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Code Releases Activity

feat(ml)!: customizable ML settings (#3891)

Browse source 
* 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 <alex.tran1502@gmail.com>
This commit is contained in:
Mert 2023-08-29 09:58:00 -04:00 committed by GitHub
parent 22f5e05060
commit bcc36d14a1
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GPG key ID: 4AEE18F83AFDEB23
56 changed files with 1424 additions and 620 deletions
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154
cli/src/api/open-api/api.ts generated
View file

@ -862,6 +862,53 @@ export interface BulkIdsDto {
*/ */
'ids': Array<string>; 'ids': Array<string>;
} }
/**
*
* @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 * @export
@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto {
*/ */
'existingIds': Array<string>; 'existingIds': Array<string>;
} }
/**
*
* @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 * @export
@ -1766,6 +1846,21 @@ export interface MergePersonDto {
*/ */
'ids': Array<string>; 'ids': Array<string>;
} }
/**
*
* @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 * @export
@ -1991,6 +2086,45 @@ export interface QueueStatusDto {
*/ */
'isPaused': boolean; '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 * @export
@ -2803,10 +2937,16 @@ export interface SystemConfigJobDto {
export interface SystemConfigMachineLearningDto { export interface SystemConfigMachineLearningDto {
/** /**
* *
* @type {boolean} * @type {ClassificationConfig}
* @memberof SystemConfigMachineLearningDto * @memberof SystemConfigMachineLearningDto
*/ */
'clipEncodeEnabled': boolean; 'classification': ClassificationConfig;
/**
*
* @type {CLIPConfig}
* @memberof SystemConfigMachineLearningDto
*/
'clip': CLIPConfig;
/** /**
* *
* @type {boolean} * @type {boolean}
@ -2815,16 +2955,10 @@ export interface SystemConfigMachineLearningDto {
'enabled': boolean; 'enabled': boolean;
/** /**
* *
* @type {boolean} * @type {RecognitionConfig}
* @memberof SystemConfigMachineLearningDto * @memberof SystemConfigMachineLearningDto
*/ */
'facialRecognitionEnabled': boolean; 'facialRecognition': RecognitionConfig;
/**
*
* @type {boolean}
* @memberof SystemConfigMachineLearningDto
*/
'tagImageEnabled': boolean;
/** /**
* *
* @type {string} * @type {string}

6
machine-learning/app/config.py
View file

@ -8,17 +8,11 @@ from .schemas import ModelType
class Settings(BaseSettings): class Settings(BaseSettings):
cache_folder: str = "/cache" 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 eager_startup: bool = False
model_ttl: int = 0 model_ttl: int = 0
host: str = "0.0.0.0" host: str = "0.0.0.0"
port: int = 3003 port: int = 3003
workers: int = 1 workers: int = 1
min_face_score: float = 0.7
test_full: bool = False test_full: bool = False
request_threads: int = os.cpu_count() or 4 request_threads: int = os.cpu_count() or 4
model_inter_op_threads: int = 1 model_inter_op_threads: int = 1

111
machine-learning/app/main.py
View file

@ -1,29 +1,26 @@
import asyncio import asyncio
import os import os
from concurrent.futures import ThreadPoolExecutor from concurrent.futures import ThreadPoolExecutor
from io import BytesIO
from typing import Any from typing import Any
import cv2 import orjson
import numpy as np
import uvicorn import uvicorn
from fastapi import Body, Depends, FastAPI from fastapi import FastAPI, Form, HTTPException, UploadFile
from PIL import Image from fastapi.responses import ORJSONResponse
from starlette.formparsers import MultiPartParser
from app.models.base import InferenceModel from app.models.base import InferenceModel
from .config import settings from .config import settings
from .models.cache import ModelCache from .models.cache import ModelCache
from .schemas import ( from .schemas import (
EmbeddingResponse,
FaceResponse,
MessageResponse, MessageResponse,
ModelType, ModelType,
TagResponse,
TextModelRequest,
TextResponse, TextResponse,
) )
MultiPartParser.max_file_size = 2**24 # spools to disk if payload is 16 MiB or larger
app = FastAPI() app = FastAPI()
@ -33,37 +30,9 @@ def init_state() -> None:
app.state.thread_pool = ThreadPoolExecutor(settings.request_threads) 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") @app.on_event("startup")
async def startup_event() -> None: async def startup_event() -> None:
init_state() 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) @app.get("/", response_model=MessageResponse)
@ -76,57 +45,27 @@ def ping() -> str:
return "pong" return "pong"
@app.post( @app.post("/predict")
"/image-classifier/tag-image", async def predict(
response_model=TagResponse, model_name: str = Form(alias="modelName"),
status_code=200, model_type: ModelType = Form(alias="modelType"),
) options: str = Form(default="{}"),
async def image_classification( text: str | None = Form(default=None),
image: Image.Image = Depends(dep_pil_image), image: UploadFile | None = None,
) -> list[str]: ) -> Any:
model = await app.state.model_cache.get(settings.classification_model, ModelType.IMAGE_CLASSIFICATION) if image is not None:
labels = await predict(model, image) inputs: str | bytes = await image.read()
return labels 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( async def run(model: InferenceModel, inputs: Any) -> Any:
"/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:
return await asyncio.get_running_loop().run_in_executor(app.state.thread_pool, model.predict, inputs) return await asyncio.get_running_loop().run_in_executor(app.state.thread_pool, model.predict, inputs)

7
machine-learning/app/models/base.py
View file

@ -60,16 +60,21 @@ class InferenceModel(ABC):
self._load(**model_kwargs) self._load(**model_kwargs)
self._loaded = True self._loaded = True
def predict(self, inputs: Any) -> Any: def predict(self, inputs: Any, **model_kwargs: Any) -> Any:
if not self._loaded: if not self._loaded:
print(f"Loading {self.model_type.value.replace('_', ' ')} model...") print(f"Loading {self.model_type.value.replace('_', ' ')} model...")
self.load() self.load()
if model_kwargs:
self.configure(**model_kwargs)
return self._predict(inputs) return self._predict(inputs)
@abstractmethod @abstractmethod
def _predict(self, inputs: Any) -> Any: def _predict(self, inputs: Any) -> Any:
... ...
def configure(self, **model_kwargs: Any) -> None:
pass
@abstractmethod @abstractmethod
def _download(self, **model_kwargs: Any) -> None: def _download(self, **model_kwargs: Any) -> None:
... ...

