From bcc36d14a178360c59e887e19f3150b86c414253 Mon Sep 17 00:00:00 2001 From: Mert <101130780+mertalev@users.noreply.github.com> Date: Tue, 29 Aug 2023 09:58:00 -0400 Subject: [PATCH] feat(ml)!: customizable ML settings (#3891) * consolidated endpoints, added live configuration * added ml settings to server * added settings dashboard * updated deps, fixed typos * simplified modelconfig updated tests * Added ml setting accordion for admin page updated tests * merge `clipText` and `clipVision` * added face distance setting clarified setting * add clip mode in request, dropdown for face models * polished ml settings updated descriptions * update clip field on error * removed unused import * add description for image classification threshold * pin safetensors for arm wheel updated poetry lock * moved dto * set model type only in ml repository * revert form-data package install use fetch instead of axios * added slotted description with link updated facial recognition description clarified effect of disabling tasks * validation before model load * removed unnecessary getconfig call * added migration * updated api updated api updated api --------- Co-authored-by: Alex Tran --- cli/src/api/open-api/api.ts | 154 +++- machine-learning/app/config.py | 6 - machine-learning/app/main.py | 111 +-- machine-learning/app/models/base.py | 7 +- machine-learning/app/models/clip.py | 10 +- .../app/models/facial_recognition.py | 12 +- .../app/models/image_classification.py | 13 +- machine-learning/app/schemas.py | 32 +- machine-learning/poetry.lock | 799 ++++++++++-------- machine-learning/pyproject.toml | 3 + mobile/openapi/.openapi-generator/FILES | 15 + mobile/openapi/README.md | Bin 18776 -> 18984 bytes mobile/openapi/doc/CLIPConfig.md | Bin 0 -> 557 bytes mobile/openapi/doc/CLIPMode.md | Bin 0 -> 374 bytes mobile/openapi/doc/ClassificationConfig.md | Bin 0 -> 540 bytes mobile/openapi/doc/ModelType.md | Bin 0 -> 375 bytes mobile/openapi/doc/RecognitionConfig.md | Bin 0 -> 569 bytes .../doc/SystemConfigMachineLearningDto.md | Bin 574 -> 656 bytes mobile/openapi/lib/api.dart | Bin 6149 -> 6318 bytes mobile/openapi/lib/api_client.dart | Bin 19097 -> 19515 bytes mobile/openapi/lib/api_helper.dart | Bin 4664 -> 4854 bytes .../lib/model/classification_config.dart | Bin 0 -> 4067 bytes mobile/openapi/lib/model/clip_config.dart | Bin 0 -> 4268 bytes mobile/openapi/lib/model/clip_mode.dart | Bin 0 -> 2496 bytes mobile/openapi/lib/model/model_type.dart | Bin 0 -> 2753 bytes .../openapi/lib/model/recognition_config.dart | Bin 0 -> 4291 bytes .../system_config_machine_learning_dto.dart | Bin 4354 -> 4151 bytes .../test/classification_config_test.dart | Bin 0 -> 887 bytes mobile/openapi/test/clip_config_test.dart | Bin 0 -> 854 bytes mobile/openapi/test/clip_mode_test.dart | Bin 0 -> 413 bytes mobile/openapi/test/model_type_test.dart | Bin 0 -> 415 bytes .../openapi/test/recognition_config_test.dart | Bin 0 -> 982 bytes ...stem_config_machine_learning_dto_test.dart | Bin 1062 -> 1055 bytes server/immich-openapi-specs.json | 104 ++- .../facial-recognition.service.spec.ts | 16 +- .../facial-recognition.services.ts | 14 +- server/src/domain/search/search.repository.ts | 1 + server/src/domain/search/search.service.ts | 9 +- server/src/domain/smart-info/dto/index.ts | 1 + .../domain/smart-info/dto/model-config.dto.ts | 50 ++ server/src/domain/smart-info/index.ts | 1 + .../smart-info/machine-learning.interface.ts | 29 +- .../smart-info/smart-info.service.spec.ts | 19 +- .../domain/smart-info/smart-info.service.ts | 21 +- .../dto/system-config-machine-learning.dto.ts | 22 +- .../system-config/system-config.core.ts | 27 +- .../system-config.service.spec.ts | 18 +- .../infra/entities/system-config.entity.ts | 35 +- .../1693236627291-RenameMLEnableFlags.ts | 25 + .../machine-learning.repository.ts | 66 +- .../repositories/typesense.repository.ts | 49 +- .../repositories/search.repository.mock.ts | 1 + web/src/api/open-api/api.ts | 154 +++- .../machine-learning-settings.svelte | 204 +++-- .../settings/setting-input-field.svelte | 8 + .../routes/admin/system-settings/+page.svelte | 8 +- 56 files changed, 1424 insertions(+), 620 deletions(-) create mode 100644 mobile/openapi/doc/CLIPConfig.md create mode 100644 mobile/openapi/doc/CLIPMode.md create mode 100644 mobile/openapi/doc/ClassificationConfig.md create mode 100644 mobile/openapi/doc/ModelType.md create mode 100644 mobile/openapi/doc/RecognitionConfig.md create mode 100644 mobile/openapi/lib/model/classification_config.dart create mode 100644 mobile/openapi/lib/model/clip_config.dart create mode 100644 mobile/openapi/lib/model/clip_mode.dart create mode 100644 mobile/openapi/lib/model/model_type.dart create mode 100644 mobile/openapi/lib/model/recognition_config.dart create mode 100644 mobile/openapi/test/classification_config_test.dart create mode 100644 mobile/openapi/test/clip_config_test.dart create mode 100644 mobile/openapi/test/clip_mode_test.dart create mode 100644 mobile/openapi/test/model_type_test.dart create mode 100644 mobile/openapi/test/recognition_config_test.dart create mode 100644 server/src/domain/smart-info/dto/index.ts create mode 100644 server/src/domain/smart-info/dto/model-config.dto.ts create mode 100644 server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts diff --git a/cli/src/api/open-api/api.ts b/cli/src/api/open-api/api.ts index 36189d39f4..f3246f0963 100644 --- a/cli/src/api/open-api/api.ts +++ b/cli/src/api/open-api/api.ts @@ -862,6 +862,53 @@ export interface BulkIdsDto { */ 'ids': Array; } +/** + * + * @export + * @interface CLIPConfig + */ +export interface CLIPConfig { + /** + * + * @type {boolean} + * @memberof CLIPConfig + */ + 'enabled': boolean; + /** + * + * @type {CLIPMode} + * @memberof CLIPConfig + */ + 'mode'?: CLIPMode; + /** + * + * @type {string} + * @memberof CLIPConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof CLIPConfig + */ + 'modelType'?: ModelType; +} + + +/** + * + * @export + * @enum {string} + */ + +export const CLIPMode = { + Vision: 'vision', + Text: 'text' +} as const; + +export type CLIPMode = typeof CLIPMode[keyof typeof CLIPMode]; + + /** * * @export @@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto { */ 'existingIds': Array; } +/** + * + * @export + * @interface ClassificationConfig + */ +export interface ClassificationConfig { + /** + * + * @type {boolean} + * @memberof ClassificationConfig + */ + 'enabled': boolean; + /** + * + * @type {number} + * @memberof ClassificationConfig + */ + 'minScore': number; + /** + * + * @type {string} + * @memberof ClassificationConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof ClassificationConfig + */ + 'modelType'?: ModelType; +} + + /** * * @export @@ -1766,6 +1846,21 @@ export interface MergePersonDto { */ 'ids': Array; } +/** + * + * @export + * @enum {string} + */ + +export const ModelType = { + ImageClassification: 'image-classification', + FacialRecognition: 'facial-recognition', + Clip: 'clip' +} as const; + +export type ModelType = typeof ModelType[keyof typeof ModelType]; + + /** * * @export @@ -1991,6 +2086,45 @@ export interface QueueStatusDto { */ 'isPaused': boolean; } +/** + * + * @export + * @interface RecognitionConfig + */ +export interface RecognitionConfig { + /** + * + * @type {boolean} + * @memberof RecognitionConfig + */ + 'enabled': boolean; + /** + * + * @type {number} + * @memberof RecognitionConfig + */ + 'maxDistance': number; + /** + * + * @type {number} + * @memberof RecognitionConfig + */ + 'minScore': number; + /** + * + * @type {string} + * @memberof RecognitionConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof RecognitionConfig + */ + 'modelType'?: ModelType; +} + + /** * * @export @@ -2803,10 +2937,16 @@ export interface SystemConfigJobDto { export interface SystemConfigMachineLearningDto { /** * - * @type {boolean} + * @type {ClassificationConfig} * @memberof SystemConfigMachineLearningDto */ - 'clipEncodeEnabled': boolean; + 'classification': ClassificationConfig; + /** + * + * @type {CLIPConfig} + * @memberof SystemConfigMachineLearningDto + */ + 'clip': CLIPConfig; /** * * @type {boolean} @@ -2815,16 +2955,10 @@ export interface SystemConfigMachineLearningDto { 'enabled': boolean; /** * - * @type {boolean} + * @type {RecognitionConfig} * @memberof SystemConfigMachineLearningDto */ - 'facialRecognitionEnabled': boolean; - /** - * - * @type {boolean} - * @memberof SystemConfigMachineLearningDto - */ - 'tagImageEnabled': boolean; + 'facialRecognition': RecognitionConfig; /** * * @type {string} diff --git a/machine-learning/app/config.py b/machine-learning/app/config.py index 8a64d91198..83053b8ae9 100644 --- a/machine-learning/app/config.py +++ b/machine-learning/app/config.py @@ -8,17 +8,11 @@ from .schemas import ModelType class Settings(BaseSettings): cache_folder: str = "/cache" - classification_model: str = "microsoft/resnet-50" - clip_image_model: str = "ViT-B-32::openai" - clip_text_model: str = "ViT-B-32::openai" - facial_recognition_model: str = "buffalo_l" - min_tag_score: float = 0.9 eager_startup: bool = False model_ttl: int = 0 host: str = "0.0.0.0" port: int = 3003 workers: int = 1 - min_face_score: float = 0.7 test_full: bool = False request_threads: int = os.cpu_count() or 4 model_inter_op_threads: int = 1 diff --git a/machine-learning/app/main.py b/machine-learning/app/main.py index ddbce0f659..0229ad00b5 100644 --- a/machine-learning/app/main.py +++ b/machine-learning/app/main.py @@ -1,29 +1,26 @@ import asyncio import os from concurrent.futures import ThreadPoolExecutor -from io import BytesIO from typing import Any -import cv2 -import numpy as np +import orjson import uvicorn -from fastapi import Body, Depends, FastAPI -from PIL import Image +from fastapi import FastAPI, Form, HTTPException, UploadFile +from fastapi.responses import ORJSONResponse +from starlette.formparsers import MultiPartParser from app.models.base import InferenceModel from .config import settings from .models.cache import ModelCache from .schemas import ( - EmbeddingResponse, - FaceResponse, MessageResponse, ModelType, - TagResponse, - TextModelRequest, TextResponse, ) +MultiPartParser.max_file_size = 2**24 # spools to disk if payload is 16 MiB or larger + app = FastAPI() @@ -33,37 +30,9 @@ def init_state() -> None: app.state.thread_pool = ThreadPoolExecutor(settings.request_threads) -async def load_models() -> None: - models: list[tuple[str, ModelType, dict[str, Any]]] = [ - (settings.classification_model, ModelType.IMAGE_CLASSIFICATION, {}), - (settings.clip_image_model, ModelType.CLIP, {"mode": "vision"}), - (settings.clip_text_model, ModelType.CLIP, {"mode": "text"}), - (settings.facial_recognition_model, ModelType.FACIAL_RECOGNITION, {}), - ] - - # Get all models - for model_name, model_type, model_kwargs in models: - await app.state.model_cache.get(model_name, model_type, eager=settings.eager_startup, **model_kwargs) - - @app.on_event("startup") async def startup_event() -> None: init_state() - await load_models() - - -@app.on_event("shutdown") -async def shutdown_event() -> None: - app.state.thread_pool.shutdown() - - -def dep_pil_image(byte_image: bytes = Body(...)) -> Image.Image: - return Image.open(BytesIO(byte_image)) - - -def dep_cv_image(byte_image: bytes = Body(...)) -> np.ndarray[int, np.dtype[Any]]: - byte_image_np = np.frombuffer(byte_image, np.uint8) - return cv2.imdecode(byte_image_np, cv2.IMREAD_COLOR) @app.get("/", response_model=MessageResponse) @@ -76,57 +45,27 @@ def ping() -> str: return "pong" -@app.post( - "/image-classifier/tag-image", - response_model=TagResponse, - status_code=200, -) -async def image_classification( - image: Image.Image = Depends(dep_pil_image), -) -> list[str]: - model = await app.state.model_cache.get(settings.classification_model, ModelType.IMAGE_CLASSIFICATION) - labels = await predict(model, image) - return labels +@app.post("/predict") +async def predict( + model_name: str = Form(alias="modelName"), + model_type: ModelType = Form(alias="modelType"), + options: str = Form(default="{}"), + text: str | None = Form(default=None), + image: UploadFile | None = None, +) -> Any: + if image is not None: + inputs: str | bytes = await image.read() + elif text is not None: + inputs = text + else: + raise HTTPException(400, "Either image or text must be provided") + + model: InferenceModel = await app.state.model_cache.get(model_name, model_type, **orjson.loads(options)) + outputs = await run(model, inputs) + return ORJSONResponse(outputs) -@app.post( - "/sentence-transformer/encode-image", - response_model=EmbeddingResponse, - status_code=200, -) -async def clip_encode_image( - image: Image.Image = Depends(dep_pil_image), -) -> list[float]: - model = await app.state.model_cache.get(settings.clip_image_model, ModelType.CLIP, mode="vision") - embedding = await predict(model, image) - return embedding - - -@app.post( - "/sentence-transformer/encode-text", - response_model=EmbeddingResponse, - status_code=200, -) -async def clip_encode_text(payload: TextModelRequest) -> list[float]: - model = await app.state.model_cache.get(settings.clip_text_model, ModelType.CLIP, mode="text") - embedding = await predict(model, payload.text) - return embedding - - -@app.post( - "/facial-recognition/detect-faces", - response_model=FaceResponse, - status_code=200, -) -async def facial_recognition( - image: cv2.Mat = Depends(dep_cv_image), -) -> list[dict[str, Any]]: - model = await app.state.model_cache.get(settings.facial_recognition_model, ModelType.FACIAL_RECOGNITION) - faces = await predict(model, image) - return faces - - -async def predict(model: InferenceModel, inputs: Any) -> Any: +async def run(model: InferenceModel, inputs: Any) -> Any: return await asyncio.get_running_loop().run_in_executor(app.state.thread_pool, model.predict, inputs) diff --git a/machine-learning/app/models/base.py b/machine-learning/app/models/base.py index 07bc16dcdc..7fa40a5d06 100644 --- a/machine-learning/app/models/base.py +++ b/machine-learning/app/models/base.py @@ -60,16 +60,21 @@ class InferenceModel(ABC): self._load(**model_kwargs) self._loaded = True - def predict(self, inputs: Any) -> Any: + def predict(self, inputs: Any, **model_kwargs: Any) -> Any: if not self._loaded: print(f"Loading {self.model_type.value.replace('_', ' ')} model...") self.load() + if model_kwargs: + self.configure(**model_kwargs) return self._predict(inputs) @abstractmethod def _predict(self, inputs: Any) -> Any: ... + def configure(self, **model_kwargs: Any) -> None: + pass + @abstractmethod