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feat(server): separate face clustering job (#5598)

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* separate facial clustering job

* update api

* fixed some tests

* invert clustering

* hdbscan

* update api

* remove commented code

* wip dbscan

* cleanup

removed cluster endpoint

remove commented code

* fixes

updated tests

minor fixes and formatting

fixed queuing

refinements

* scale search range based on library size

* defer non-core faces

* optimizations

removed unused query option

* assign faces individually for correctness

fixed unit tests

remove unused method

* don't select face embedding

update sql

linting

fixed ml typing

* updated job mock

* paginate people query

* select face embeddings because typeorm

* fix setting face detection concurrency

* update sql

formatting

linting

* simplify logic

remove unused imports

* more specific delete signature

* more accurate typing for face stubs

* add migration

formatting

* chore: better typing

* don't select embedding by default

remove unused import

* updated sql

* use normal try/catch

* stricter concurrency typing and enforcement

* update api

* update job concurrency panel to show disabled queues

formatting

* check jobId in queueAll

fix tests

* remove outdated comment

* better facial recognition icon

* wording

wording

formatting

* fixed tests

* fix

* formatting & sql

* try to fix sql check

* more detailed description

* update sql

* formatting

* wording

* update `minFaces` description

---------

Co-authored-by: Jason Rasmussen <jrasm91@gmail.com>
Co-authored-by: Alex Tran <alex.tran1502@gmail.com>
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Mert 2024-01-18 00:08:48 -05:00 • committed by GitHub
parent 44873b4224
commit 68f52818ae
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57 changed files with 1081 additions and 631 deletions
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10
machine-learning/app/main.py
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@ -6,7 +6,7 @@ import threading
import time
from concurrent.futures import ThreadPoolExecutor
from contextlib import asynccontextmanager
from typing import Any, AsyncGenerator, Iterator
from typing import Any, AsyncGenerator, Callable, Iterator
from zipfile import BadZipFile
import orjson
@ -105,14 +105,14 @@ async def predict(
model = await load(await model_cache.get(model_name, model_type, **kwargs))
model.configure(**kwargs)
outputs = await run(model, inputs)
outputs = await run(model.predict, inputs)
return ORJSONResponse(outputs)
async def run(model: InferenceModel, inputs: Any) -> Any:
async def run(func: Callable[..., Any], inputs: Any) -> Any:
if thread_pool is None:
return model.predict(inputs)
return await asyncio.get_running_loop().run_in_executor(thread_pool, model.predict, inputs)
return func(inputs)
return await asyncio.get_running_loop().run_in_executor(thread_pool, func, inputs)
async def load(model: InferenceModel) -> InferenceModel: