feat(cli): add rfdetr export subcommand for ONNX/TFLite export

[omkar-334]

What does this PR do?

Adds a command-line path for exporting trained RF-DETR checkpoints, resolving the long-standing TODO in rfdetr/export/main.py to expose TFLite export (and its quantization / calibration options) from the shell. Until now, export was reachable only from Python via RFDETR.export(format=...).

Rather than extend the legacy argparser, this adds a proper rfdetr export subcommand that wraps RFDETR.export (TFLite already worked in Python; this surfaces it to the CLI).

Related to #1024

Type of Change

• New feature (non-breaking change that adds functionality)

Testing

• I have tested this change locally
• I have added/updated tests for this change

Test details:
I verified the training and export end to end -> Train a checkpoint, run rfdetr export --checkpoint <ckpt> --format onnx, and the exported rfdetr-nano.onnx loads and runs in onnxruntime (dets / labels outputs).

Checklist

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code where necessary, particularly in hard-to-understand areas
• My changes generate no new warnings or errors
• I have updated the documentation accordingly (if applicable)

Additional Context

export (jsonargparse) and fit/validate/test/predict (LightningCLI) are two different parsers, so a single rfdetr command needs a thin root to choose between them. Treating LightningCLI as the root would force the [train] extra on export-only users and produce a stitched, two-part top-level --help. The root therefore owns top-level help and dispatch and delegates to each backend, which leaves LightningCLI's training semantics untouched and keeps per-command rfdetr <command> --help backend-native.

Usage

# install (no [train] / PyTorch Lightning needed for export)
pip install "rfdetr[cli,onnx]"          # ONNX
pip install "rfdetr[cli,onnx,tflite]"   # TFLite

# discover
rfdetr --help            # lists fit/validate/test/predict + the export subcommand
rfdetr export --help     # all flags, derived from RFDETR.export

# ONNX
rfdetr export --checkpoint output/checkpoint_best_total.pth --format onnx --output_dir output

# TFLite (FP32 + FP16)
rfdetr export --checkpoint output/checkpoint_best_total.pth --format tflite --output_dir output

# TFLite INT8 with calibration images
rfdetr export --checkpoint output/checkpoint_best_total.pth --format tflite --quantization int8 --calibration_data path/to/val_images/ --max_images 100 --output_dir output

# flags from a YAML file
rfdetr export --config export.yaml

[codecov]

Codecov Report

❌ Patch coverage is 92.30769% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 77%. Comparing base (27b9d23) to head (7e70ea9).

❌ Your project check has failed because the head coverage (77%) is below the target coverage (95%). You can increase the head coverage or adjust the target coverage.

Additional details and impacted files

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  Lines         9047    9096   +49     
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+ Hits          6979    7024   +45     
- Misses        2068    2072    +4     

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[Borda]

Lte's do not add it until it is stable, so far I tested TFlite, the predictions were quite questionable...