def _download(self, **model_kwargs: Any) -> None: ... diff --git a/machine-learning/app/models/clip.py b/machine-learning/app/models/clip.py index c59abfbb9f..b4afacca93 100644 --- a/machine-learning/app/models/clip.py +++ b/machine-learning/app/models/clip.py @@ -1,5 +1,6 @@ import os import zipfile +from io import BytesIO from typing import Any, Literal import onnxruntime as ort @@ -8,7 +9,7 @@ from clip_server.model.clip import BICUBIC, _convert_image_to_rgb from clip_server.model.clip_onnx import _MODELS, _S3_BUCKET_V2, CLIPOnnxModel, download_model from clip_server.model.pretrained_models import _VISUAL_MODEL_IMAGE_SIZE from clip_server.model.tokenization import Tokenizer -from PIL.Image import Image +from PIL import Image from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor from ..schemas import ModelType @@ -74,9 +75,12 @@ class CLIPEncoder(InferenceModel): image_size = _VISUAL_MODEL_IMAGE_SIZE[CLIPOnnxModel.get_model_name(self.model_name)] self.transform = _transform_pil_image(image_size) - def _predict(self, image_or_text: Image | str) -> list[float]: + def _predict(self, image_or_text: Image.Image | str) -> list[float]: + if isinstance(image_or_text, bytes): + image_or_text = Image.open(BytesIO(image_or_text)) + match image_or_text: - case Image(): + case Image.Image(): if self.mode == "text": raise TypeError("Cannot encode image as text-only model") pixel_values = self.transform(image_or_text) diff --git a/machine-learning/app/models/facial_recognition.py b/machine-learning/app/models/facial_recognition.py index b0ff1d0414..630c9d2e7c 100644 --- a/machine-learning/app/models/facial_recognition.py +++ b/machine-learning/app/models/facial_recognition.py @@ -9,7 +9,6 @@ from insightface.model_zoo import ArcFaceONNX, RetinaFace from insightface.utils.face_align import norm_crop from insightface.utils.storage import BASE_REPO_URL, download_file -from ..config import settings from ..schemas import ModelType from .base import InferenceModel @@ -20,7 +19,7 @@ class FaceRecognizer(InferenceModel): def __init__( self, model_name: str, - min_score: float = settings.min_face_score, + min_score: float = 0.7, cache_dir: Path | str | None = None, **model_kwargs: Any, ) -> None: @@ -69,11 +68,13 @@ class FaceRecognizer(InferenceModel): ) self.rec_model.prepare(ctx_id=0) - def _predict(self, image: cv2.Mat) -> list[dict[str, Any]]: + def _predict(self, image: np.ndarray[int, np.dtype[Any]] | bytes) -> list[dict[str, Any]]: + if isinstance(image, bytes): + image = cv2.imdecode(np.frombuffer(image, np.uint8), cv2.IMREAD_COLOR) bboxes, kpss = self.det_model.detect(image) if bboxes.size == 0: return [] - assert isinstance(kpss, np.ndarray) + assert isinstance(image, np.ndarray) and isinstance(kpss, np.ndarray) scores = bboxes[:, 4].tolist() bboxes = bboxes[:, :4].round().tolist() @@ -102,3 +103,6 @@ class FaceRecognizer(InferenceModel): @property def cached(self) -> bool: return self.cache_dir.is_dir() and any(self.cache_dir.glob("*.onnx")) + + def configure(self, **model_kwargs: Any) -> None: + self.det_model.det_thresh = model_kwargs.get("min_score", self.det_model.det_thresh) diff --git a/machine-learning/app/models/image_classification.py b/machine-learning/app/models/image_classification.py index 6c12dd8d76..bdcf76f5f3 100644 --- a/machine-learning/app/models/image_classification.py +++ b/machine-learning/app/models/image_classification.py @@ -1,13 +1,13 @@ +from io import BytesIO from pathlib import Path from typing import Any from huggingface_hub import snapshot_download from optimum.onnxruntime import ORTModelForImageClassification from optimum.pipelines import pipeline -from PIL.Image import Image +from PIL import Image from transformers import AutoImageProcessor -from ..config import settings from ..schemas import ModelType from .base import InferenceModel @@ -18,7 +18,7 @@ class ImageClassifier(InferenceModel): def __init__( self, model_name: str, - min_score: float = settings.min_tag_score, + min_score: float = 0.9, cache_dir: Path | str | None = None, **model_kwargs: Any, ) -> None: @@ -56,8 +56,13 @@ class ImageClassifier(InferenceModel): feature_extractor=processor, ) - def _predict(self, image: Image) -> list[str]: + def _predict(self, image: Image.Image | bytes) -> list[str]: + if isinstance(image, bytes): + image = Image.open(BytesIO(image)) predictions: list[dict[str, Any]] = self.model(image) # type: ignore tags = [tag for pred in predictions for tag in pred["label"].split(", ") if pred["score"] >= self.min_score] return tags + + def configure(self, **model_kwargs: Any) -> None: + self.min_score = model_kwargs.get("min_score", self.min_score) diff --git a/machine-learning/app/schemas.py b/machine-learning/app/schemas.py index b19b498739..cad2796871 100644 --- a/machine-learning/app/schemas.py +++ b/machine-learning/app/schemas.py @@ -1,4 +1,4 @@ -from enum import Enum +from enum import StrEnum from pydantic import BaseModel @@ -20,18 +20,6 @@ class MessageResponse(BaseModel): message: str -class TagResponse(BaseModel): - __root__: list[str] - - -class Embedding(BaseModel): - __root__: list[float] - - -class EmbeddingResponse(BaseModel): - __root__: Embedding - - class BoundingBox(BaseModel): x1: int y1: int @@ -39,23 +27,7 @@ class BoundingBox(BaseModel): y2: int -class Face(BaseModel): - image_width: int - image_height: int - bounding_box: BoundingBox - score: float - embedding: Embedding - - class Config: - alias_generator = to_lower_camel - allow_population_by_field_name = True - - -class FaceResponse(BaseModel): - __root__: list[Face] - - -class ModelType(Enum): +class ModelType(StrEnum): IMAGE_CLASSIFICATION = "image-classification" CLIP = "clip" FACIAL_RECOGNITION = "facial-recognition" diff --git a/machine-learning/poetry.lock b/machine-learning/poetry.lock index cb668f9a17..1a617a38cd 100644 --- a/machine-learning/poetry.lock +++ b/machine-learning/poetry.lock @@ -720,69 +720,69 @@ files = [ [[package]] name = "cython" -version = "3.0.0" +version = "3.0.2" description = "The Cython compiler for writing C extensions in the Python language." optional = false python-versions = 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b/machine-learning/pyproject.toml index 355fb23bdd..756121f53e 100644 --- a/machine-learning/pyproject.toml +++ b/machine-learning/pyproject.toml @@ -30,6 +30,9 @@ rich = "^13.4.2" ftfy = "^6.1.1" setuptools = "^68.0.0" open-clip-torch = "^2.20.0" +python-multipart = "^0.0.6" +orjson = "^3.9.5" +safetensors = "0.3.2" [tool.poetry.group.dev.dependencies] mypy = "^1.3.0" diff --git a/mobile/openapi/.openapi-generator/FILES b/mobile/openapi/.openapi-generator/FILES index e62417987a..517c33f249 100644 --- a/mobile/openapi/.openapi-generator/FILES +++ b/mobile/openapi/.openapi-generator/FILES @@ -35,11 +35,14 @@ doc/AuthDeviceResponseDto.md doc/AuthenticationApi.md doc/BulkIdResponseDto.md doc/BulkIdsDto.md +doc/CLIPConfig.md +doc/CLIPMode.md doc/ChangePasswordDto.md doc/CheckDuplicateAssetDto.md doc/CheckDuplicateAssetResponseDto.md doc/CheckExistingAssetsDto.md doc/CheckExistingAssetsResponseDto.md +doc/ClassificationConfig.md doc/CreateAlbumDto.md doc/CreateProfileImageResponseDto.md doc/CreateTagDto.md @@ -68,6 +71,7 @@ doc/LogoutResponseDto.md doc/MapMarkerResponseDto.md