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Deep neural networks thrive on abundant labeled data, yet obtaining large‑scale, high‑quality annotated datasets remains a bottleneck across many domains. Synthetic data generation offers a promising alternative, but existing tools often suffer from limited realism, rigid pipelines, or insufficient configurability.
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