Drop 37 ambiguous/badly-cropped samples where model disagrees with label

Clean labels using Qwen3-VL-4B VLM verification

fix gear 4: replace noisy labels with 300 augmented from clean reference crop

v3: deep clean via per-source cross-val + manual curation

add per-label verification composites and cleaning scripts

clean: remove 445 noisy train + 99 noisy val samples via ensemble model

val: keep only 2 MNIST per digit (340→20), focus val on real racing

move 20 more racing 4s into val set (19→39 real racing samples)

cleanup: remove temp files, fix find_label_issues.py guard

clean: fix 36 mislabels, remove 122 ambiguous samples via cleanlab

fix: build_dataset.py writes HF Image feature type

fix: restore HF Image feature type in parquet schema

v2: add new sources, extraction pipeline, better train/val split

Update README with full dataset documentation

Initial dataset: racing gear digits + MNIST supplement

initial commit