doc/MemoryLaneResponseDto.md doc/MergePersonDto.md +doc/ModelType.md doc/OAuthApi.md doc/OAuthCallbackDto.md doc/OAuthConfigDto.md @@ -80,6 +84,7 @@ doc/PersonApi.md doc/PersonResponseDto.md doc/PersonUpdateDto.md doc/QueueStatusDto.md +doc/RecognitionConfig.md doc/SearchAlbumResponseDto.md doc/SearchApi.md doc/SearchAssetDto.md @@ -189,6 +194,9 @@ lib/model/check_duplicate_asset_dto.dart lib/model/check_duplicate_asset_response_dto.dart lib/model/check_existing_assets_dto.dart lib/model/check_existing_assets_response_dto.dart +lib/model/classification_config.dart +lib/model/clip_config.dart +lib/model/clip_mode.dart lib/model/create_album_dto.dart lib/model/create_profile_image_response_dto.dart lib/model/create_tag_dto.dart @@ -216,6 +224,7 @@ lib/model/logout_response_dto.dart lib/model/map_marker_response_dto.dart lib/model/memory_lane_response_dto.dart lib/model/merge_person_dto.dart +lib/model/model_type.dart lib/model/o_auth_callback_dto.dart lib/model/o_auth_config_dto.dart lib/model/o_auth_config_response_dto.dart @@ -225,6 +234,7 @@ lib/model/people_update_item.dart lib/model/person_response_dto.dart lib/model/person_update_dto.dart lib/model/queue_status_dto.dart +lib/model/recognition_config.dart lib/model/search_album_response_dto.dart lib/model/search_asset_dto.dart lib/model/search_asset_response_dto.dart @@ -309,6 +319,9 @@ test/check_duplicate_asset_dto_test.dart test/check_duplicate_asset_response_dto_test.dart test/check_existing_assets_dto_test.dart test/check_existing_assets_response_dto_test.dart +test/classification_config_test.dart +test/clip_config_test.dart +test/clip_mode_test.dart test/create_album_dto_test.dart test/create_profile_image_response_dto_test.dart test/create_tag_dto_test.dart @@ -337,6 +350,7 @@ test/logout_response_dto_test.dart test/map_marker_response_dto_test.dart test/memory_lane_response_dto_test.dart 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zWbG)I=QK?{x!ge_hM1>i3#8Cg2aqFy2dr(!6v^^;%Pn=;Z%YmIns|Bw|1tonSJVsC4 mL2ny03%PHHQ?}$$G51MTtsJhC((YqPiTqfS_>I5lE&C54lQNkA literal 0 HcmV?d00001 diff --git a/mobile/openapi/test/system_config_machine_learning_dto_test.dart b/mobile/openapi/test/system_config_machine_learning_dto_test.dart index e8003763fc52d291595270884ce7ce957c9fff63..a6d04bd7bf815daecd67a97fc67c0e4113c17daf 100644 GIT binary patch delta 143 zcmZ3+F`r|@KSpKeoW$bd%(Tqp#FEVXJm>tpw9IscWE8>4ADI;S(1d0)>+(DMcm}{V sWEOywu_WgJ89>R&#Y~CHL8;04>3Nw*2B#$^XC~$#i32qm0o8W{0Blw^(*OVf delta 139 zcmbQwv5aHGKSr^n{QMk+ { personMock = newPersonRepositoryMock(); searchMock = newSearchRepositoryMock(); storageMock = newStorageRepositoryMock(); + configMock = newSystemConfigRepositoryMock(); mediaMock.crop.mockResolvedValue(croppedFace); @@ -179,9 +180,18 @@ describe(FacialRecognitionService.name, () => { machineLearningMock.detectFaces.mockResolvedValue([]); assetMock.getByIds.mockResolvedValue([assetStub.image]); await sut.handleRecognizeFaces({ id: assetStub.image.id }); - expect(machineLearningMock.detectFaces).toHaveBeenCalledWith('http://immich-machine-learning:3003', { - imagePath: assetStub.image.resizePath, - }); + expect(machineLearningMock.detectFaces).toHaveBeenCalledWith( + 'http://immich-machine-learning:3003', + { + imagePath: assetStub.image.resizePath, + }, + { + enabled: true, + maxDistance: 0.6, + minScore: 0.7, + modelName: 'buffalo_l', + }, + ); expect(faceMock.create).not.toHaveBeenCalled(); expect(jobMock.queue).not.toHaveBeenCalled(); }); diff --git a/server/src/domain/facial-recognition/facial-recognition.services.ts b/server/src/domain/facial-recognition/facial-recognition.services.ts index 68886d1f2b..ad90dca24a 100644 --- a/server/src/domain/facial-recognition/facial-recognition.services.ts +++ b/server/src/domain/facial-recognition/facial-recognition.services.ts @@ -32,7 +32,7 @@ export class FacialRecognitionService { async handleQueueRecognizeFaces({ force }: IBaseJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { + if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) { return true; } @@ -59,7 +59,7 @@ export class FacialRecognitionService { async handleRecognizeFaces({ id }: IEntityJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { + if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) { return true; } @@ -68,7 +68,11 @@ export class FacialRecognitionService { return false; } - const faces = await this.machineLearning.detectFaces(machineLearning.url, { imagePath: asset.resizePath }); + const faces = await this.machineLearning.detectFaces( + machineLearning.url, + { imagePath: asset.resizePath }, + machineLearning.facialRecognition, + ); this.logger.debug(`${faces.length} faces detected in ${asset.resizePath}`); this.logger.verbose(faces.map((face) => ({ ...face, embedding: `float[${face.embedding.length}]` }))); @@ -80,7 +84,7 @@ export class FacialRecognitionService { // try to find a matching face and link to the associated person // The closer to 0, the better the match. Range is from 0 to 2 - if (faceSearchResult.total && faceSearchResult.distances[0] < 0.6) { + if (faceSearchResult.total && faceSearchResult.distances[0] <= machineLearning.facialRecognition.maxDistance) { this.logger.verbose(`Match face with distance ${faceSearchResult.distances[0]}`); personId = faceSearchResult.items[0].personId; } @@ -115,7 +119,7 @@ export class FacialRecognitionService { async handleGenerateFaceThumbnail(data: IFaceThumbnailJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { + if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) { return true; } diff --git a/server/src/domain/search/search.repository.ts b/server/src/domain/search/search.repository.ts index 78885bff00..40ff4e8520 100644 --- a/server/src/domain/search/search.repository.ts +++ b/server/src/domain/search/search.repository.ts @@ -86,6 +86,7 @@ export interface ISearchRepository { deleteAssets(ids: string[]): Promise; deleteFaces(ids: string[]): Promise; deleteAllFaces(): Promise; + updateCLIPField(num_dim: number): Promise; searchAlbums(query: string, filters: SearchFilter): Promise>; searchAssets(query: string, filters: SearchFilter): Promise>; diff --git a/server/src/domain/search/search.service.ts b/server/src/domain/search/search.service.ts index 29edcfc6c4..8084b4f6b9 100644 --- a/server/src/domain/search/search.service.ts +++ b/server/src/domain/search/search.service.ts @@ -121,15 +121,18 @@ export class SearchService { await this.configCore.requireFeature(FeatureFlag.SEARCH); const query = dto.q || dto.query || '*'; - const hasClip = machineLearning.enabled && machineLearning.clipEncodeEnabled; + const hasClip = machineLearning.enabled && machineLearning.clip.enabled; const strategy = dto.clip && hasClip ? SearchStrategy.CLIP : SearchStrategy.TEXT; const filters = { userId: authUser.id, ...dto }; let assets: SearchResult; switch (strategy) { case SearchStrategy.CLIP: - const clip = await this.machineLearning.encodeText(machineLearning.url, query); - assets = await this.searchRepository.vectorSearch(clip, filters); + const { + machineLearning: { clip }, + } = await this.configCore.getConfig(); + const embedding = await this.machineLearning.encodeText(machineLearning.url, { text: query }, clip); + assets = await this.searchRepository.vectorSearch(embedding, filters); break; case