10
machine-learning/app/models/clip.py
View file

@ -1,5 +1,6 @@
import os import os
import zipfile import zipfile
from io import BytesIO
from typing import Any, Literal from typing import Any, Literal
import onnxruntime as ort 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.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.pretrained_models import _VISUAL_MODEL_IMAGE_SIZE
from clip_server.model.tokenization import Tokenizer 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 torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from ..schemas import ModelType from ..schemas import ModelType
@ -74,9 +75,12 @@ class CLIPEncoder(InferenceModel):
image_size = _VISUAL_MODEL_IMAGE_SIZE[CLIPOnnxModel.get_model_name(self.model_name)] image_size = _VISUAL_MODEL_IMAGE_SIZE[CLIPOnnxModel.get_model_name(self.model_name)]
self.transform = _transform_pil_image(image_size) 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: match image_or_text:
case Image(): case Image.Image():
if self.mode == "text": if self.mode == "text":
raise TypeError("Cannot encode image as text-only model") raise TypeError("Cannot encode image as text-only model")
pixel_values = self.transform(image_or_text) pixel_values = self.transform(image_or_text)

12
machine-learning/app/models/facial_recognition.py
View file

@ -9,7 +9,6 @@ from insightface.model_zoo import ArcFaceONNX, RetinaFace
from insightface.utils.face_align import norm_crop from insightface.utils.face_align import norm_crop
from insightface.utils.storage import BASE_REPO_URL, download_file from insightface.utils.storage import BASE_REPO_URL, download_file
from ..config import settings
from ..schemas import ModelType from ..schemas import ModelType
from .base import InferenceModel from .base import InferenceModel
@ -20,7 +19,7 @@ class FaceRecognizer(InferenceModel):
def __init__( def __init__(
self, self,
model_name: str, model_name: str,
min_score: float = settings.min_face_score, min_score: float = 0.7,
cache_dir: Path | str | None = None, cache_dir: Path | str | None = None,
**model_kwargs: Any, **model_kwargs: Any,
) -> None: ) -> None:
@ -69,11 +68,13 @@ class FaceRecognizer(InferenceModel):
) )
self.rec_model.prepare(ctx_id=0) 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) bboxes, kpss = self.det_model.detect(image)
if bboxes.size == 0: if bboxes.size == 0:
return [] return []
assert isinstance(kpss, np.ndarray) assert isinstance(image, np.ndarray) and isinstance(kpss, np.ndarray)
scores = bboxes[:, 4].tolist() scores = bboxes[:, 4].tolist()
bboxes = bboxes[:, :4].round().tolist() bboxes = bboxes[:, :4].round().tolist()
@ -102,3 +103,6 @@ class FaceRecognizer(InferenceModel):
@property @property
def cached(self) -> bool: def cached(self) -> bool:
return self.cache_dir.is_dir() and any(self.cache_dir.glob("*.onnx")) 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)

13
machine-learning/app/models/image_classification.py
View file

@ -1,13 +1,13 @@
from io import BytesIO
from pathlib import Path from pathlib import Path
from typing import Any from typing import Any
from huggingface_hub import snapshot_download from huggingface_hub import snapshot_download
from optimum.onnxruntime import ORTModelForImageClassification from optimum.onnxruntime import ORTModelForImageClassification
from optimum.pipelines import pipeline from optimum.pipelines import pipeline
from PIL.Image import Image from PIL import Image
from transformers import AutoImageProcessor from transformers import AutoImageProcessor
from ..config import settings
from ..schemas import ModelType from ..schemas import ModelType
from .base import InferenceModel from .base import InferenceModel
@ -18,7 +18,7 @@ class ImageClassifier(InferenceModel):
def __init__( def __init__(
self, self,
model_name: str, model_name: str,
min_score: float = settings.min_tag_score, min_score: float = 0.9,
cache_dir: Path | str | None = None, cache_dir: Path | str | None = None,
**model_kwargs: Any, **model_kwargs: Any,
) -> None: ) -> None:
@ -56,8 +56,13 @@ class ImageClassifier(InferenceModel):
feature_extractor=processor, 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 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] tags = [tag for pred in predictions for tag in pred["label"].split(", ") if pred["score"] >= self.min_score]
return tags return tags
def configure(self, **model_kwargs: Any) -> None:
self.min_score = model_kwargs.get("min_score", self.min_score)

32
machine-learning/app/schemas.py
View file

@ -1,4 +1,4 @@
from enum import Enum from enum import StrEnum
from pydantic import BaseModel from pydantic import BaseModel
@ -20,18 +20,6 @@ class MessageResponse(BaseModel):
message: str message: str
class TagResponse(BaseModel):
__root__: list[str]
class Embedding(BaseModel):
__root__: list[float]
class EmbeddingResponse(BaseModel):
__root__: Embedding
class BoundingBox(BaseModel): class BoundingBox(BaseModel):
x1: int x1: int
y1: int y1: int
@ -39,23 +27,7 @@ class BoundingBox(BaseModel):
y2: int y2: int
class Face(BaseModel): class ModelType(StrEnum):
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):
IMAGE_CLASSIFICATION = "image-classification" IMAGE_CLASSIFICATION = "image-classification"
CLIP = "clip" CLIP = "clip"
FACIAL_RECOGNITION = "facial-recognition" FACIAL_RECOGNITION = "facial-recognition"

799
machine-learning/poetry.lock generated
View file

@ -720,69 +720,69 @@ files = [
[[package]] [[package]]
name = "cython" name = "cython"
version = "3.0.0" version = "3.0.2"
description = "The Cython compiler for writing C extensions in the Python language." description = "The Cython compiler for writing C extensions in the Python language."
optional = false optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
files = [ files = [
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{file = "Cython-3.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:626a4a6ef4b7ced87c348ea805488e4bd39dad9d0b39659aa9e1040b62bbfedf"}, {file = "Cython-3.0.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c298b1589205ecaaed0457ad05e0c8a43e7db2053607f48ed4a899cb6aa114df"},
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@ -2442,13 +2496,13 @@ numpy = [
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{file = "watchfiles-0.19.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:68dce92b29575dda0f8d30c11742a8e2b9b8ec768ae414b54f7453f27bdf9545"}, {file = "watchfiles-0.20.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89d1de8218874925bce7bb2ae9657efc504411528930d7a83f98b1749864f2ef"},
{file = "watchfiles-0.19.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl", hash = "sha256:5569fc7f967429d4bc87e355cdfdcee6aabe4b620801e2cf5805ea245c06097c"}, {file = "watchfiles-0.20.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl", hash = "sha256:13f995d5152a8ba4ed7c2bbbaeee4e11a5944defc7cacd0ccb4dcbdcfd78029a"},
{file = "watchfiles-0.19.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:5471582658ea56fca122c0f0d0116a36807c63fefd6fdc92c71ca9a4491b6b48"}, {file = "watchfiles-0.20.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:9b5c8d3be7b502f8c43a33c63166ada8828dbb0c6d49c8f9ce990a96de2f5a49"},
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{file = "watchfiles-0.19.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20b44221764955b1e703f012c74015306fb7e79a00c15370785f309b1ed9aa8d"}, {file = "watchfiles-0.20.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87d9e1f75c4f86c93d73b5bd1ebe667558357548f11b4f8af4e0e272f79413ce"},
{file = "watchfiles-0.19.0.tar.gz", hash = "sha256:d9b073073e048081e502b6c6b0b88714c026a1a4c890569238d04aca5f9ca74b"}, {file = "watchfiles-0.20.0.tar.gz", hash = "sha256:728575b6b94c90dd531514677201e8851708e6e4b5fe7028ac506a200b622019"},
] ]
[package.dependencies] [package.dependencies]
@ -4552,4 +4693,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.11" python-versions = "^3.11"
content-hash = "1a8981686295b3de58b41192c608a69a2c05983c47f93451c8a6ed50304b7cb3" content-hash = "6d200d3ea1ccf9fb89f44043e3e0845e70f19aac374b96227559375f44508dc5"

3
machine-learning/pyproject.toml
View file

@ -30,6 +30,9 @@ rich = "^13.4.2"
ftfy = "^6.1.1" ftfy = "^6.1.1"
setuptools = "^68.0.0" setuptools = "^68.0.0"
open-clip-torch = "^2.20.0" open-clip-torch = "^2.20.0"
python-multipart = "^0.0.6"
orjson = "^3.9.5"
safetensors = "0.3.2"
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]
mypy = "^1.3.0" mypy = "^1.3.0"

