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[mob][photos] Use normalized embeddings in complete clustering

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This commit is contained in:
laurenspriem 2024-05-09 14:51:59 +05:30
parent 8c373857a2
commit 6eb34937b8
1 changed files with 7 additions and 2 deletions
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9
mobile/lib/services/machine_learning/face_ml/face_clustering/face_clustering_service.dart
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@ -854,7 +854,10 @@ class FaceClusteringService {
.toList();
final count = clusterIdToFaceInfos[clusterId]!.length;
final Vector meanEmbedding = embeddings.reduce((a, b) => a + b) / count;
clusterIdToMeanEmbeddingAndWeight[clusterId] = (meanEmbedding, count);
final Vector meanEmbeddingNormalized =
meanEmbedding / meanEmbedding.norm();
clusterIdToMeanEmbeddingAndWeight[clusterId] =
(meanEmbeddingNormalized, count);
}
// Now merge the clusters that are close to each other, based on mean embedding
@ -889,8 +892,10 @@ class FaceClusteringService {
final count2 = clusterIdToMeanEmbeddingAndWeight[clusterID2]!.$2;
final weight1 = count1 / (count1 + count2);
final weight2 = count2 / (count1 + count2);
final weightedMean = mean1 * weight1 + mean2 * weight2;
final weightedMeanNormalized = weightedMean / weightedMean.norm();
clusterIdToMeanEmbeddingAndWeight[clusterID1] = (
mean1 * weight1 + mean2 * weight2,
weightedMeanNormalized,
count1 + count2,
);
clusterIdToMeanEmbeddingAndWeight.remove(clusterID2);