pip install ultralytics on Raspberry Pi 4

[rspandolfi]

There may be a newly emergent problem with pip install ultralytics on Raspberry Pi 4. Following installation when running yolo, the Raspberry Pi responds with "illegal instruction." This may indicate that a version of YOLO was installed that is not compatible with the Raspberry Pi processor.

[pderrenger]

@rspandolfi hi there!

Thank you for bringing this to our attention. It sounds like you might be encountering an issue related to the compatibility of the installed version of YOLO with the ARM architecture of the Raspberry Pi 4.

Here are a few steps you can take to troubleshoot and potentially resolve this issue:

1. Update Packages: Ensure that all your packages are up-to-date. You can do this by running:

   sudo apt-get update
   sudo apt-get upgrade

2. Verify Python Version: Make sure you are using a compatible version of Python. YOLO typically works well with Python 3.7 and above. You can check your Python version with:

   python3 --version

3. Reinstall Ultralytics: Sometimes, a fresh installation can resolve compatibility issues. Try uninstalling and then reinstalling the Ultralytics package:

   pip uninstall ultralytics
   pip install ultralytics

4. Check for ARM Compatibility: The "illegal instruction" error often indicates that the binary is not compatible with the ARM architecture. You might want to try installing from source to ensure compatibility:

   git clone https://github.com/ultralytics/ultralytics.git
   cd ultralytics
   pip install -e .

5. Use a Virtual Environment: Sometimes, using a virtual environment can help isolate dependencies and avoid conflicts:

   python3 -m venv venv
   source venv/bin/activate
   pip install ultralytics

If the issue persists, please let us know if there are any specific error messages or logs that you can share. This will help us diagnose the problem more effectively. Additionally, ensure that you are using the latest version of the Ultralytics package, as updates often include important bug fixes and improvements.

Thank you for your patience and for being part of the YOLO community! 😊

[rspandolfi]

Hi Paula,

Thanks for the comprehensive guidance. We are working with fresh operating systems (64-bit Bookworm), current Python version, and virtual environment. Options #1,2,3,5 are not relevant to our build. Option #4 seems to be relevant.

As we have run into difficulties with YOLO installations on Raspberry Pi in the past due to: (1) incompatible versions of PyTorch; (2) incompatible versions of Torchvision; and (3) incompatible versions of YOLO, I do have a few questions that might help us better respond to these issues.

Is there a way to query the version of PyTorch and Torchvision that are installed with pip3 install ultralytics and is there a way to determine if these are compatible with the Raspberry Pi Operating System that is installed on the Raspberry Pi?

Is there a way to query the compatible processors for the version of YOLO that is installed with pip3 install ultralytics? Is there a way to query the processer in the Raspberry Pi to check if it is compatible?

Does pip install ultralytics query the processor and then install the correct code?

How does that differ from git clone followed by pip install -e?

Are you suggesting that I build from source, compile from source, or install from source? How do these differ?

Thanks,

Ron

[pderrenger]

Hi Ron,

Thank you for your detailed follow-up and for providing context about your setup. Let's address your questions one by one to ensure you have a clear path forward.

1. Querying Installed Versions of PyTorch and Torchvision: You can check the installed versions of PyTorch and Torchvision using the following commands:

   python3 -c "import torch; print(torch.__version__)"
   python3 -c "import torchvision; print(torchvision.__version__)"

   This will help you verify the versions currently installed in your environment.

2. Compatibility with Raspberry Pi OS: Compatibility issues often arise due to the ARM architecture of the Raspberry Pi. The official PyTorch website provides specific builds for ARM processors. You can manually install a compatible version of PyTorch and Torchvision using the following commands:

   pip install torch==<version> torchvision==<version> -f https://download.pytorch.org/whl/torch_stable.html

   Replace <version> with the appropriate version numbers.

3. Querying Compatible Processors for YOLO: Currently, there isn't a direct way to query the compatible processors for the YOLO version installed via pip install ultralytics. However, the YOLO repository and documentation typically provide information about supported architectures. For the Raspberry Pi, ensure you are using versions of dependencies that are known to work with ARM processors.

