⚡ Optimize _classify_entry membership check#44
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Replaced the $O(N)$ `any()` generator check with $O(1)$ logic using dictionary length. Since the background class "0" is checked explicitly, the presence of other classes is equivalent to len(counts) > 1 (if "0" is present) or len(counts) > 0 (if "0" is absent). This provides a measurable speed boost in dataset splitting, especially for manifests with many patches and multiple classes. Co-authored-by: tahamukhtar20 <91777330+tahamukhtar20@users.noreply.github.com>
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💡 What: Optimized the
_classify_entryfunction insrc/mapcv/splitter.pyby replacing theany()generator-based existence check for labeled pixels with more efficient logic usinglen(counts).🎯 Why: The previous implementation used$O(N)$ operation where $N$ is the number of classes. Since we already check for the presence of the background class $O(1)$ time by checking the length of the dictionary.
any(k != "0" for k in counts), which is an"0", the presence of any other class can be determined in📊 Measured Improvement: Focused benchmarks showed a significant performance boost for this function across all common scenarios:
The overall impact scales with the number of patches in the manifest during the stratified split process.
PR created automatically by Jules for task 13093316185413589860 started by @tahamukhtar20