15
mobile/openapi/.openapi-generator/FILES generated
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@ -35,11 +35,14 @@ doc/AuthDeviceResponseDto.md
doc/AuthenticationApi.md doc/AuthenticationApi.md
doc/BulkIdResponseDto.md doc/BulkIdResponseDto.md
doc/BulkIdsDto.md doc/BulkIdsDto.md
doc/CLIPConfig.md
doc/CLIPMode.md
doc/ChangePasswordDto.md doc/ChangePasswordDto.md
doc/CheckDuplicateAssetDto.md doc/CheckDuplicateAssetDto.md
doc/CheckDuplicateAssetResponseDto.md doc/CheckDuplicateAssetResponseDto.md
doc/CheckExistingAssetsDto.md doc/CheckExistingAssetsDto.md
doc/CheckExistingAssetsResponseDto.md doc/CheckExistingAssetsResponseDto.md
doc/ClassificationConfig.md
doc/CreateAlbumDto.md doc/CreateAlbumDto.md
doc/CreateProfileImageResponseDto.md doc/CreateProfileImageResponseDto.md
doc/CreateTagDto.md doc/CreateTagDto.md
@ -68,6 +71,7 @@ doc/LogoutResponseDto.md
doc/MapMarkerResponseDto.md doc/MapMarkerResponseDto.md
doc/MemoryLaneResponseDto.md doc/MemoryLaneResponseDto.md
doc/MergePersonDto.md doc/MergePersonDto.md
doc/ModelType.md
doc/OAuthApi.md doc/OAuthApi.md
doc/OAuthCallbackDto.md doc/OAuthCallbackDto.md
doc/OAuthConfigDto.md doc/OAuthConfigDto.md
@ -80,6 +84,7 @@ doc/PersonApi.md
doc/PersonResponseDto.md doc/PersonResponseDto.md
doc/PersonUpdateDto.md doc/PersonUpdateDto.md
doc/QueueStatusDto.md doc/QueueStatusDto.md
doc/RecognitionConfig.md
doc/SearchAlbumResponseDto.md doc/SearchAlbumResponseDto.md
doc/SearchApi.md doc/SearchApi.md
doc/SearchAssetDto.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_duplicate_asset_response_dto.dart
lib/model/check_existing_assets_dto.dart lib/model/check_existing_assets_dto.dart
lib/model/check_existing_assets_response_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_album_dto.dart
lib/model/create_profile_image_response_dto.dart lib/model/create_profile_image_response_dto.dart
lib/model/create_tag_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/map_marker_response_dto.dart
lib/model/memory_lane_response_dto.dart lib/model/memory_lane_response_dto.dart
lib/model/merge_person_dto.dart lib/model/merge_person_dto.dart
lib/model/model_type.dart
lib/model/o_auth_callback_dto.dart lib/model/o_auth_callback_dto.dart
lib/model/o_auth_config_dto.dart lib/model/o_auth_config_dto.dart
lib/model/o_auth_config_response_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_response_dto.dart
lib/model/person_update_dto.dart lib/model/person_update_dto.dart
lib/model/queue_status_dto.dart lib/model/queue_status_dto.dart
lib/model/recognition_config.dart
lib/model/search_album_response_dto.dart lib/model/search_album_response_dto.dart
lib/model/search_asset_dto.dart lib/model/search_asset_dto.dart
lib/model/search_asset_response_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_duplicate_asset_response_dto_test.dart
test/check_existing_assets_dto_test.dart test/check_existing_assets_dto_test.dart
test/check_existing_assets_response_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_album_dto_test.dart
test/create_profile_image_response_dto_test.dart test/create_profile_image_response_dto_test.dart
test/create_tag_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/map_marker_response_dto_test.dart
test/memory_lane_response_dto_test.dart test/memory_lane_response_dto_test.dart
test/merge_person_dto_test.dart test/merge_person_dto_test.dart
test/model_type_test.dart
test/o_auth_api_test.dart test/o_auth_api_test.dart
test/o_auth_callback_dto_test.dart test/o_auth_callback_dto_test.dart
test/o_auth_config_dto_test.dart test/o_auth_config_dto_test.dart
@ -349,6 +363,7 @@ test/person_api_test.dart
test/person_response_dto_test.dart test/person_response_dto_test.dart
test/person_update_dto_test.dart test/person_update_dto_test.dart
test/queue_status_dto_test.dart test/queue_status_dto_test.dart
test/recognition_config_test.dart
test/search_album_response_dto_test.dart test/search_album_response_dto_test.dart
test/search_api_test.dart test/search_api_test.dart
test/search_asset_dto_test.dart test/search_asset_dto_test.dart

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104
server/immich-openapi-specs.json
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@ -5354,6 +5354,34 @@
], ],
"type": "object" "type": "object"
}, },
"CLIPConfig": {
"properties": {
"enabled": {
"type": "boolean"
},
"mode": {
"$ref": "#/components/schemas/CLIPMode"
},
"modelName": {
"type": "string"
},
"modelType": {
"$ref": "#/components/schemas/ModelType"
}
},
"required": [
"enabled",
"modelName"
],
"type": "object"
},
"CLIPMode": {
"enum": [
"vision",
"text"
],
"type": "string"
},
"ChangePasswordDto": { "ChangePasswordDto": {
"properties": { "properties": {
"newPassword": { "newPassword": {
@ -5432,6 +5460,28 @@
], ],
"type": "object" "type": "object"
}, },
"ClassificationConfig": {
"properties": {
"enabled": {
"type": "boolean"
},
"minScore": {
"type": "integer"
},
"modelName": {
"type": "string"
},
"modelType": {
"$ref": "#/components/schemas/ModelType"
}
},
"required": [
"minScore",
"enabled",
"modelName"
],
"type": "object"
},
"CreateAlbumDto": { "CreateAlbumDto": {
"properties": { "properties": {
"albumName": { "albumName": {
@ -6144,6 +6194,14 @@
], ],
"type": "object" "type": "object"
}, },
"ModelType": {
"enum": [
"image-classification",
"facial-recognition",
"clip"
],
"type": "string"
},
"OAuthCallbackDto": { "OAuthCallbackDto": {
"properties": { "properties": {
"url": { "url": {
@ -6323,6 +6381,32 @@
], ],
"type": "object" "type": "object"
}, },
"RecognitionConfig": {
"properties": {
"enabled": {
"type": "boolean"
},
"maxDistance": {
"type": "integer"
},
"minScore": {
"type": "integer"
},
"modelName": {
"type": "string"
},
"modelType": {
"$ref": "#/components/schemas/ModelType"
}
},
"required": [
"minScore",
"maxDistance",
"enabled",
"modelName"
],
"type": "object"
},
"SearchAlbumResponseDto": { "SearchAlbumResponseDto": {
"properties": { "properties": {
"count": { "count": {
@ -6968,17 +7052,17 @@
}, },
"SystemConfigMachineLearningDto": { "SystemConfigMachineLearningDto": {
"properties": { "properties": {
"clipEncodeEnabled": { "classification": {
"type": "boolean" "$ref": "#/components/schemas/ClassificationConfig"
},
"clip": {
"$ref": "#/components/schemas/CLIPConfig"
}, },
"enabled": { "enabled": {
"type": "boolean" "type": "boolean"
}, },
"facialRecognitionEnabled": { "facialRecognition": {
"type": "boolean" "$ref": "#/components/schemas/RecognitionConfig"
},
"tagImageEnabled": {
"type": "boolean"
}, },
"url": { "url": {
"type": "string" "type": "string"
@ -6987,9 +7071,9 @@
"required": [ "required": [
"enabled", "enabled",
"url", "url",
"clipEncodeEnabled", "classification",
"facialRecognitionEnabled", "clip",
"tagImageEnabled" "facialRecognition"
], ],
"type": "object" "type": "object"
}, },

