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Remove more legacy ml code

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This commit is contained in:
Manav Rathi 2024-03-31 18:38:46 +05:30
parent 707e14702e
commit 0f2181c09b
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8 changed files with 6 additions and 331 deletions
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1
web/apps/photos/package.json
View file

@ -16,7 +16,6 @@
"@tensorflow/tfjs-converter": "^4.10.0",
"@tensorflow/tfjs-core": "^4.10.0",
"@tensorflow/tfjs-tflite": "0.0.1-alpha.7",
"@zip.js/zip.js": "2.4.2",
"bip39": "^3.0.4",
"blazeface-back": "^0.0.9",
"bootstrap": "^4.5.2",

12
web/apps/photos/src/components/ml-debug/index.tsx
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@ -1,12 +0,0 @@
// import dynamic from 'next/dynamic';
// const MLDebugWithNoSSR = dynamic(
// () => import('components/MachineLearning/MlDebug-disabled'),
// {
// ssr: false,
// }
// );
export default function MLDebug() {
return <div>{/* <MLDebugWithNoSSR></MLDebugWithNoSSR> */}</div>;
}

104
web/apps/photos/src/utils/machineLearning/clustering.ts
View file

@ -1,104 +0,0 @@
import { euclidean } from "hdbscan";
// import { RawNodeDatum } from 'react-d3-tree/lib/types/common';
// import { f32Average, getAllFacesFromMap } from '.';
import { addLogLine } from "@ente/shared/logging";
import {
FacesCluster,
FaceWithEmbedding,
MLSyncContext,
NearestCluster,
} from "types/machineLearning";
export function updateClusterSummaries(syncContext: MLSyncContext) {
if (
!syncContext.mlLibraryData?.faceClusteringResults?.clusters ||
syncContext.mlLibraryData?.faceClusteringResults?.clusters.length < 1
) {
return;
}
const resultClusters =
syncContext.mlLibraryData.faceClusteringResults.clusters;
resultClusters.forEach((resultCluster) => {
syncContext.mlLibraryData.faceClustersWithNoise.clusters.push({
faces: resultCluster,
// summary: this.getClusterSummary(resultCluster),
});
});
}
export function getNearestCluster(
syncContext: MLSyncContext,
noise: FaceWithEmbedding,
): NearestCluster {
let nearest: FacesCluster = null;
let nearestDist = 100000;
syncContext.mlLibraryData.faceClustersWithNoise.clusters.forEach((c) => {
const dist = euclidean(
Array.from(noise.embedding),
Array.from(c.summary),
);
if (dist < nearestDist) {
nearestDist = dist;
nearest = c;
}
});
addLogLine("nearestDist: ", nearestDist);
return { cluster: nearest, distance: nearestDist };
}
// 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);
// noise.forEach((n) => {
// const noiseFace = allFaces[n];
// const nearest = this.getNearestCluster(syncContext, noiseFace);
// if (nearest.cluster && nearest.distance < this.maxFaceDistance) {
// addLogLine('Adding noise to cluser: ', n, nearest.distance);
// nearest.cluster.faces.push(n);
// } else {
// addLogLine(
// '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(
// treeNode: TreeNode<number>,
// allObjects: Array<any>
// ): RawNodeDatum {
// if (!treeNode.left && !treeNode.right) {
// return {
// name: treeNode.data.toString(),
// attributes: {
// face: allObjects[treeNode.data],
// },
// };
// }
// const children = [];
// treeNode.left && children.push(toD3Tree(treeNode.left, allObjects));
// treeNode.right && children.push(toD3Tree(treeNode.right, allObjects));
// return {
// name: treeNode.data.toString(),
// children: children,
// };
// }

28
web/apps/photos/src/utils/machineLearning/compatibility.ts
View file

@ -1,28 +0,0 @@
import {
offscreenCanvasSupported,
runningInChrome,
webglSupported,
} from "utils/common";
import { addLogLine } from "@ente/shared/logging";
import isElectron from "is-electron";
export function canEnableMlSearch(): boolean {
// check if is chrome or ente desktop
if (!runningInChrome(false) && !isElectron()) {
addLogLine("Not running in Chrome Desktop or Ente Desktop App");
return false;
}
if (!offscreenCanvasSupported()) {
addLogLine("OffscreenCanvas is NOT supported");
return false;
}
if (!webglSupported()) {
addLogLine("webgl is NOT supported");
return false;
}
return true;
}

