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This commit is contained in:
Manav Rathi 2024-05-14 14:13:41 +05:30
parent b75977186f
commit 86c9deb7b8
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6 changed files with 108 additions and 113 deletions
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0
web/apps/photos/src/constants/mlConfig.ts
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7
web/apps/photos/src/services/machineLearning/faceService.ts
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@ -9,13 +9,12 @@ import {
type Versioned, type Versioned,
} from "services/ml/types"; } from "services/ml/types";
import { imageBitmapToBlob, warpAffineFloat32List } from "utils/image"; import { imageBitmapToBlob, warpAffineFloat32List } from "utils/image";
import { import mlIDbStorage from "utils/storage/mlIDbStorage";
import ReaderService, {
getFaceId, getFaceId,
getLocalFile, getLocalFile,
getOriginalImageBitmap, getOriginalImageBitmap,
} from "utils/machineLearning"; } from "./readerService";
import mlIDbStorage from "utils/storage/mlIDbStorage";
import ReaderService from "./readerService";
class FaceService { class FaceService {
async syncFileFaceDetections( async syncFileFaceDetections(

2
web/apps/photos/src/services/machineLearning/peopleService.ts
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@ -1,8 +1,8 @@
import log from "@/next/log"; import log from "@/next/log";
import { Face, MLSyncContext, Person } from "services/ml/types"; import { Face, MLSyncContext, Person } from "services/ml/types";
import { getLocalFile, getOriginalImageBitmap } from "utils/machineLearning";
import mlIDbStorage from "utils/storage/mlIDbStorage"; import mlIDbStorage from "utils/storage/mlIDbStorage";
import FaceService, { isDifferentOrOld } from "./faceService"; import FaceService, { isDifferentOrOld } from "./faceService";
import { getLocalFile, getOriginalImageBitmap } from "./readerService";
class PeopleService { class PeopleService {
async syncPeopleIndex(syncContext: MLSyncContext) { async syncPeopleIndex(syncContext: MLSyncContext) {

109
web/apps/photos/src/services/machineLearning/readerService.ts
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@ -1,11 +1,18 @@
import { FILE_TYPE } from "@/media/file-type"; import { FILE_TYPE } from "@/media/file-type";
import { decodeLivePhoto } from "@/media/live-photo";
import log from "@/next/log"; import log from "@/next/log";
import { MLSyncContext, MLSyncFileContext } from "services/ml/types"; import PQueue from "p-queue";
import DownloadManager from "services/download";
import { getLocalFiles } from "services/fileService";
import { Dimensions } from "services/ml/geom";
import { import {
getLocalFileImageBitmap, DetectedFace,
getOriginalImageBitmap, MLSyncContext,
getThumbnailImageBitmap, MLSyncFileContext,
} from "utils/machineLearning"; } from "services/ml/types";
import { EnteFile } from "types/file";
import { getRenderableImage } from "utils/file";
import { clamp } from "utils/image";
class ReaderService { class ReaderService {
async getImageBitmap( async getImageBitmap(
@ -55,3 +62,95 @@ class ReaderService {
} }
} }
export default new ReaderService(); export default new ReaderService();
export async function getLocalFile(fileId: number) {
const localFiles = await getLocalFiles();
return localFiles.find((f) => f.id === fileId);
}
export function getFaceId(detectedFace: DetectedFace, imageDims: Dimensions) {
const xMin = clamp(
detectedFace.detection.box.x / imageDims.width,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const yMin = clamp(
detectedFace.detection.box.y / imageDims.height,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const xMax = clamp(
(detectedFace.detection.box.x + detectedFace.detection.box.width) /
imageDims.width,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const yMax = clamp(
(detectedFace.detection.box.y + detectedFace.detection.box.height) /
imageDims.height,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const rawFaceID = `${xMin}_${yMin}_${xMax}_${yMax}`;
const faceID = `${detectedFace.fileId}_${rawFaceID}`;
return faceID;
}
async function getImageBlobBitmap(blob: Blob): Promise<ImageBitmap> {
return await createImageBitmap(blob);
}
async function getOriginalFile(file: EnteFile, queue?: PQueue) {
let fileStream;
if (queue) {
fileStream = await queue.add(() => DownloadManager.getFile(file));
} else {
fileStream = await DownloadManager.getFile(file);
}
return new Response(fileStream).blob();
}
async function getOriginalConvertedFile(file: EnteFile, queue?: PQueue) {
const fileBlob = await getOriginalFile(file, queue);
if (file.metadata.fileType === FILE_TYPE.IMAGE) {
return await getRenderableImage(file.metadata.title, fileBlob);
} else {
const { imageFileName, imageData } = await decodeLivePhoto(
file.metadata.title,
fileBlob,
);
return await getRenderableImage(imageFileName, new Blob([imageData]));
}
}
export async function getOriginalImageBitmap(file: EnteFile, queue?: PQueue) {
const fileBlob = await getOriginalConvertedFile(file, queue);
log.info("[MLService] Got file: ", file.id.toString());
return getImageBlobBitmap(fileBlob);
}
export async function getThumbnailImageBitmap(file: EnteFile) {
const thumb = await DownloadManager.getThumbnail(file);
log.info("[MLService] Got thumbnail: ", file.id.toString());
return getImageBlobBitmap(new Blob([thumb]));
}
export async function getLocalFileImageBitmap(
enteFile: EnteFile,
localFile: globalThis.File,
) {
let fileBlob = localFile as Blob;
fileBlob = await getRenderableImage(enteFile.metadata.title, fileBlob);
return getImageBlobBitmap(fileBlob);
}