SearchStrategy.TEXT: default: diff --git a/server/src/domain/smart-info/dto/index.ts b/server/src/domain/smart-info/dto/index.ts new file mode 100644 index 0000000000..aa672a787c --- /dev/null +++ b/server/src/domain/smart-info/dto/index.ts @@ -0,0 +1 @@ +export * from './model-config.dto'; diff --git a/server/src/domain/smart-info/dto/model-config.dto.ts b/server/src/domain/smart-info/dto/model-config.dto.ts new file mode 100644 index 0000000000..40da07ab9e --- /dev/null +++ b/server/src/domain/smart-info/dto/model-config.dto.ts @@ -0,0 +1,50 @@ +import { ApiProperty } from '@nestjs/swagger'; +import { Type } from 'class-transformer'; +import { IsBoolean, IsEnum, IsNotEmpty, IsNumber, IsOptional, IsString, Max, Min } from 'class-validator'; +import { CLIPMode, ModelType } from '../machine-learning.interface'; + +export class ModelConfig { + @IsBoolean() + enabled!: boolean; + + @IsString() + @IsNotEmpty() + modelName!: string; + + @IsEnum(ModelType) + @IsOptional() + @ApiProperty({ enumName: 'ModelType', enum: ModelType }) + modelType?: ModelType; +} + +export class ClassificationConfig extends ModelConfig { + @IsNumber() + @Min(0) + @Max(1) + @Type(() => Number) + @ApiProperty({ type: 'integer' }) + minScore!: number; +} + +export class CLIPConfig extends ModelConfig { + @IsEnum(CLIPMode) + @IsOptional() + @ApiProperty({ enumName: 'CLIPMode', enum: CLIPMode }) + mode?: CLIPMode; +} + +export class RecognitionConfig extends ModelConfig { + @IsNumber() + @Min(0) + @Max(1) + @Type(() => Number) + @ApiProperty({ type: 'integer' }) + minScore!: number; + + @IsNumber() + @Min(0) + @Max(2) + @Type(() => Number) + @ApiProperty({ type: 'integer' }) + maxDistance!: number; +} diff --git a/server/src/domain/smart-info/index.ts b/server/src/domain/smart-info/index.ts index 86c2d1eccd..b53b21428d 100644 --- a/server/src/domain/smart-info/index.ts +++ b/server/src/domain/smart-info/index.ts @@ -1,3 +1,4 @@ +export * from './dto'; export * from './machine-learning.interface'; export * from './smart-info.repository'; export * from './smart-info.service'; diff --git a/server/src/domain/smart-info/machine-learning.interface.ts b/server/src/domain/smart-info/machine-learning.interface.ts index 7c431fd5f3..8e4b3789b4 100644 --- a/server/src/domain/smart-info/machine-learning.interface.ts +++ b/server/src/domain/smart-info/machine-learning.interface.ts @@ -1,9 +1,15 @@ +import { ClassificationConfig, CLIPConfig, RecognitionConfig } from './dto'; + export const IMachineLearningRepository = 'IMachineLearningRepository'; -export interface MachineLearningInput { +export interface VisionModelInput { imagePath: string; } +export interface TextModelInput { + text: string; +} + export interface BoundingBox { x1: number; y1: number; @@ -19,9 +25,20 @@ export interface DetectFaceResult { embedding: number[]; } -export interface IMachineLearningRepository { - classifyImage(url: string, input: MachineLearningInput): Promise; - encodeImage(url: string, input: MachineLearningInput): Promise; - encodeText(url: string, input: string): Promise; - detectFaces(url: string, input: MachineLearningInput): Promise; +export enum ModelType { + IMAGE_CLASSIFICATION = 'image-classification', + FACIAL_RECOGNITION = 'facial-recognition', + CLIP = 'clip', +} + +export enum CLIPMode { + VISION = 'vision', + TEXT = 'text', +} + +export interface IMachineLearningRepository { + classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise; + encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise; + encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise; + detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise; } diff --git a/server/src/domain/smart-info/smart-info.service.spec.ts b/server/src/domain/smart-info/smart-info.service.spec.ts index 7461058e29..8ff1437a0c 100644 --- a/server/src/domain/smart-info/smart-info.service.spec.ts +++ b/server/src/domain/smart-info/smart-info.service.spec.ts @@ -84,9 +84,13 @@ describe(SmartInfoService.name, () => { await sut.handleClassifyImage({ id: asset.id }); - expect(machineMock.classifyImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', { - imagePath: 'path/to/resize.ext', - }); + expect(machineMock.classifyImage).toHaveBeenCalledWith( + 'http://immich-machine-learning:3003', + { + imagePath: 'path/to/resize.ext', + }, + { enabled: true, minScore: 0.9, modelName: 'microsoft/resnet-50' }, + ); expect(smartMock.upsert).toHaveBeenCalledWith({ assetId: 'asset-1', tags: ['tag1', 'tag2', 'tag3'], @@ -141,13 +145,16 @@ describe(SmartInfoService.name, () => { }); it('should save the returned objects', async () => { + smartMock.upsert.mockResolvedValue(); machineMock.encodeImage.mockResolvedValue([0.01, 0.02, 0.03]); await sut.handleEncodeClip({ id: asset.id }); - expect(machineMock.encodeImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', { - imagePath: 'path/to/resize.ext', - }); + expect(machineMock.encodeImage).toHaveBeenCalledWith( + 'http://immich-machine-learning:3003', + { imagePath: 'path/to/resize.ext' }, + { enabled: true, modelName: 'ViT-B-32::openai' }, + ); expect(smartMock.upsert).toHaveBeenCalledWith({ assetId: 'asset-1', clipEmbedding: [0.01, 0.02, 0.03], diff --git a/server/src/domain/smart-info/smart-info.service.ts b/server/src/domain/smart-info/smart-info.service.ts index 2512c4c32d..319324b2a8 100644 --- a/server/src/domain/smart-info/smart-info.service.ts +++ b/server/src/domain/smart-info/smart-info.service.ts @@ -22,7 +22,7 @@ export class SmartInfoService { async handleQueueObjectTagging({ force }: IBaseJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.tagImageEnabled) { + if (!machineLearning.enabled || !machineLearning.classification.enabled) { return true; } @@ -43,7 +43,7 @@ export class SmartInfoService { async handleClassifyImage({ id }: IEntityJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.tagImageEnabled) { + if (!machineLearning.enabled || !machineLearning.classification.enabled) { return true; } @@ -52,7 +52,11 @@ export class SmartInfoService { return false; } - const tags = await this.machineLearning.classifyImage(machineLearning.url, { imagePath: asset.resizePath }); + const tags = await this.machineLearning.classifyImage( + machineLearning.url, + { imagePath: asset.resizePath }, + machineLearning.classification, + ); await this.repository.upsert({ assetId: asset.id, tags }); return true; @@ -60,7 +64,7 @@ export class SmartInfoService { async handleQueueEncodeClip({ force }: IBaseJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) { + if (!machineLearning.enabled || !machineLearning.clip.enabled) { return true; } @@ -81,7 +85,7 @@ export class SmartInfoService { async handleEncodeClip({ id }: IEntityJob) { const { machineLearning } = await this.configCore.getConfig(); - if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) { + if (!machineLearning.enabled || !machineLearning.clip.enabled) { return true; } @@ -90,7 +94,12 @@ export class SmartInfoService { return false; } - const clipEmbedding = await this.machineLearning.encodeImage(machineLearning.url, { imagePath: asset.resizePath }); + const clipEmbedding = await this.machineLearning.encodeImage( + machineLearning.url, + { imagePath: asset.resizePath }, + machineLearning.clip, + ); + await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding }); return true; diff --git a/server/src/domain/system-config/dto/system-config-machine-learning.dto.ts b/server/src/domain/system-config/dto/system-config-machine-learning.dto.ts index b4063669d3..330560ea87 100644 --- a/server/src/domain/system-config/dto/system-config-machine-learning.dto.ts +++ b/server/src/domain/system-config/dto/system-config-machine-learning.dto.ts @@ -1,4 +1,6 @@ -import { IsBoolean, IsUrl, ValidateIf } from 'class-validator'; +import { ClassificationConfig, CLIPConfig, RecognitionConfig } from '@app/domain'; +import { Type } from 'class-transformer'; +import { IsBoolean, IsObject, IsUrl, ValidateIf, ValidateNested } from 'class-validator'; export class SystemConfigMachineLearningDto { @IsBoolean() @@ -8,12 +10,18 @@ export class SystemConfigMachineLearningDto { @ValidateIf((dto) => dto.enabled) url!: string; - @IsBoolean() - clipEncodeEnabled!: boolean; + @Type(() => ClassificationConfig) + @ValidateNested() + @IsObject() + classification!: ClassificationConfig; - @IsBoolean() - facialRecognitionEnabled!: boolean; + @Type(() => CLIPConfig) + @ValidateNested() + @IsObject() + clip!: CLIPConfig; - @IsBoolean() - tagImageEnabled!: boolean; + @Type(() => RecognitionConfig) + @ValidateNested() + @IsObject() + facialRecognition!: RecognitionConfig; } diff --git a/server/src/domain/system-config/system-config.core.ts b/server/src/domain/system-config/system-config.core.ts index 5fa55a7092..f4154cd154 100644 --- a/server/src/domain/system-config/system-config.core.ts +++ b/server/src/domain/system-config/system-config.core.ts @@ -47,12 +47,25 @@ export const defaults = Object.freeze({ [QueueName.THUMBNAIL_GENERATION]: { concurrency: 5 }, [QueueName.VIDEO_CONVERSION]: { concurrency: 1 }, }, + machineLearning: { enabled: process.env.IMMICH_MACHINE_LEARNING_ENABLED !== 'false', url: process.env.IMMICH_MACHINE_LEARNING_URL || 'http://immich-machine-learning:3003', - facialRecognitionEnabled: true, - tagImageEnabled: true, - clipEncodeEnabled: true, + classification: { + enabled: true, + modelName: 'microsoft/resnet-50', + minScore: 0.9, + }, + clip: { + enabled: true, + modelName: 'ViT-B-32::openai', + }, + facialRecognition: { + enabled: true, + modelName: 'buffalo_l', + minScore: 0.7, + maxDistance: 0.6, + }, }, oauth: { enabled: false, @@ -143,9 +156,9 @@ export class SystemConfigCore { const mlEnabled = config.machineLearning.enabled; return { - [FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clipEncodeEnabled, - [FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognitionEnabled, - [FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.tagImageEnabled, + [FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clip.enabled, + [FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognition.enabled, + [FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.classification.enabled, [FeatureFlag.SIDECAR]: true, [FeatureFlag.SEARCH]: process.env.TYPESENSE_ENABLED !== 'false', @@ -230,7 +243,7 @@ export class SystemConfigCore { _.set(config, key, value); } - return _.defaultsDeep(config, defaults) as SystemConfig; + return plainToClass(SystemConfigDto, _.defaultsDeep(config, defaults)); } private async loadFromFile(filepath: string, force = false) { diff --git a/server/src/domain/system-config/system-config.service.spec.ts b/server/src/domain/system-config/system-config.service.spec.ts index fd450a2963..3e0d8b4705 100644 --- a/server/src/domain/system-config/system-config.service.spec.ts +++ b/server/src/domain/system-config/system-config.service.spec.ts @@ -49,9 +49,21 @@ const updatedConfig = Object.freeze({ machineLearning: { enabled: true, url: 'http://immich-machine-learning:3003', - facialRecognitionEnabled: true, - tagImageEnabled: true, - clipEncodeEnabled: true, + classification: { + enabled: true, + modelName: 'microsoft/resnet-50', + minScore: 0.9, + }, + clip: { + enabled: true, + modelName: 'ViT-B-32::openai', + }, + facialRecognition: { + enabled: true, + modelName: 'buffalo_l', + minScore: 0.7, + maxDistance: 0.6, + }, }, oauth: { autoLaunch: true, diff --git a/server/src/infra/entities/system-config.entity.ts b/server/src/infra/entities/system-config.entity.ts index 642f40c16c..f124a1306c 100644 --- a/server/src/infra/entities/system-config.entity.ts +++ b/server/src/infra/entities/system-config.entity.ts @@ -1,4 +1,4 @@ -import { QueueName } from '@app/domain/job/job.constants'; +import { QueueName } from '@app/domain'; import { Column, Entity, PrimaryColumn } from 'typeorm'; @Entity('system_config') @@ -39,9 +39,18 @@ export enum SystemConfigKey { MACHINE_LEARNING_ENABLED = 'machineLearning.enabled', MACHINE_LEARNING_URL = 'machineLearning.url', - MACHINE_LEARNING_FACIAL_RECOGNITION_ENABLED = 'machineLearning.facialRecognitionEnabled', - MACHINE_LEARNING_TAG_IMAGE_ENABLED = 'machineLearning.tagImageEnabled', - MACHINE_LEARNING_CLIP_ENCODE_ENABLED = 'machineLearning.clipEncodeEnabled', + + MACHINE_LEARNING_CLASSIFICATION_ENABLED = 'machineLearning.classification.enabled', + MACHINE_LEARNING_CLASSIFICATION_MODEL_NAME = 'machineLearning.classification.modelName', + MACHINE_LEARNING_CLASSIFICATION_MIN_SCORE = 'machineLearning.classification.minScore', + + MACHINE_LEARNING_CLIP_ENABLED = 'machineLearning.clip.enabled', + MACHINE_LEARNING_CLIP_MODEL_NAME = 'machineLearning.clip.modelName', + + MACHINE_LEARNING_FACIAL_RECOGNITION_ENABLED = 'machineLearning.facialRecognition.enabled', + MACHINE_LEARNING_FACIAL_RECOGNITION_MODEL_NAME = 'machineLearning.facialRecognition.modelName', + MACHINE_LEARNING_FACIAL_RECOGNITION_MIN_SCORE = 'machineLearning.facialRecognition.minScore', + MACHINE_LEARNING_FACIAL_RECOGNITION_MAX_DISTANCE = 'machineLearning.facialRecognition.maxDistance', OAUTH_ENABLED = 'oauth.enabled', OAUTH_ISSUER_URL = 'oauth.issuerUrl', @@ -114,9 +123,21 @@ export interface SystemConfig { machineLearning: { enabled: boolean; url: string; - clipEncodeEnabled: boolean; - facialRecognitionEnabled: boolean; - tagImageEnabled: boolean; + classification: { + enabled: boolean; + modelName: string; + minScore: number; + }; + clip: { + enabled: boolean; + modelName: string; + }; + facialRecognition: { + enabled: boolean; + modelName: string; + minScore: number; + maxDistance: number; + }; }; oauth: { enabled: boolean; diff --git a/server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts b/server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts new file mode 100644 index 0000000000..096356f6e0 --- /dev/null +++ b/server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts @@ -0,0 +1,25 @@ +import { MigrationInterface, QueryRunner } from "typeorm" + +export class RenameMLEnableFlags1693236627291 implements MigrationInterface { + public async up(queryRunner: QueryRunner): Promise { + await queryRunner.query(` + UPDATE system_config SET key = CASE + WHEN key = 'ffmpeg.classificationEnabled' THEN 'ffmpeg.classification.enabled' + WHEN key = 'ffmpeg.clipEnabled' THEN 'ffmpeg.clip.enabled' + WHEN key = 'ffmpeg.facialRecognitionEnabled' THEN 'ffmpeg.facialRecognition.enabled' + ELSE key + END + `); + } + + public async down(queryRunner: QueryRunner): Promise { + await queryRunner.query(` + UPDATE system_config SET key = CASE + WHEN key = 'ffmpeg.classification.enabled' THEN 'ffmpeg.classificationEnabled' + WHEN key = 'ffmpeg.clip.enabled' THEN 'ffmpeg.clipEnabled' + WHEN key = 'ffmpeg.facialRecognition.enabled' THEN 'ffmpeg.facialRecognitionEnabled' + ELSE key + END + `); + } +} diff --git a/server/src/infra/repositories/machine-learning.repository.ts b/server/src/infra/repositories/machine-learning.repository.ts index 3d3e22449a..fd4e934293 100644 --- a/server/src/infra/repositories/machine-learning.repository.ts +++ b/server/src/infra/repositories/machine-learning.repository.ts @@ -1,29 +1,65 @@ -import { DetectFaceResult, IMachineLearningRepository, MachineLearningInput } from '@app/domain'; +import { + ClassificationConfig, + CLIPConfig, + CLIPMode, + DetectFaceResult, + IMachineLearningRepository, + ModelConfig, + ModelType, + RecognitionConfig, + TextModelInput, + VisionModelInput, +} from '@app/domain'; import { Injectable } from '@nestjs/common'; -import axios from 'axios'; -import { createReadStream } from 'fs'; - -const client = axios.create(); +import { readFile } from 'fs/promises'; @Injectable() export class MachineLearningRepository implements IMachineLearningRepository { - private post(input: MachineLearningInput, endpoint: string): Promise { - return client.post(endpoint, createReadStream(input.imagePath)).then((res) => res.data); + private async post(url: string, input: TextModelInput | VisionModelInput, config: ModelConfig): Promise { + const formData = await this.getFormData(input, config); + const res = await fetch(`${url}/predict`, { method: 'POST', body: formData }); + return res.json(); } - classifyImage(url: string, input: MachineLearningInput): Promise { - return this.post(input, `${url}/image-classifier/tag-image`); + classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise { + return this.post(url, input, { ...config, modelType: ModelType.IMAGE_CLASSIFICATION }); } - detectFaces(url: string, input: MachineLearningInput): Promise { - return this.post(input, `${url}/facial-recognition/detect-faces`); + detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise { + return this.post(url, input, { ...config, modelType: ModelType.FACIAL_RECOGNITION }); } - encodeImage(url: string, input: MachineLearningInput): Promise { - return this.post(input, `${url}/sentence-transformer/encode-image`); + encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise { + return this.post(url, input, { + ...config, + modelType: ModelType.CLIP, + mode: CLIPMode.VISION, + } as CLIPConfig); } - encodeText(url: string, input: string): Promise { - return client.post(`${url}/sentence-transformer/encode-text`, { text: input }).then((res) => res.data); + encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise { + return this.post(url, input, { ...config, modelType: ModelType.CLIP, mode: CLIPMode.TEXT } as CLIPConfig); + } + + async getFormData(input: TextModelInput | VisionModelInput, config: ModelConfig): Promise { + const formData = new FormData(); + const { modelName, modelType, ...options } = config; + + formData.append('modelName', modelName); + if (modelType) { + formData.append('modelType', modelType); + } + if (options) { + formData.append('options', JSON.stringify(options)); + } + if ('imagePath' in input) { + formData.append('image', new Blob([await readFile(input.imagePath)])); + } else if ('text' in input) { + formData.append('text', input.text); + } else { + throw new Error('Invalid input'); + } + + return formData; } } diff --git a/server/src/infra/repositories/typesense.repository.ts b/server/src/infra/repositories/typesense.repository.ts index bb78a0995c..594f9973bb 100644 --- a/server/src/infra/repositories/typesense.repository.ts +++ b/server/src/infra/repositories/typesense.repository.ts @@ -52,6 +52,8 @@ export class TypesenseRepository implements ISearchRepository { private logger = new Logger(TypesenseRepository.name); private _client: Client | null = null; + private _updateCLIPLock = false; + private get client(): Client { if (!this._client) { throw new Error('Typesense client not available (no apiKey was provided)'); @@ -141,7 +143,7 @@ export class TypesenseRepository implements ISearchRepository { await this.updateAlias(collection); } } catch (error: any) { - this.handleError(error); + await this.handleError(error); } } @@ -221,6 +223,30 @@ export class TypesenseRepository implements ISearchRepository { return records.num_deleted; } + async deleteAllAssets(): Promise { + const records = await this.client.collections(assetSchema.name).documents().delete({ filter_by: 'ownerId:!=null' }); + return records.num_deleted; + } + + async updateCLIPField(num_dim: number): Promise { + const clipField = assetSchema.fields?.find((field) => field.name === 'smartInfo.clipEmbedding'); + if (clipField && !this._updateCLIPLock) { + try { + this._updateCLIPLock = true; + clipField.num_dim = num_dim; + await this.deleteAllAssets(); + await this.client + .collections(assetSchema.name) + .update({ fields: [{ name: 'smartInfo.clipEmbedding', drop: true } as any, clipField] }); + this.logger.log(`Successfully updated CLIP dimensions to ${num_dim}`); + } catch (err: any) { + this.logger.error(`Error while updating CLIP field: ${err.message}`); + } finally { + this._updateCLIPLock = false; + } + } + } + async delete(collection: SearchCollection, ids: string[]): Promise { await this.client .collections(schemaMap[collection].name) @@ -326,21 +352,34 @@ export class TypesenseRepository implements ISearchRepository { } as SearchResult; } - private handleError(error: any) { + private async handleError(error: any) { this.logger.error('Unable to index documents'); const results = error.importResults || []; + let dimsChanged = false; for (const result of results) { try { result.document = JSON.parse(result.document); + if (result.error.includes('Field `smartInfo.clipEmbedding` must have')) { + dimsChanged = true; + this.logger.warn( + `CLIP embedding dimensions have changed, now ${result.document.smartInfo.clipEmbedding.length} dims. Updating schema...`, + ); + await this.updateCLIPField(result.document.smartInfo.clipEmbedding.length); + break; + } + if (result.document?.smartInfo?.clipEmbedding) { result.document.smartInfo.clipEmbedding = ''; } - } catch {} + } catch (err: any) { + this.logger.error(`Error while updating CLIP field: ${(err.message, err.stack)}`); + } } - this.logger.verbose(JSON.stringify(results, null, 2)); + if (!dimsChanged) { + this.logger.log(JSON.stringify(results, null, 2)); + } } - private async updateAlias(collection: SearchCollection) { const schema = schemaMap[collection]; const alias = await this.client diff --git a/server/test/repositories/search.repository.mock.ts b/server/test/repositories/search.repository.mock.ts index 5bf8f63397..af4dbce64d 100644 --- a/server/test/repositories/search.repository.mock.ts +++ b/server/test/repositories/search.repository.mock.ts @@ -11,6 +11,7 @@ export const newSearchRepositoryMock = (): jest.Mocked => { deleteAssets: jest.fn(), deleteFaces: jest.fn(), deleteAllFaces: jest.fn(), + updateCLIPField: jest.fn(), searchAssets: jest.fn(), searchAlbums: jest.fn(), vectorSearch: jest.fn(), diff --git a/web/src/api/open-api/api.ts b/web/src/api/open-api/api.ts index 36189d39f4..f3246f0963 100644 --- a/web/src/api/open-api/api.ts +++ b/web/src/api/open-api/api.ts @@ -862,6 +862,53 @@ export interface BulkIdsDto { */ 'ids': Array; } +/** + * + * @export + * @interface CLIPConfig + */ +export interface CLIPConfig { + /** + * + * @type {boolean} + * @memberof CLIPConfig + */ + 'enabled': boolean; + /** + * + * @type {CLIPMode} + * @memberof CLIPConfig + */ + 'mode'?: CLIPMode; + /** + * + * @type {string} + * @memberof CLIPConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof CLIPConfig + */ + 'modelType'?: ModelType; +} + + +/** + * + * @export + * @enum {string} + */ + +export const CLIPMode = { + Vision: 'vision', + Text: 'text' +} as const; + +export type CLIPMode = typeof CLIPMode[keyof typeof CLIPMode]; + + /** * * @export @@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto { */ 'existingIds': Array; } +/** + * + * @export + * @interface ClassificationConfig + */ +export interface ClassificationConfig { + /** + * + * @type {boolean} + * @memberof ClassificationConfig + */ + 'enabled': boolean; + /** + * + * @type {number} + * @memberof ClassificationConfig + */ + 'minScore': number; + /** + * + * @type {string} + * @memberof ClassificationConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof ClassificationConfig + */ + 'modelType'?: ModelType; +} + + /** * * @export @@ -1766,6 +1846,21 @@ export interface MergePersonDto { */ 'ids': Array; } +/** + * + * @export + * @enum {string} + */ + +export const ModelType = { + ImageClassification: 'image-classification', + FacialRecognition: 'facial-recognition', + Clip: 'clip' +} as const; + +export type ModelType = typeof ModelType[keyof typeof ModelType]; + + /** * * @export @@ -1991,6 +2086,45 @@ export interface QueueStatusDto { */ 'isPaused': boolean; } +/** + * + * @export + * @interface RecognitionConfig + */ +export interface RecognitionConfig { + /** + * + * @type {boolean} + * @memberof RecognitionConfig + */ + 'enabled': boolean; + /** + * + * @type {number} + * @memberof RecognitionConfig + */ + 'maxDistance': number; + /** + * + * @type {number} + * @memberof RecognitionConfig + */ + 'minScore': number; + /** + * + * @type {string} + * @memberof RecognitionConfig + */ + 'modelName': string; + /** + * + * @type {ModelType} + * @memberof RecognitionConfig + */ + 'modelType'?: ModelType; +} + + /** * * @export @@ -2803,10 +2937,16 @@ export interface SystemConfigJobDto { export interface SystemConfigMachineLearningDto { /** * - * @type {boolean} + * @type {ClassificationConfig} * @memberof SystemConfigMachineLearningDto */ - 'clipEncodeEnabled': boolean; + 'classification': ClassificationConfig; + /** + * + * @type {CLIPConfig} + * @memberof SystemConfigMachineLearningDto + */ + 'clip': CLIPConfig; /** * * @type {boolean} @@ -2815,16 +2955,10 @@ export interface SystemConfigMachineLearningDto { 'enabled': boolean; /** * - * @type {boolean} + * @type {RecognitionConfig} * @memberof SystemConfigMachineLearningDto */ - 'facialRecognitionEnabled': boolean; - /** - * - * @type {boolean} - * @memberof SystemConfigMachineLearningDto - */ - 'tagImageEnabled': boolean; + 'facialRecognition': RecognitionConfig; /** * * @type {string} diff --git a/web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte b/web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte index f8ac971cf2..af30634d25 100644 --- a/web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte +++ b/web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte @@ -4,38 +4,45 @@ NotificationType, } from '$lib/components/shared-components/notification/notification'; import { handleError } from '$lib/utils/handle-error'; - import { api, SystemConfigDto } from '@api'; + import { api, SystemConfigMachineLearningDto } from '@api'; import { isEqual } from 'lodash-es'; import { fade } from 'svelte/transition'; import SettingButtonsRow from '../setting-buttons-row.svelte'; import SettingInputField, { SettingInputFieldType } from '../setting-input-field.svelte'; import SettingSwitch from '../setting-switch.svelte'; + import SettingAccordion from '../setting-accordion.svelte'; + import SettingSelect from '../setting-select.svelte'; + export let machineLearningConfig: SystemConfigMachineLearningDto; // this is the config that is being edited export let disabled = false; - let config: SystemConfigDto; - let defaultConfig: SystemConfigDto; + let savedConfig: SystemConfigMachineLearningDto; + let defaultConfig: SystemConfigMachineLearningDto; async function refreshConfig() { - [config, defaultConfig] = await Promise.all([ - api.systemConfigApi.getConfig().then((res) => res.data), - api.systemConfigApi.getDefaults().then((res) => res.data), + [savedConfig, defaultConfig] = await Promise.all([ + api.systemConfigApi.getConfig().then((res) => res.data.machineLearning), + api.systemConfigApi.getDefaults().then((res) => res.data.machineLearning), ]); } async function reset() { const { data: resetConfig } = await api.systemConfigApi.getConfig(); - config = resetConfig; + machineLearningConfig = { ...resetConfig.machineLearning }; + savedConfig = { ...resetConfig.machineLearning }; notificationController.show({ message: 'Reset to the last saved settings', type: NotificationType.Info }); } async function saveSetting() { try { const { data: current } = await api.systemConfigApi.getConfig(); - await api.systemConfigApi.updateConfig({ - systemConfigDto: { ...current, machineLearning: config.machineLearning }, + const result = await api.systemConfigApi.updateConfig({ + systemConfigDto: { ...current, machineLearning: machineLearningConfig }, }); - await refreshConfig(); + + machineLearningConfig = { ...result.data.machineLearning }; + savedConfig = { ...result.data.machineLearning }; + notificationController.show({ message: 'Settings saved', type: NotificationType.Info }); } catch (error) { handleError(error, 'Unable to save settings'); @@ -43,10 +50,7 @@ } async function resetToDefault() { - await refreshConfig(); - const { data: defaults } = await api.systemConfigApi.getDefaults(); - config = defaults; - + machineLearningConfig = { ...defaultConfig }; notificationController.show({ message: 'Reset settings to defaults', type: NotificationType.Info }); } @@ -54,52 +58,152 @@
{#await refreshConfig() then}
-
- + +
+ -
+
- + +
- + +
+ - +
- + +

+ The name of an image classification model listed here. It must be tagged with the 'Image Classification' task and must support ONNX conversion. +

+
+ + +
+
+ + +
+ + +
+ + +

+ The name of a CLIP model listed here. Note that you must re-run the 'Encode CLIP' job for all images upon changing a model. +

+
+
+
+ + +
+ + +
+ + + + + + +
+
diff --git a/web/src/lib/components/admin-page/settings/setting-input-field.svelte b/web/src/lib/components/admin-page/settings/setting-input-field.svelte index 65a5018e58..843e799b39 100644 --- a/web/src/lib/components/admin-page/settings/setting-input-field.svelte +++ b/web/src/lib/components/admin-page/settings/setting-input-field.svelte @@ -13,6 +13,9 @@ export let inputType: SettingInputFieldType; export let value: string | number; + export let min = Number.MIN_VALUE.toString(); + export let max = Number.MAX_VALUE.toString(); + export let step = '1'; export let label = ''; export let desc = ''; export let required = false; @@ -48,6 +51,8 @@

{desc}

+ {:else} + {/if} + + + + - - - -