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comment out erroring used code

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Abhinav 2023-01-20 21:16:39 +05:30
parent 3b183bbb00
commit 9073760799
1 changed files with 39 additions and 42 deletions
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81
src/utils/machineLearning/clustering.ts
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@ -1,27 +1,24 @@
import { euclidean, TreeNode } from 'hdbscan';
import { RawNodeDatum } from 'react-d3-tree/lib/types/common';
import { f32Average, getAllFacesFromMap } from '.';
// import { f32Average, getAllFacesFromMap } from '.';
import {
FacesCluster,
Cluster,
FaceDescriptor,
// Cluster,
// FaceDescriptor,
FaceWithEmbedding,
MLSyncContext,
NearestCluster,
} from 'types/machineLearning';
import { getAllFacesMap } from 'utils/storage/mlStorage';
// import { getAllFacesMap } from 'utils/storage/mlStorage';
export function getClusterSummary(cluster: Cluster): FaceDescriptor {
// const faceScore = (f) => f.detection.score; // f.alignedRect.box.width *
// return cluster
// .map((f) => this.allFaces[f].face)
// .sort((f1, f2) => faceScore(f2) - faceScore(f1))[0].descriptor;
const descriptors = cluster.map((f) => this.allFaces[f].embedding);
return f32Average(descriptors);
}
// export function getClusterSummary(cluster: Cluster): FaceDescriptor {
// const faceScore = (f) => f.detection.score; // f.alignedRect.box.width *
// return cluster
// .map((f) => this.allFaces[f].face)
// .sort((f1, f2) => faceScore(f2) - faceScore(f1))[0].descriptor;
// const descriptors = cluster.map((f) => this.allFaces[f].embedding);
// return f32Average(descriptors);
// }
export function updateClusterSummaries(syncContext: MLSyncContext) {
if (
@ -63,36 +60,36 @@ export function getNearestCluster(
return { cluster: nearest, distance: nearestDist };
}
export async function assignNoiseWithinLimit(syncContext: MLSyncContext) {
if (
!syncContext.mlLibraryData?.faceClusteringResults?.noise ||
syncContext.mlLibraryData?.faceClusteringResults.noise.length < 1
) {
return;
}
// export async function assignNoiseWithinLimit(syncContext: MLSyncContext) {
// if (
// !syncContext.mlLibraryData?.faceClusteringResults?.noise ||
// syncContext.mlLibraryData?.faceClusteringResults.noise.length < 1
// ) {
// return;
// }
const noise = syncContext.mlLibraryData.faceClusteringResults.noise;
const allFacesMap = await getAllFacesMap();
const allFaces = getAllFacesFromMap(allFacesMap);
// const noise = syncContext.mlLibraryData.faceClusteringResults.noise;
// const allFacesMap = await getAllFacesMap();
// const allFaces = getAllFacesFromMap(allFacesMap);
noise.forEach((n) => {
const noiseFace = allFaces[n];
const nearest = this.getNearestCluster(syncContext, noiseFace);
// noise.forEach((n) => {
// const noiseFace = allFaces[n];
// const nearest = this.getNearestCluster(syncContext, noiseFace);
if (nearest.cluster && nearest.distance < this.maxFaceDistance) {
console.log('Adding noise to cluser: ', n, nearest.distance);
nearest.cluster.faces.push(n);
} else {
console.log(
'No cluster for noise: ',
n,
'within distance: ',
this.maxFaceDistance
);
this.clustersWithNoise.noise.push(n);
}
});
}
// if (nearest.cluster && nearest.distance < this.maxFaceDistance) {
// console.log('Adding noise to cluser: ', n, nearest.distance);
// nearest.cluster.faces.push(n);
// } else {
// console.log(
// 'No cluster for noise: ',
// n,
// 'within distance: ',
// this.maxFaceDistance
// );
// this.clustersWithNoise.noise.push(n);
// }
// });
// }
// TODO: remove recursion to avoid stack size limits
export function toD3Tree(