mirror of
https://github.com/immich-app/immich.git
synced 2025-01-03 13:09:27 +02:00
df1e8679d9
* added testing * github action for python, made mypy happy * formatted with black * minor fixes and styling * test model cache * cache test dependencies * narrowed model cache tests * moved endpoint tests to their own class * cleaned up fixtures * formatting * removed unused dep
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
from pathlib import Path
|
|
from typing import Any
|
|
|
|
import cv2
|
|
from insightface.app import FaceAnalysis
|
|
|
|
from ..config import settings
|
|
from ..schemas import ModelType
|
|
from .base import InferenceModel
|
|
|
|
|
|
class FaceRecognizer(InferenceModel):
|
|
_model_type = ModelType.FACIAL_RECOGNITION
|
|
|
|
def __init__(
|
|
self,
|
|
model_name: str,
|
|
min_score: float = settings.min_face_score,
|
|
cache_dir: Path | str | None = None,
|
|
**model_kwargs: Any,
|
|
) -> None:
|
|
self.min_score = min_score
|
|
super().__init__(model_name, cache_dir, **model_kwargs)
|
|
|
|
def load(self, **model_kwargs: Any) -> None:
|
|
self.model = FaceAnalysis(
|
|
name=self.model_name,
|
|
root=self.cache_dir.as_posix(),
|
|
allowed_modules=["detection", "recognition"],
|
|
**model_kwargs,
|
|
)
|
|
self.model.prepare(
|
|
ctx_id=0,
|
|
det_thresh=self.min_score,
|
|
det_size=(640, 640),
|
|
)
|
|
|
|
def predict(self, image: cv2.Mat) -> list[dict[str, Any]]:
|
|
height, width, _ = image.shape
|
|
results = []
|
|
faces = self.model.get(image)
|
|
|
|
for face in faces:
|
|
x1, y1, x2, y2 = face.bbox
|
|
|
|
results.append(
|
|
{
|
|
"imageWidth": width,
|
|
"imageHeight": height,
|
|
"boundingBox": {
|
|
"x1": round(x1),
|
|
"y1": round(y1),
|
|
"x2": round(x2),
|
|
"y2": round(y2),
|
|
},
|
|
"score": face.det_score.item(),
|
|
"embedding": face.normed_embedding.tolist(),
|
|
}
|
|
)
|
|
return results
|