TensorFlow Lite model deployment results about hub HOT 3 CLOSED

👋 Hello @jamesleech89, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

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from hub.

@jamesleech89 hello! It sounds like you're experiencing discrepancies between your model's predictions in TensorFlow Lite format compared to its performance via the Ultralytics API and preview tab. This can happen due to several reasons:

1. Quantization: If your TensorFlow Lite model is quantized, it might introduce slight precision losses, affecting the model's predictions. This is a common trade-off for the reduced model size and faster inference times on edge devices.

2. Preprocessing and Postprocessing: Ensure that the image preprocessing (resizing, normalization) and postprocessing (applying confidence thresholds and non-maximum suppression) steps are consistent across all platforms. Differences in these steps can lead to varied results.

3. Model Version: Double-check that the TensorFlow Lite model is exported from the exact same model version and weights as the one used in the Ultralytics preview tab and API.

4. Framework Differences: Sometimes, subtle differences in how frameworks handle operations can lead to discrepancies. TensorFlow Lite might handle certain operations differently than PyTorch, which Ultralytics models are originally implemented in.

For a detailed guide on exporting models and ensuring consistency across different platforms, please refer to the Ultralytics HUB Docs. If the issue persists, consider providing more details about the preprocessing and postprocessing steps, along with any specific settings used during the TensorFlow Lite model export. This will help in diagnosing the issue more accurately. 😊

from hub.

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

• Docs: https://docs.ultralytics.com
• HUB: https://hub.ultralytics.com
• Community: https://community.ultralytics.com

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

from hub.