14
server/src/domain/facial-recognition/facial-recognition.service.spec.ts
View file

@ -115,6 +115,7 @@ describe(FacialRecognitionService.name, () => {
personMock = newPersonRepositoryMock(); personMock = newPersonRepositoryMock();
searchMock = newSearchRepositoryMock(); searchMock = newSearchRepositoryMock();
storageMock = newStorageRepositoryMock(); storageMock = newStorageRepositoryMock();
configMock = newSystemConfigRepositoryMock();
mediaMock.crop.mockResolvedValue(croppedFace); mediaMock.crop.mockResolvedValue(croppedFace);
@ -179,9 +180,18 @@ describe(FacialRecognitionService.name, () => {
machineLearningMock.detectFaces.mockResolvedValue([]); machineLearningMock.detectFaces.mockResolvedValue([]);
assetMock.getByIds.mockResolvedValue([assetStub.image]); assetMock.getByIds.mockResolvedValue([assetStub.image]);
await sut.handleRecognizeFaces({ id: assetStub.image.id }); await sut.handleRecognizeFaces({ id: assetStub.image.id });
expect(machineLearningMock.detectFaces).toHaveBeenCalledWith('http://immich-machine-learning:3003', { expect(machineLearningMock.detectFaces).toHaveBeenCalledWith(
'http://immich-machine-learning:3003',
{
imagePath: assetStub.image.resizePath, imagePath: assetStub.image.resizePath,
}); },
{
enabled: true,
maxDistance: 0.6,
minScore: 0.7,
modelName: 'buffalo_l',
},
);
expect(faceMock.create).not.toHaveBeenCalled(); expect(faceMock.create).not.toHaveBeenCalled();
expect(jobMock.queue).not.toHaveBeenCalled(); expect(jobMock.queue).not.toHaveBeenCalled();
}); });

14
server/src/domain/facial-recognition/facial-recognition.services.ts
View file

@ -32,7 +32,7 @@ export class FacialRecognitionService {
async handleQueueRecognizeFaces({ force }: IBaseJob) { async handleQueueRecognizeFaces({ force }: IBaseJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
return true; return true;
} }
@ -59,7 +59,7 @@ export class FacialRecognitionService {
async handleRecognizeFaces({ id }: IEntityJob) { async handleRecognizeFaces({ id }: IEntityJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
return true; return true;
} }
@ -68,7 +68,11 @@ export class FacialRecognitionService {
return false; 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 ${asset.resizePath}`); this.logger.debug(`${faces.length} faces detected in ${asset.resizePath}`);
this.logger.verbose(faces.map((face) => ({ ...face, embedding: `float[${face.embedding.length}]` }))); 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 // 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 // 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]}`); this.logger.verbose(`Match face with distance ${faceSearchResult.distances[0]}`);
personId = faceSearchResult.items[0].personId; personId = faceSearchResult.items[0].personId;
} }
@ -115,7 +119,7 @@ export class FacialRecognitionService {
async handleGenerateFaceThumbnail(data: IFaceThumbnailJob) { async handleGenerateFaceThumbnail(data: IFaceThumbnailJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) { if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
return true; return true;
} }

1
server/src/domain/search/search.repository.ts
View file

@ -86,6 +86,7 @@ export interface ISearchRepository {
deleteAssets(ids: string[]): Promise<void>; deleteAssets(ids: string[]): Promise<void>;
deleteFaces(ids: string[]): Promise<void>; deleteFaces(ids: string[]): Promise<void>;
deleteAllFaces(): Promise<number>; deleteAllFaces(): Promise<number>;
updateCLIPField(num_dim: number): Promise<void>;
searchAlbums(query: string, filters: SearchFilter): Promise<SearchResult<AlbumEntity>>; searchAlbums(query: string, filters: SearchFilter): Promise<SearchResult<AlbumEntity>>;
searchAssets(query: string, filters: SearchFilter): Promise<SearchResult<AssetEntity>>; searchAssets(query: string, filters: SearchFilter): Promise<SearchResult<AssetEntity>>;

9
server/src/domain/search/search.service.ts
View file

@ -121,15 +121,18 @@ export class SearchService {
await this.configCore.requireFeature(FeatureFlag.SEARCH); await this.configCore.requireFeature(FeatureFlag.SEARCH);
const query = dto.q || dto.query || '*'; 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 strategy = dto.clip && hasClip ? SearchStrategy.CLIP : SearchStrategy.TEXT;
const filters = { userId: authUser.id, ...dto }; const filters = { userId: authUser.id, ...dto };
let assets: SearchResult<AssetEntity>; let assets: SearchResult<AssetEntity>;
switch (strategy) { switch (strategy) {
case SearchStrategy.CLIP: case SearchStrategy.CLIP:
const clip = await this.machineLearning.encodeText(machineLearning.url, query); const {
assets = await this.searchRepository.vectorSearch(clip, filters); 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; break;
case SearchStrategy.TEXT: case SearchStrategy.TEXT:
default: default:

1
server/src/domain/smart-info/dto/index.ts Normal file
View file

@ -0,0 +1 @@
export * from './model-config.dto';

50
server/src/domain/smart-info/dto/model-config.dto.ts Normal file
View file

@ -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;
}

1
server/src/domain/smart-info/index.ts
View file

@ -1,3 +1,4 @@
export * from './dto';
export * from './machine-learning.interface'; export * from './machine-learning.interface';
export * from './smart-info.repository'; export * from './smart-info.repository';
export * from './smart-info.service'; export * from './smart-info.service';

29
server/src/domain/smart-info/machine-learning.interface.ts
View file

@ -1,9 +1,15 @@
import { ClassificationConfig, CLIPConfig, RecognitionConfig } from './dto';
export const IMachineLearningRepository = 'IMachineLearningRepository'; export const IMachineLearningRepository = 'IMachineLearningRepository';
export interface MachineLearningInput { export interface VisionModelInput {
imagePath: string; imagePath: string;
} }
export interface TextModelInput {
text: string;
}
export interface BoundingBox { export interface BoundingBox {
x1: number; x1: number;
y1: number; y1: number;
@ -19,9 +25,20 @@ export interface DetectFaceResult {
embedding: number[]; embedding: number[];
} }
export interface IMachineLearningRepository { export enum ModelType {
classifyImage(url: string, input: MachineLearningInput): Promise<string[]>; IMAGE_CLASSIFICATION = 'image-classification',
encodeImage(url: string, input: MachineLearningInput): Promise<number[]>; FACIAL_RECOGNITION = 'facial-recognition',
encodeText(url: string, input: string): Promise<number[]>; CLIP = 'clip',
detectFaces(url: string, input: MachineLearningInput): Promise<DetectFaceResult[]>; }
export enum CLIPMode {
VISION = 'vision',
TEXT = 'text',
}
export interface IMachineLearningRepository {
classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise<string[]>;
encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise<number[]>;
encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise<number[]>;
detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise<DetectFaceResult[]>;
} }

