mirror of
https://github.com/immich-app/immich.git
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c73832bd9c
* download facial recognition models * download hf models * simplified logic * updated `predict` for facial recognition * ensure download method is called * fixed repo_id for clip * fixed download destination * use st's own `snapshot_download` * conditional download * fixed predict method * check if loaded * minor fixes * updated mypy overrides * added pytest-mock * updated tests * updated lock
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
from pathlib import Path
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from typing import Any
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from huggingface_hub import snapshot_download
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from PIL.Image import Image
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from transformers.pipelines import pipeline
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from ..config import settings
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from ..schemas import ModelType
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from .base import InferenceModel
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class ImageClassifier(InferenceModel):
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_model_type = ModelType.IMAGE_CLASSIFICATION
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def __init__(
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self,
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model_name: str,
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min_score: float = settings.min_tag_score,
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cache_dir: Path | str | None = None,
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**model_kwargs: Any,
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) -> None:
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self.min_score = min_score
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super().__init__(model_name, cache_dir, **model_kwargs)
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def _download(self, **model_kwargs: Any) -> None:
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snapshot_download(
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cache_dir=self.cache_dir, repo_id=self.model_name, allow_patterns=["*.bin", "*.json", "*.txt"]
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)
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def _load(self, **model_kwargs: Any) -> None:
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self.model = pipeline(
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self.model_type.value,
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self.model_name,
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model_kwargs={"cache_dir": self.cache_dir, **model_kwargs},
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)
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def _predict(self, image: Image) -> list[str]:
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predictions: list[dict[str, Any]] = self.model(image) # type: ignore
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tags = [tag for pred in predictions for tag in pred["label"].split(", ") if pred["score"] >= self.min_score]
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return tags
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