 MB)
     ---------------------------------------- 1.6/1.6 MB 7.0 MB/s eta 0:00:00
Collecting opencv-python (from -r requirements.windows.cuda11_8.txt (line 12))
  Downloading https://mirror.baidu.com/pypi/packages/cf/09/b24c266cd61ddeed101b90c92a26f54d060b06f4a1b102eb891576d6e9e2/opencv_python-4.6.0.66-cp36-abi3-win_amd64.whl (35.6 MB)
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Collecting opencv-contrib-python<=4.6.0.66 (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/63/0b/6ef1acbaa21e5245c85a42f9f0ecfaf2e7420b24615a00f0eee170328e6b/opencv_contrib_python-4.6.0.66-cp36-abi3-win_amd64.whl (42.5 MB)
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Collecting cython (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/ba/a4/457fdf9a6cb89fbb3a9c51a3cfb5fb6ecd36eabae6abe077784be95fc121/Cython-3.0.10-cp39-cp39-win_amd64.whl (2.8 MB)
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Collecting lxml (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/fa/49/b430692c850591cfa9b3b66864b4d03c806705374da977a6c37b4e2e621a/lxml-5.2.1-cp39-cp39-win_amd64.whl (3.8 MB)
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Collecting premailer (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
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Collecting attrdict (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
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Collecting PyMuPDF<1.21.0 (from paddleocr==2.7.0.3->-r requirements.windows.cuda11_8.txt (line 8))
  Downloading https://mirror.baidu.com/pypi/packages/f2/a2/13216bcc975c107322a62536452116f9c81eb305c9bdfdc460e5d38efc1c/PyMuPDF-1.20.2-cp39-cp39-win_amd64.whl (6.6 MB)
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INFO: pip is looking at multiple versions of paddleocr to determine which version is compatible with other requirements. This could take a while.
ERROR: Cannot install -r requirements.windows.cuda11_8.txt (line 5), -r requirements.windows.cuda11_8.txt (line 8) and Pillow<10.0.0 because these package versions have conflicting dependencies.

The conflict is caused by:
    The user requested Pillow<10.0.0
    paddlepaddle-gpu 2.6.0 depends on Pillow
    paddleocr 2.7.0.3 depends on Pillow>=10.0.0

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

To resolve this, I changed the Pillow version from "Pillow<10.0.0" to "Pillow>10.0.0", and then it successfully downloaded and installed the dependencies without any problems. My question is: Is this "requirements.txt" file used when the module is being installed? If so, perhaps the Pillow version specified within it should be updated.

I'm not sure if this change affects anything else, but I thought I should bring it up to let you know.

Re: ALPR Requirement -- Suggestion/Question

Chris Maunder3-Apr-24 1:39