17
server/src/domain/smart-info/smart-info.service.spec.ts
View file

@ -84,9 +84,13 @@ describe(SmartInfoService.name, () => {
await sut.handleClassifyImage({ id: asset.id }); await sut.handleClassifyImage({ id: asset.id });
expect(machineMock.classifyImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', { expect(machineMock.classifyImage).toHaveBeenCalledWith(
'http://immich-machine-learning:3003',
{
imagePath: 'path/to/resize.ext', imagePath: 'path/to/resize.ext',
}); },
{ enabled: true, minScore: 0.9, modelName: 'microsoft/resnet-50' },
);
expect(smartMock.upsert).toHaveBeenCalledWith({ expect(smartMock.upsert).toHaveBeenCalledWith({
assetId: 'asset-1', assetId: 'asset-1',
tags: ['tag1', 'tag2', 'tag3'], tags: ['tag1', 'tag2', 'tag3'],
@ -141,13 +145,16 @@ describe(SmartInfoService.name, () => {
}); });
it('should save the returned objects', async () => { it('should save the returned objects', async () => {
smartMock.upsert.mockResolvedValue();
machineMock.encodeImage.mockResolvedValue([0.01, 0.02, 0.03]); machineMock.encodeImage.mockResolvedValue([0.01, 0.02, 0.03]);
await sut.handleEncodeClip({ id: asset.id }); await sut.handleEncodeClip({ id: asset.id });
expect(machineMock.encodeImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', { expect(machineMock.encodeImage).toHaveBeenCalledWith(
imagePath: 'path/to/resize.ext', 'http://immich-machine-learning:3003',
}); { imagePath: 'path/to/resize.ext' },
{ enabled: true, modelName: 'ViT-B-32::openai' },
);
expect(smartMock.upsert).toHaveBeenCalledWith({ expect(smartMock.upsert).toHaveBeenCalledWith({
assetId: 'asset-1', assetId: 'asset-1',
clipEmbedding: [0.01, 0.02, 0.03], clipEmbedding: [0.01, 0.02, 0.03],

21
server/src/domain/smart-info/smart-info.service.ts
View file

@ -22,7 +22,7 @@ export class SmartInfoService {
async handleQueueObjectTagging({ force }: IBaseJob) { async handleQueueObjectTagging({ force }: IBaseJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.tagImageEnabled) { if (!machineLearning.enabled || !machineLearning.classification.enabled) {
return true; return true;
} }
@ -43,7 +43,7 @@ export class SmartInfoService {
async handleClassifyImage({ id }: IEntityJob) { async handleClassifyImage({ id }: IEntityJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.tagImageEnabled) { if (!machineLearning.enabled || !machineLearning.classification.enabled) {
return true; return true;
} }
@ -52,7 +52,11 @@ export class SmartInfoService {
return false; 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 }); await this.repository.upsert({ assetId: asset.id, tags });
return true; return true;
@ -60,7 +64,7 @@ export class SmartInfoService {
async handleQueueEncodeClip({ force }: IBaseJob) { async handleQueueEncodeClip({ force }: IBaseJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) { if (!machineLearning.enabled || !machineLearning.clip.enabled) {
return true; return true;
} }
@ -81,7 +85,7 @@ export class SmartInfoService {
async handleEncodeClip({ id }: IEntityJob) { async handleEncodeClip({ id }: IEntityJob) {
const { machineLearning } = await this.configCore.getConfig(); const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) { if (!machineLearning.enabled || !machineLearning.clip.enabled) {
return true; return true;
} }
@ -90,7 +94,12 @@ export class SmartInfoService {
return false; 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 }); await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding });
return true; return true;

22
server/src/domain/system-config/dto/system-config-machine-learning.dto.ts
View file

@ -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 { export class SystemConfigMachineLearningDto {
@IsBoolean() @IsBoolean()
@ -8,12 +10,18 @@ export class SystemConfigMachineLearningDto {
@ValidateIf((dto) => dto.enabled) @ValidateIf((dto) => dto.enabled)
url!: string; url!: string;
@IsBoolean() @Type(() => ClassificationConfig)
clipEncodeEnabled!: boolean; @ValidateNested()
@IsObject()
classification!: ClassificationConfig;
@IsBoolean() @Type(() => CLIPConfig)
facialRecognitionEnabled!: boolean; @ValidateNested()
@IsObject()
clip!: CLIPConfig;
@IsBoolean() @Type(() => RecognitionConfig)
tagImageEnabled!: boolean; @ValidateNested()
@IsObject()
facialRecognition!: RecognitionConfig;
} }

27
server/src/domain/system-config/system-config.core.ts
View file

@ -47,12 +47,25 @@ export const defaults = Object.freeze<SystemConfig>({
[QueueName.THUMBNAIL_GENERATION]: { concurrency: 5 }, [QueueName.THUMBNAIL_GENERATION]: { concurrency: 5 },
[QueueName.VIDEO_CONVERSION]: { concurrency: 1 }, [QueueName.VIDEO_CONVERSION]: { concurrency: 1 },
}, },
machineLearning: { machineLearning: {
enabled: process.env.IMMICH_MACHINE_LEARNING_ENABLED !== 'false', enabled: process.env.IMMICH_MACHINE_LEARNING_ENABLED !== 'false',
url: process.env.IMMICH_MACHINE_LEARNING_URL || 'http://immich-machine-learning:3003', url: process.env.IMMICH_MACHINE_LEARNING_URL || 'http://immich-machine-learning:3003',
facialRecognitionEnabled: true, classification: {
tagImageEnabled: true, enabled: true,
clipEncodeEnabled: 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: { oauth: {
enabled: false, enabled: false,
@ -143,9 +156,9 @@ export class SystemConfigCore {
const mlEnabled = config.machineLearning.enabled; const mlEnabled = config.machineLearning.enabled;
return { return {
[FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clipEncodeEnabled, [FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clip.enabled,
[FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognitionEnabled, [FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognition.enabled,
[FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.tagImageEnabled, [FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.classification.enabled,
[FeatureFlag.SIDECAR]: true, [FeatureFlag.SIDECAR]: true,
[FeatureFlag.SEARCH]: process.env.TYPESENSE_ENABLED !== 'false', [FeatureFlag.SEARCH]: process.env.TYPESENSE_ENABLED !== 'false',
@ -230,7 +243,7 @@ export class SystemConfigCore {
_.set(config, key, value); _.set(config, key, value);
} }
return _.defaultsDeep(config, defaults) as SystemConfig; return plainToClass(SystemConfigDto, _.defaultsDeep(config, defaults));
} }
private async loadFromFile(filepath: string, force = false) { private async loadFromFile(filepath: string, force = false) {

18
server/src/domain/system-config/system-config.service.spec.ts
View file

@ -49,9 +49,21 @@ const updatedConfig = Object.freeze<SystemConfig>({
machineLearning: { machineLearning: {
enabled: true, enabled: true,
url: 'http://immich-machine-learning:3003', url: 'http://immich-machine-learning:3003',
facialRecognitionEnabled: true, classification: {
tagImageEnabled: true, enabled: true,
clipEncodeEnabled: 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: { oauth: {
autoLaunch: true, autoLaunch: true,