11
web/apps/photos/src/utils/machineLearning/index.ts
View file

@ -1,10 +1,15 @@
import { addLogLine } from "@ente/shared/logging";
import { CACHES } from "@ente/shared/storage/cacheStorage/constants";
import { cached } from "@ente/shared/storage/cacheStorage/helpers";
import * as tf from "@tensorflow/tfjs-core";
import { NormalizedFace } from "blazeface-back";
import { FILE_TYPE } from "constants/file";
import { BLAZEFACE_FACE_SIZE } from "constants/mlConfig";
import { euclidean } from "hdbscan";
import PQueue from "p-queue";
import DownloadManager from "services/download";
import { getLocalFiles } from "services/fileService";
import { decodeLivePhoto } from "services/livePhotoService";
import { EnteFile } from "types/file";
import { Dimensions } from "types/image";
import {
@ -18,12 +23,6 @@ import {
RealWorldObject,
Versioned,
} from "types/machineLearning";
// import { mlFilesStore, mlPeopleStore } from 'utils/storage/mlStorage';
import { addLogLine } from "@ente/shared/logging";
import { CACHES } from "@ente/shared/storage/cacheStorage/constants";
import { cached } from "@ente/shared/storage/cacheStorage/helpers";
import { FILE_TYPE } from "constants/file";
import { decodeLivePhoto } from "services/livePhotoService";
import { getRenderableImage } from "utils/file";
import { imageBitmapToBlob } from "utils/image";
import mlIDbStorage from "utils/storage/mlIDbStorage";

161
web/apps/photos/src/utils/machineLearning/mldataExport.ts
View file

@ -1,161 +0,0 @@
import { addLogLine } from "@ente/shared/logging";
import { CacheStorageService } from "@ente/shared/storage/cacheStorage";
import { CACHES } from "@ente/shared/storage/cacheStorage/constants";
import * as zip from "@zip.js/zip.js";
import { MlFileData } from "types/machineLearning";
import mlIDbStorage from "utils/storage/mlIDbStorage";
class FileSystemWriter extends zip.Writer {
writableStream: FileSystemWritableFileStream;
constructor(writableStream: FileSystemWritableFileStream) {
super();
this.writableStream = writableStream;
}
async writeUint8Array(array: Uint8Array) {
// addLogLine('zipWriter needs to write data: ', array.byteLength);
return this.writableStream.write(array);
}
async getData() {
return undefined;
}
}
class FileReader extends zip.Reader {
file: File;
constructor(file: File) {
super();
this.file = file;
}
public async init() {
this.size = this.file.size;
// addLogLine('zipReader init, size: ', this.size);
}
public async readUint8Array(
index: number,
length: number,
): Promise<Uint8Array> {
// addLogLine('zipReader needs data: ', index, length);
const slicedFile = this.file.slice(index, index + length);
const arrayBuffer = await slicedFile.arrayBuffer();
return new Uint8Array(arrayBuffer);
}
}
export async function exportMlData(
mlDataZipWritable: FileSystemWritableFileStream,
) {
const zipWriter = new zip.ZipWriter(
new FileSystemWriter(mlDataZipWritable),
);
try {
try {
await exportMlDataToZipWriter(zipWriter);
} finally {
await zipWriter.close();
}
} catch (e) {
await mlDataZipWritable.abort();
throw e;
}
await mlDataZipWritable.close();
addLogLine("Ml Data Exported");
}
async function exportMlDataToZipWriter(zipWriter: zip.ZipWriter) {
const mlDbData = await mlIDbStorage.getAllMLData();
const faceClusteringResults =
mlDbData?.library?.data?.faceClusteringResults;
faceClusteringResults && (faceClusteringResults.debugInfo = undefined);
addLogLine(
"Exporting ML DB data: ",
JSON.stringify(Object.keys(mlDbData)),
JSON.stringify(
Object.keys(mlDbData)?.map((k) => Object.keys(mlDbData[k])?.length),
),
);
await zipWriter.add(
"indexeddb/mldata.json",
new zip.TextReader(JSON.stringify(mlDbData)),
);
const faceCropCache = await CacheStorageService.open(CACHES.FACE_CROPS);
const files =
mlDbData["files"] && (Object.values(mlDbData["files"]) as MlFileData[]);
for (const fileData of files || []) {
for (const face of fileData.faces || []) {
const faceCropUrl = face.crop?.imageUrl;
if (!faceCropUrl) {
console.error("face crop not found for faceId: ", face.id);
continue;
}
const response = await faceCropCache.match(faceCropUrl);
if (response && response.ok) {
const blob = await response.blob();
await zipWriter.add(
`caches/${CACHES.FACE_CROPS}${faceCropUrl}`,
new zip.BlobReader(blob),
{ level: 0 },
);
} else {
console.error(
"face crop cache entry not found for faceCropUrl: ",
faceCropUrl,
);
}
}
}
}
export async function importMlData(mlDataZipFile: File) {
const zipReader = new zip.ZipReader(new FileReader(mlDataZipFile));
try {
await importMlDataFromZipReader(zipReader);
} finally {
await zipReader.close();
}
addLogLine("ML Data Imported");
}
async function importMlDataFromZipReader(zipReader: zip.ZipReader) {
const zipEntries = await zipReader.getEntries();
// addLogLine(zipEntries);
const faceCropPath = `caches/${CACHES.FACE_CROPS}`;
const faceCropCache = await CacheStorageService.open(CACHES.FACE_CROPS);
let mldataEntry;
for (const entry of zipEntries) {
if (entry.filename === "indexeddb/mldata.json") {
mldataEntry = entry;
} else if (entry.filename.startsWith(faceCropPath)) {
const faceCropUrl = entry.filename.substring(faceCropPath.length);
// addLogLine('importing faceCropUrl: ', faceCropUrl);
const faceCropCacheBlob: Blob = await entry.getData(
new zip.BlobWriter("image/jpeg"),
);
faceCropCache.put(faceCropUrl, new Response(faceCropCacheBlob));
}
}
const mlDataJsonStr: string = await mldataEntry.getData(
new zip.TextWriter(),
);
const mlDbData = JSON.parse(mlDataJsonStr);
addLogLine(
"importing ML DB data: ",
JSON.stringify(Object.keys(mlDbData)),
JSON.stringify(
Object.keys(mlDbData)?.map((k) => Object.keys(mlDbData[k])?.length),
),
);
await mlIDbStorage.putAllMLData(mlDbData);
}

