app.py

import os

import numpy as np
from fastapi import Depends, FastAPI, File, Response, UploadFile, status

from auth import validate_token
from model.model import Model
from routers.fecnet_router import router as fecnet_router
from schema import EmbeddingResponse, SimilarityResponse

app = FastAPI(
    title="Facial Expression Embedding Service",
)

app.include_router(fecnet_router)

model = Model(
    os.getenv("MODEL_REPO_ID", ""),
    os.getenv("MODEL_FILENAME", ""),
    os.getenv("HF_TOKEN", ""),
)


@app.post(
    "/embed",
    status_code=status.HTTP_200_OK,
    dependencies=[Depends(validate_token)],
    response_model=EmbeddingResponse,
)
async def calculate_embedding(
    image: UploadFile = File(...),
):
    try:
        image_content = await image.read()
        if isinstance(image_content, str):
            image_content = image_content.encode()
        pred = model.predict(model.preprocess(image_content))
        return EmbeddingResponse(embedding=pred[0].tolist())
    except Exception as e:
        return Response(
            content=str(e), status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
        )


@app.post(
    "/similarity",
    status_code=status.HTTP_200_OK,
    dependencies=[Depends(validate_token)],
    response_model=SimilarityResponse,
)
async def calculate_similarity_score(
    image1: UploadFile = File(...),
    image2: UploadFile = File(...),
):
    try:
        image1_content = await image1.read()
        if isinstance(image1_content, str):
            image1_content = image1_content.encode()
        image2_content = await image2.read()
        if isinstance(image2_content, str):
            image2_content = image2_content.encode()
        pred = model.predict(
            np.vstack(
                [model.preprocess(image1_content), model.preprocess(image2_content)]
            )
        )
        return SimilarityResponse(score=float(model.distance(pred[0], pred[1])))
    except Exception as e:
        return Response(
            content=str(e), status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
        )