35
server/src/infra/entities/system-config.entity.ts
View file

@ -1,4 +1,4 @@
import { QueueName } from '@app/domain/job/job.constants'; import { QueueName } from '@app/domain';
import { Column, Entity, PrimaryColumn } from 'typeorm'; import { Column, Entity, PrimaryColumn } from 'typeorm';
@Entity('system_config') @Entity('system_config')
@ -39,9 +39,18 @@ export enum SystemConfigKey {
MACHINE_LEARNING_ENABLED = 'machineLearning.enabled', MACHINE_LEARNING_ENABLED = 'machineLearning.enabled',
MACHINE_LEARNING_URL = 'machineLearning.url', MACHINE_LEARNING_URL = 'machineLearning.url',
MACHINE_LEARNING_FACIAL_RECOGNITION_ENABLED = 'machineLearning.facialRecognitionEnabled',
MACHINE_LEARNING_TAG_IMAGE_ENABLED = 'machineLearning.tagImageEnabled', MACHINE_LEARNING_CLASSIFICATION_ENABLED = 'machineLearning.classification.enabled',
MACHINE_LEARNING_CLIP_ENCODE_ENABLED = 'machineLearning.clipEncodeEnabled', 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_ENABLED = 'oauth.enabled',
OAUTH_ISSUER_URL = 'oauth.issuerUrl', OAUTH_ISSUER_URL = 'oauth.issuerUrl',
@ -114,9 +123,21 @@ export interface SystemConfig {
machineLearning: { machineLearning: {
enabled: boolean; enabled: boolean;
url: string; url: string;
clipEncodeEnabled: boolean; classification: {
facialRecognitionEnabled: boolean; enabled: boolean;
tagImageEnabled: boolean; modelName: string;
minScore: number;
};
clip: {
enabled: boolean;
modelName: string;
};
facialRecognition: {
enabled: boolean;
modelName: string;
minScore: number;
maxDistance: number;
};
}; };
oauth: { oauth: {
enabled: boolean; enabled: boolean;

25
server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts Normal file
View file

@ -0,0 +1,25 @@
import { MigrationInterface, QueryRunner } from "typeorm"
export class RenameMLEnableFlags1693236627291 implements MigrationInterface {
public async up(queryRunner: QueryRunner): Promise<void> {
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<void> {
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
`);
}
}

66
server/src/infra/repositories/machine-learning.repository.ts
View file

@ -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 { Injectable } from '@nestjs/common';
import axios from 'axios'; import { readFile } from 'fs/promises';
import { createReadStream } from 'fs';
const client = axios.create();
@Injectable() @Injectable()
export class MachineLearningRepository implements IMachineLearningRepository { export class MachineLearningRepository implements IMachineLearningRepository {
private post<T>(input: MachineLearningInput, endpoint: string): Promise<T> { private async post<T>(url: string, input: TextModelInput | VisionModelInput, config: ModelConfig): Promise<T> {
return client.post<T>(endpoint, createReadStream(input.imagePath)).then((res) => res.data); const formData = await this.getFormData(input, config);
const res = await fetch(`${url}/predict`, { method: 'POST', body: formData });
return res.json();
} }
classifyImage(url: string, input: MachineLearningInput): Promise<string[]> { classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise<string[]> {
return this.post<string[]>(input, `${url}/image-classifier/tag-image`); return this.post<string[]>(url, input, { ...config, modelType: ModelType.IMAGE_CLASSIFICATION });
} }
detectFaces(url: string, input: MachineLearningInput): Promise<DetectFaceResult[]> { detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise<DetectFaceResult[]> {
return this.post<DetectFaceResult[]>(input, `${url}/facial-recognition/detect-faces`); return this.post<DetectFaceResult[]>(url, input, { ...config, modelType: ModelType.FACIAL_RECOGNITION });
} }
encodeImage(url: string, input: MachineLearningInput): Promise<number[]> { encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise<number[]> {
return this.post<number[]>(input, `${url}/sentence-transformer/encode-image`); return this.post<number[]>(url, input, {
...config,
modelType: ModelType.CLIP,
mode: CLIPMode.VISION,
} as CLIPConfig);
} }
encodeText(url: string, input: string): Promise<number[]> { encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise<number[]> {
return client.post<number[]>(`${url}/sentence-transformer/encode-text`, { text: input }).then((res) => res.data); return this.post<number[]>(url, input, { ...config, modelType: ModelType.CLIP, mode: CLIPMode.TEXT } as CLIPConfig);
}
async getFormData(input: TextModelInput | VisionModelInput, config: ModelConfig): Promise<FormData> {
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;
} }
} }

49
server/src/infra/repositories/typesense.repository.ts
View file

@ -52,6 +52,8 @@ export class TypesenseRepository implements ISearchRepository {
private logger = new Logger(TypesenseRepository.name); private logger = new Logger(TypesenseRepository.name);
private _client: Client | null = null; private _client: Client | null = null;
private _updateCLIPLock = false;
private get client(): Client { private get client(): Client {
if (!this._client) { if (!this._client) {
throw new Error('Typesense client not available (no apiKey was provided)'); throw new Error('Typesense client not available (no apiKey was provided)');
@ -141,7 +143,7 @@ export class TypesenseRepository implements ISearchRepository {
await this.updateAlias(collection); await this.updateAlias(collection);
} }
} catch (error: any) { } catch (error: any) {
this.handleError(error); await this.handleError(error);
} }
} }
@ -221,6 +223,30 @@ export class TypesenseRepository implements ISearchRepository {
return records.num_deleted; return records.num_deleted;
} }
async deleteAllAssets(): Promise<number> {
const records = await this.client.collections(assetSchema.name).documents().delete({ filter_by: 'ownerId:!=null' });
return records.num_deleted;
}
async updateCLIPField(num_dim: number): Promise<void> {
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<void> { async delete(collection: SearchCollection, ids: string[]): Promise<void> {
await this.client await this.client
.collections(schemaMap[collection].name) .collections(schemaMap[collection].name)
@ -326,21 +352,34 @@ export class TypesenseRepository implements ISearchRepository {
} as SearchResult<T>; } as SearchResult<T>;
} }
private handleError(error: any) { private async handleError(error: any) {
this.logger.error('Unable to index documents'); this.logger.error('Unable to index documents');
const results = error.importResults || []; const results = error.importResults || [];
let dimsChanged = false;
for (const result of results) { for (const result of results) {
try { try {
result.document = JSON.parse(result.document); 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) { if (result.document?.smartInfo?.clipEmbedding) {
result.document.smartInfo.clipEmbedding = '<truncated>'; result.document.smartInfo.clipEmbedding = '<truncated>';
} }
} 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) { private async updateAlias(collection: SearchCollection) {
const schema = schemaMap[collection]; const schema = schemaMap[collection];
const alias = await this.client const alias = await this.client

1
server/test/repositories/search.repository.mock.ts
View file

@ -11,6 +11,7 @@ export const newSearchRepositoryMock = (): jest.Mocked<ISearchRepository> => {
deleteAssets: jest.fn(), deleteAssets: jest.fn(),
deleteFaces: jest.fn(), deleteFaces: jest.fn(),
deleteAllFaces: jest.fn(), deleteAllFaces: jest.fn(),
updateCLIPField: jest.fn(),
searchAssets: jest.fn(), searchAssets: jest.fn(),
searchAlbums: jest.fn(), searchAlbums: jest.fn(),
vectorSearch: jest.fn(), vectorSearch: jest.fn(),