13
web/apps/photos/src/worker/ml.worker.ts
View file

@ -3,23 +3,12 @@ import { expose } from "comlink";
import mlService from "services/machineLearning/machineLearningService";
import { EnteFile } from "types/file";
import { MachineLearningWorker } from "types/machineLearning";
// import ReverseProxiedElectronCacheStorageProxy from './electronCacheStorageProxy.proxy';
// import { setupResponseComlinkTransferHandler } from 'utils/comlink';
export class DedicatedMLWorker implements MachineLearningWorker {
constructor() {
addLogLine("DedicatedMLWorker constructor called");
// this.init();
}
// public async init() {
// const recp = new ReverseProxiedElectronCacheStorageProxy();
// const cacheProxy = await recp.open('thumbs');
// const thumb = await cacheProxy.match('13578875');
// addLogLine('worker init cache.match', thumb);
// }
public async closeLocalSyncContext() {
return mlService.closeLocalSyncContext();
}
@ -51,5 +40,3 @@ export class DedicatedMLWorker implements MachineLearningWorker {
}
expose(DedicatedMLWorker, self);
// setupResponseComlinkTransferHandler();

7
web/yarn.lock
View file

@ -947,11 +947,6 @@
resolved "https://registry.yarnpkg.com/@webgpu/types/-/types-0.1.38.tgz#6fda4b410edc753d3213c648320ebcf319669020"
integrity sha512-7LrhVKz2PRh+DD7+S+PVaFd5HxaWQvoMqBbsV9fNJO1pjUs1P8bM2vQVNfk+3URTqbuTI7gkXi0rfsN0IadoBA==
"@zip.js/zip.js@2.4.2":
version "2.4.2"
resolved "https://registry.yarnpkg.com/@zip.js/zip.js/-/zip.js-2.4.2.tgz#7c2d4b381c0f73dffa1d02ef630c4168ebd5cc4a"
integrity sha512-D4xr9g7U625Q01lQASr9g1sQWEGhndyd+G3v3OvY/qH3pwaJDpbVDy+TO6yEq7c8teQdjjTiiBvlcQcVtT+itg==
acorn-jsx@^5.3.2:
version "5.3.2"
resolved "https://registry.yarnpkg.com/acorn-jsx/-/acorn-jsx-5.3.2.tgz#7ed5bb55908b3b2f1bc55c6af1653bada7f07937"
@ -2828,7 +2823,7 @@ libsodium-wrappers@0.7.9:
dependencies:
libsodium "^0.7.0"
libsodium@^0.7.0:
libsodium@0.7.9, libsodium@^0.7.0:
version "0.7.9"
resolved "https://registry.yarnpkg.com/libsodium/-/libsodium-0.7.9.tgz#4bb7bcbf662ddd920d8795c227ae25bbbfa3821b"
integrity sha512-gfeADtR4D/CM0oRUviKBViMGXZDgnFdMKMzHsvBdqLBHd9ySi6EtYnmuhHVDDYgYpAO8eU8hEY+F8vIUAPh08A==