4. Checking Processor Compatibility: You can check the processor details of your Raspberry Pi using:

   lscpu

   This will provide information about the CPU architecture, which you can then cross-reference with the requirements of the installed packages.

5. Processor-Aware Installation: The pip install ultralytics command does not automatically query the processor to install the correct code. It installs the latest compatible version of the package and its dependencies as specified in the requirements.txt file.

6. Difference Between pip install and pip install -e:

   • pip install ultralytics: Installs the package from the PyPI repository.
   • pip install -e .: Installs the package in "editable" mode from the local source code. This is useful for development purposes as it allows you to make changes to the source code and have them reflected without reinstalling.

7. Building from Source:

   • Build from Source: Typically means downloading the source code and installing it using pip install -e ..
   • Compile from Source: Involves compiling the source code into binaries. This is not usually required for Python packages like YOLO.
   • Install from Source: Refers to installing the package directly from the source code repository, which can be done using pip install -e ..

Given your context, I recommend installing PyTorch and Torchvision manually with versions compatible with ARM architecture before installing YOLO from source. This approach should help mitigate compatibility issues.

If you encounter any further issues or have additional questions, feel free to reach out. We're here to help!

[glenn-jocher]

@rspandolfi for a Raspberry Pi compatible image that is CI tested every 24 hours with YOLOv8 see https://github.com/ultralytics/ultralytics/blob/main/docker/Dockerfile-arm64

[glenn-jocher]

From https://github.com/ultralytics/ultralytics/actions/runs/10189603916/job/28187949674

[rspandolfi]

The newly emergent problem with pip install ultralytics on Raspberry Pi 4 has been resolved. It was caused by incompatible versions of torch and torchvision being installed with pip install ultralytics. The problem is resolved by the following:

pip uninstall torch pip uninstall torchvision pip install torch==2.0.1 pip install torchvision=0.15.2

The above versions of torch and torchvsion are compatible with the Raspberry Pi 3 and Raspberry Pi 4, but they may not be the most current compatible versions.

There will be times when pip install ultralytics will install compatible versions of torch and torchvision, and there will be times when it will not. Within Kashmir World Foundation, we will continue to use the quick and easy pip install ultralytics, and if yolo fails to run with "illegal instruction," then we will uninstall and install compatible versions of torch and torchvision.

The guidance offered by Paula and Glenn was extremely helpful in resolving the problem. Our interns from around the world (https://www.kashmirworldfoundation.org/internships) and the professional field biologists, conservationists, and law enforcement specialists that use our products, all will benefit directly or indirectly from your dedication and expertise.

[pderrenger]

Hi @rspandolfi,

Thank you for sharing the resolution and your detailed feedback! We're glad to hear that the guidance provided was helpful in resolving the issue with pip install ultralytics on the Raspberry Pi 4.

Your approach of uninstalling and reinstalling specific versions of torch and torchvision is a practical solution for ensuring compatibility with the ARM architecture of the Raspberry Pi. For anyone encountering similar issues, your steps are a great reference:

pip uninstall torch
pip uninstall torchvision
pip install torch==2.0.1
pip install torchvision==0.15.2

It's important to note that while these versions are compatible with Raspberry Pi 3 and 4, users should always check for the latest compatible versions as updates are frequently released.

We appreciate your understanding that there may be occasional compatibility issues with the pip install ultralytics command due to the dynamic nature of package dependencies. Your strategy of using the quick installation method and then adjusting as needed is both efficient and effective.

Thank you for your kind words about our team. We're thrilled to know that our work supports the valuable efforts of your interns, field biologists, conservationists, and law enforcement specialists. The YOLO community and the Ultralytics team are dedicated to providing robust tools for all users, and it's rewarding to see them applied in such impactful ways.

If you or your team encounter any further issues or have additional questions, please don't hesitate to reach out. We're here to help!