154
web/src/api/open-api/api.ts generated
View file

@ -862,6 +862,53 @@ export interface BulkIdsDto {
*/ */
'ids': Array<string>; 'ids': Array<string>;
} }
/**
*
* @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 * @export
@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto {
*/ */
'existingIds': Array<string>; 'existingIds': Array<string>;
} }
/**
*
* @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 * @export
@ -1766,6 +1846,21 @@ export interface MergePersonDto {
*/ */
'ids': Array<string>; 'ids': Array<string>;
} }
/**
*
* @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 * @export
@ -1991,6 +2086,45 @@ export interface QueueStatusDto {
*/ */
'isPaused': boolean; '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 * @export
@ -2803,10 +2937,16 @@ export interface SystemConfigJobDto {
export interface SystemConfigMachineLearningDto { export interface SystemConfigMachineLearningDto {
/** /**
* *
* @type {boolean} * @type {ClassificationConfig}
* @memberof SystemConfigMachineLearningDto * @memberof SystemConfigMachineLearningDto
*/ */
'clipEncodeEnabled': boolean; 'classification': ClassificationConfig;
/**
*
* @type {CLIPConfig}
* @memberof SystemConfigMachineLearningDto
*/
'clip': CLIPConfig;
/** /**
* *
* @type {boolean} * @type {boolean}
@ -2815,16 +2955,10 @@ export interface SystemConfigMachineLearningDto {
'enabled': boolean; 'enabled': boolean;
/** /**
* *
* @type {boolean} * @type {RecognitionConfig}
* @memberof SystemConfigMachineLearningDto * @memberof SystemConfigMachineLearningDto
*/ */
'facialRecognitionEnabled': boolean; 'facialRecognition': RecognitionConfig;
/**
*
* @type {boolean}
* @memberof SystemConfigMachineLearningDto
*/
'tagImageEnabled': boolean;
/** /**
* *
* @type {string} * @type {string}

176
web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte
View file

@ -4,38 +4,45 @@
NotificationType, NotificationType,
} from '$lib/components/shared-components/notification/notification'; } from '$lib/components/shared-components/notification/notification';
import { handleError } from '$lib/utils/handle-error'; import { handleError } from '$lib/utils/handle-error';
import { api, SystemConfigDto } from '@api'; import { api, SystemConfigMachineLearningDto } from '@api';
import { isEqual } from 'lodash-es'; import { isEqual } from 'lodash-es';
import { fade } from 'svelte/transition'; import { fade } from 'svelte/transition';
import SettingButtonsRow from '../setting-buttons-row.svelte'; import SettingButtonsRow from '../setting-buttons-row.svelte';
import SettingInputField, { SettingInputFieldType } from '../setting-input-field.svelte'; import SettingInputField, { SettingInputFieldType } from '../setting-input-field.svelte';
import SettingSwitch from '../setting-switch.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; export let disabled = false;
let config: SystemConfigDto; let savedConfig: SystemConfigMachineLearningDto;
let defaultConfig: SystemConfigDto; let defaultConfig: SystemConfigMachineLearningDto;
async function refreshConfig() { async function refreshConfig() {
[config, defaultConfig] = await Promise.all([ [savedConfig, defaultConfig] = await Promise.all([
api.systemConfigApi.getConfig().then((res) => res.data), api.systemConfigApi.getConfig().then((res) => res.data.machineLearning),
api.systemConfigApi.getDefaults().then((res) => res.data), api.systemConfigApi.getDefaults().then((res) => res.data.machineLearning),
]); ]);
} }
async function reset() { async function reset() {
const { data: resetConfig } = await api.systemConfigApi.getConfig(); 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 }); notificationController.show({ message: 'Reset to the last saved settings', type: NotificationType.Info });
} }
async function saveSetting() { async function saveSetting() {
try { try {
const { data: current } = await api.systemConfigApi.getConfig(); const { data: current } = await api.systemConfigApi.getConfig();
await api.systemConfigApi.updateConfig({ const result = await api.systemConfigApi.updateConfig({
systemConfigDto: { ...current, machineLearning: config.machineLearning }, systemConfigDto: { ...current, machineLearning: machineLearningConfig },
}); });
await refreshConfig();
machineLearningConfig = { ...result.data.machineLearning };
savedConfig = { ...result.data.machineLearning };
notificationController.show({ message: 'Settings saved', type: NotificationType.Info }); notificationController.show({ message: 'Settings saved', type: NotificationType.Info });
} catch (error) { } catch (error) {
handleError(error, 'Unable to save settings'); handleError(error, 'Unable to save settings');
@ -43,10 +50,7 @@
} }
async function resetToDefault() { async function resetToDefault() {
await refreshConfig(); machineLearningConfig = { ...defaultConfig };
const { data: defaults } = await api.systemConfigApi.getDefaults();
config = defaults;
notificationController.show({ message: 'Reset settings to defaults', type: NotificationType.Info }); notificationController.show({ message: 'Reset settings to defaults', type: NotificationType.Info });
} }
</script> </script>
@ -54,12 +58,13 @@
<div class="mt-2"> <div class="mt-2">
{#await refreshConfig() then} {#await refreshConfig() then}
<div in:fade={{ duration: 500 }}> <div in:fade={{ duration: 500 }}>
<form autocomplete="off" on:submit|preventDefault class="mx-4 flex flex-col gap-4 py-4"> <form autocomplete="off" on:submit|preventDefault class="mx-4 mt-4">
<div class="flex flex-col gap-4">
<SettingSwitch <SettingSwitch
title="Enabled" title="ENABLED"
subtitle="Use machine learning features" subtitle="If disabled, all ML features will be disabled regardless of the below settings."
{disabled} {disabled}
bind:checked={config.machineLearning.enabled} bind:checked={machineLearningConfig.enabled}
/> />
<hr /> <hr />
@ -67,39 +72,138 @@
<SettingInputField <SettingInputField
inputType={SettingInputFieldType.TEXT} inputType={SettingInputFieldType.TEXT}
label="URL" label="URL"
desc="URL of machine learning server" desc="URL of the machine learning server"
bind:value={config.machineLearning.url} bind:value={machineLearningConfig.url}
required={true} required={true}
disabled={disabled || !config.machineLearning.enabled} disabled={disabled || !machineLearningConfig.enabled}
isEdited={!(config.machineLearning.url === config.machineLearning.url)} isEdited={machineLearningConfig.url !== savedConfig.url}
/>
</div>
<SettingAccordion title="Image Tagging" subtitle="Tag and classify images with object labels">
<div class="ml-4 mt-4 flex flex-col gap-4">
<SettingSwitch
title="ENABLED"
subtitle="If disabled, images will not be tagged. This affects the Things section in the Explore page as well as 'm:' searches."
bind:checked={machineLearningConfig.classification.enabled}
disabled={disabled || !machineLearningConfig.enabled}
/> />
<hr />
<SettingInputField
inputType={SettingInputFieldType.TEXT}
label="IMAGE CLASSIFICATION MODEL"
bind:value={machineLearningConfig.classification.modelName}
required={true}
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.classification.enabled}
isEdited={machineLearningConfig.classification.modelName !== savedConfig.classification.modelName}
>
<p slot="desc" class="immich-form-label pb-2 text-sm">
The name of an image classification model listed <a
href="https://huggingface.co/models?pipeline_tag=image-classification&sort=trending"><u>here</u></a
>. It must be tagged with the 'Image Classification' task and must support ONNX conversion.
</p>
</SettingInputField>
<SettingInputField
inputType={SettingInputFieldType.NUMBER}
label="IMAGE CLASSIFICATION THRESHOLD"
desc="Minimum confidence score to add a particular object tag. Lower values will add more tags to images, but may result in more false positives. Will not have any effect until the Tag Objects job is re-run."
bind:value={machineLearningConfig.classification.minScore}
step="0.1"
min="0"
max="1"
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.classification.enabled}
isEdited={machineLearningConfig.classification.minScore !== savedConfig.classification.minScore}
/>
</div>
</SettingAccordion>
<SettingAccordion title="Smart Search" subtitle="Search for images semantically using CLIP embeddings">
<div class="ml-4 mt-4 flex flex-col gap-4">
<SettingSwitch <SettingSwitch
title="SMART SEARCH" title="ENABLED"
subtitle="Extract CLIP embeddings for smart search" subtitle="If disabled, images will not be encoded for smart search."
bind:checked={config.machineLearning.clipEncodeEnabled} bind:checked={machineLearningConfig.clip.enabled}
disabled={disabled || !config.machineLearning.enabled} disabled={disabled || !machineLearningConfig.enabled}
/> />
<hr />
<SettingInputField
inputType={SettingInputFieldType.TEXT}
label="CLIP MODEL"
bind:value={machineLearningConfig.clip.modelName}
required={true}
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.clip.enabled}
isEdited={machineLearningConfig.clip.modelName !== savedConfig.clip.modelName}
>
<p slot="desc" class="immich-form-label pb-2 text-sm">
The name of a CLIP model listed <a
href="https://clip-as-service.jina.ai/user-guides/benchmark/#size-and-efficiency"><u>here</u></a
>. Note that you must re-run the 'Encode CLIP' job for all images upon changing a model.
</p>
</SettingInputField>
</div>
</SettingAccordion>
<SettingAccordion title="Facial Recognition" subtitle="Detect, recognize and group faces in images">
<div class="ml-4 mt-4 flex flex-col gap-4">
<SettingSwitch <SettingSwitch
title="FACIAL RECOGNITION" title="ENABLED"
subtitle="Recognize and group faces in photos" subtitle="If disabled, images will not be encoded for facial recognition and will not populate the People section in the Explore page."
disabled={disabled || !config.machineLearning.enabled} bind:checked={machineLearningConfig.facialRecognition.enabled}
bind:checked={config.machineLearning.facialRecognitionEnabled} disabled={disabled || !machineLearningConfig.enabled}
/> />
<SettingSwitch <hr />
title="IMAGE TAGGING"
subtitle="Tag and classify images" <SettingSelect
disabled={disabled || !config.machineLearning.enabled} label="FACIAL RECOGNITION MODEL"
bind:checked={config.machineLearning.tagImageEnabled} desc="Smaller models are faster and use less memory, but perform worse. Note that you must re-run the Recognize Faces job for all images upon changing a model."
name="facial-recognition-model"
bind:value={machineLearningConfig.facialRecognition.modelName}
options={[
{ value: 'buffalo_l', text: 'buffalo_l' },
{ value: 'buffalo_s', text: 'buffalo_s' },
]}
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
isEdited={machineLearningConfig.facialRecognition.modelName !== savedConfig.facialRecognition.modelName}
/> />
<SettingInputField
inputType={SettingInputFieldType.NUMBER}
label="MIN DETECTION SCORE"
desc="Minimum confidence score for a face to be detected from 0-1. Lower values will detect more faces but may result in false positives."
bind:value={machineLearningConfig.facialRecognition.minScore}
step="0.1"
min="0"
max="1"
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
isEdited={machineLearningConfig.facialRecognition.minScore !== savedConfig.facialRecognition.minScore}
/>
<SettingInputField
inputType={SettingInputFieldType.NUMBER}
label="MAX RECOGNITION DISTANCE"
desc="Maximum distance between two faces to be considered the same person, ranging from 0-2. Lowering this can prevent labeling two people as the same person, while raising it can prevent labeling the same person as two different people. Note that it is easier to merge two people than to split one person in two, so err on the side of a lower threshold when possible."
bind:value={machineLearningConfig.facialRecognition.maxDistance}
step="0.1"
min="0"
max="2"
disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
isEdited={machineLearningConfig.facialRecognition.maxDistance !==
savedConfig.facialRecognition.maxDistance}
/>
</div>
</SettingAccordion>
<SettingButtonsRow <SettingButtonsRow
on:reset={reset} on:reset={reset}
on:save={saveSetting} on:save={saveSetting}
on:reset-to-default={resetToDefault} on:reset-to-default={resetToDefault}
showResetToDefault={!isEqual(config, defaultConfig)} showResetToDefault={!isEqual(savedConfig, defaultConfig)}
{disabled} {disabled}
/> />
</form> </form>