0
web/apps/photos/src/types/machineLearning/ui.ts
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103
web/apps/photos/src/utils/machineLearning/index.ts
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@ -1,103 +0,0 @@
import { FILE_TYPE } from "@/media/file-type";
import { decodeLivePhoto } from "@/media/live-photo";
import log from "@/next/log";
import PQueue from "p-queue";
import DownloadManager from "services/download";
import { getLocalFiles } from "services/fileService";
import { Dimensions } from "services/ml/geom";
import { DetectedFace } from "services/ml/types";
import { EnteFile } from "types/file";
import { getRenderableImage } from "utils/file";
import { clamp } from "utils/image";
export async function getLocalFile(fileId: number) {
const localFiles = await getLocalFiles();
return localFiles.find((f) => f.id === fileId);
}
export function getFaceId(detectedFace: DetectedFace, imageDims: Dimensions) {
const xMin = clamp(
detectedFace.detection.box.x / imageDims.width,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const yMin = clamp(
detectedFace.detection.box.y / imageDims.height,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const xMax = clamp(
(detectedFace.detection.box.x + detectedFace.detection.box.width) /
imageDims.width,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const yMax = clamp(
(detectedFace.detection.box.y + detectedFace.detection.box.height) /
imageDims.height,
0.0,
0.999999,
)
.toFixed(5)
.substring(2);
const rawFaceID = `${xMin}_${yMin}_${xMax}_${yMax}`;
const faceID = `${detectedFace.fileId}_${rawFaceID}`;
return faceID;
}
async function getImageBlobBitmap(blob: Blob): Promise<ImageBitmap> {
return await createImageBitmap(blob);
}
async function getOriginalFile(file: EnteFile, queue?: PQueue) {
let fileStream;
if (queue) {
fileStream = await queue.add(() => DownloadManager.getFile(file));
} else {
fileStream = await DownloadManager.getFile(file);
}
return new Response(fileStream).blob();
}
async function getOriginalConvertedFile(file: EnteFile, queue?: PQueue) {
const fileBlob = await getOriginalFile(file, queue);
if (file.metadata.fileType === FILE_TYPE.IMAGE) {
return await getRenderableImage(file.metadata.title, fileBlob);
} else {
const { imageFileName, imageData } = await decodeLivePhoto(
file.metadata.title,
fileBlob,
);
return await getRenderableImage(imageFileName, new Blob([imageData]));
}
}
export async function getOriginalImageBitmap(file: EnteFile, queue?: PQueue) {
const fileBlob = await getOriginalConvertedFile(file, queue);
log.info("[MLService] Got file: ", file.id.toString());
return getImageBlobBitmap(fileBlob);
}
export async function getThumbnailImageBitmap(file: EnteFile) {
const thumb = await DownloadManager.getThumbnail(file);
log.info("[MLService] Got thumbnail: ", file.id.toString());
return getImageBlobBitmap(new Blob([thumb]));
}
export async function getLocalFileImageBitmap(
enteFile: EnteFile,
localFile: globalThis.File,
) {
let fileBlob = localFile as Blob;
fileBlob = await getRenderableImage(enteFile.metadata.title, fileBlob);
return getImageBlobBitmap(fileBlob);
}