Object Detection on Raspberry Pi 4

TensorFlow General Discussion
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I’m trying to import tflite-support.task on Raspberry Pi 4. However, I’m getting:
ModuleNotFoundError: No module named 'tflite_support.task'
Python version is 3.11.2 and tflite-support is 0.1.0a1.

I did some research and found that 0.1.0a1 version doesn’t include task library but the requirement for the object detection model in the GitHub repository is tflite-support>=0.4.2.

When I try to install the dependency via pip:
python -m pip install --upgrade tflite-support==0.4.4,

the output is:
ERROR: Could not find a version that satisfies the requirement tflite-support==0.4.4 (from versions: 0.1.0a0.dev3, 0.1.0a0.dev4, 0.1.0a0.dev5, 0.1.0a0, 0.1.0a1) ERROR: No matching distribution found for tflite-support==0.4.4

I’m kind of confused. Any idea of fixing the problem?

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  1. You’re using Python 3.11.2. Sometimes, newer Python versions have limited support for certain libraries, especially if the libraries are not updated frequently. TensorFlow and its related packages usually lag behind the latest Python release. It’s often safer to use Python 3.7 or 3.8, which are more commonly supported in machine learning libraries. Consider downgrading your Python version.
  2. Check Available tflite-support Versions: The error message suggests that only early alpha versions (0.1.0aX) of tflite-support are available for your current setup. This could be due to the Python version or the architecture of the Raspberry Pi.
  3. Alternative Installation Methods: Sometimes, installing via pip doesn’t provide the latest versions due to compatibility checks. You can try a few things:
  • Install a Pre-compiled Wheel: Search for a pre-compiled wheel (.whl file) of tflite-support that is compatible with your system. This can sometimes bypass version issues found in PyPI.
  • Build From Source: If a pre-compiled wheel is not available, consider building the package from source. This requires more effort but can solve compatibility issues.
  1. Check for System Compatibility: Ensure that your Raspberry Pi’s OS and architecture are compatible with the version of tflite-support you’re trying to install. Some packages might have limited support for ARM architecture.
  2. Use TensorFlow Lite API Directly: If you can’t resolve the tflite-support issue, consider using the TensorFlow Lite API directly for object detection, although this might require more coding and setup.
  3. Explore Alternatives: If your primary goal is object detection on a Raspberry Pi, there might be alternative libraries or approaches that are more straightforward to set up on your device.
  4. Community Support: Check forums like GitHub issues, Stack Overflow, or Raspberry Pi communities. Others might have faced and solved similar issues.
  5. Update Raspberry Pi: Ensure your Raspberry Pi is updated to the latest OS version and has all the necessary dependencies for machine learning tasks.
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