Enable TensorFlow ops for --nms and --agnostic-nms

[leeflix]

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Enhancements to TensorFlow Lite (TFLite) export functionality in YOLOv5.

📊 Key Changes

• Added nms and agnostic_nms arguments to export_tflite function.
• Updated representative dataset generation by setting ncalib to a default value of 100.
• Appended tf.lite.OpsSet.SELECT_TF_OPS to supported operations when nms or agnostic_nms is enabled during TFLite export.

🎯 Purpose & Impact

• 🎨 The introduction of nms (Non-Maximum Suppression) and agnostic_nms parameters aims to allow users more control over the post-processing steps during TFLite model conversion, potentially leading to more efficient on-device inference.
• 🔍 Setting a default ncalib value helps standardize the quantization calibration step, which can improve the quality of the int8 quantized models.
• 🚀 Including SELECT_TF_OPS supports a wider range of TensorFlow operations when exporting to TFLite, thereby enhancing model compatibility and performance on a broader set of devices.
• 🧿 Users may experience improvements in model accuracy and efficiency, especially for edge devices and mobile applications leveraging TFLite models.

[github-actions]

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