8
web/src/lib/components/admin-page/settings/setting-input-field.svelte
View file

@ -13,6 +13,9 @@
export let inputType: SettingInputFieldType; export let inputType: SettingInputFieldType;
export let value: string | number; 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 label = '';
export let desc = ''; export let desc = '';
export let required = false; export let required = false;
@ -48,6 +51,8 @@
<p class="immich-form-label pb-2 text-sm" id="{label}-desc"> <p class="immich-form-label pb-2 text-sm" id="{label}-desc">
{desc} {desc}
</p> </p>
{:else}
<slot name="desc" />
{/if} {/if}
<input <input
@ -57,6 +62,9 @@
id={label} id={label}
name={label} name={label}
type={inputType} type={inputType}
{min}
{max}
{step}
{required} {required}
{value} {value}
on:input={handleInput} on:input={handleInput}

8
web/src/routes/admin/system-settings/+page.svelte
View file

@ -68,6 +68,10 @@
<FFmpegSettings disabled={$featureFlags.configFile} ffmpegConfig={configs.ffmpeg} /> <FFmpegSettings disabled={$featureFlags.configFile} ffmpegConfig={configs.ffmpeg} />
</SettingAccordion> </SettingAccordion>
<SettingAccordion title="Machine Learning Settings" subtitle="Manage model settings">
<MachineLearningSettings disabled={$featureFlags.configFile} machineLearningConfig={configs.machineLearning} />
</SettingAccordion>
<SettingAccordion <SettingAccordion
title="Job Settings" title="Job Settings"
subtitle="Manage job concurrency" subtitle="Manage job concurrency"
@ -84,10 +88,6 @@
<OAuthSettings disabled={$featureFlags.configFile} oauthConfig={configs.oauth} /> <OAuthSettings disabled={$featureFlags.configFile} oauthConfig={configs.oauth} />
</SettingAccordion> </SettingAccordion>
<SettingAccordion title="Machine Learning" subtitle="Manage machine learning settings">
<MachineLearningSettings disabled={$featureFlags.configFile} />
</SettingAccordion>
<SettingAccordion <SettingAccordion
title="Storage Template" title="Storage Template"
subtitle="Manage the folder structure and file name of the upload asset" subtitle="Manage the folder structure and file name of the upload asset"