immich/machine-learning/app/conftest.py

import json
from pathlib import Path
from typing import Any, Iterator
from unittest import mock

import numpy as np
import pytest
from fastapi.testclient import TestClient
from PIL import Image

from .main import app, init_state
from .schemas import ndarray_f32


@pytest.fixture
def pil_image() -> Image.Image:
    return Image.new("RGB", (600, 800))


@pytest.fixture
def cv_image(pil_image: Image.Image) -> ndarray_f32:
    return np.asarray(pil_image)[:, :, ::-1]  # PIL uses RGB while cv2 uses BGR


@pytest.fixture
def mock_get_model() -> Iterator[mock.Mock]:
    with mock.patch("app.models.cache.from_model_type", autospec=True) as mocked:
        yield mocked


@pytest.fixture(scope="session")
def deployed_app() -> TestClient:
    init_state()
    return TestClient(app)


@pytest.fixture(scope="session")
def responses() -> dict[str, Any]:
    return json.load(open("responses.json", "r"))


@pytest.fixture(scope="session")
def clip_model_cfg() -> dict[str, Any]:
    return {
        "embed_dim": 512,
        "vision_cfg": {"image_size": 224, "layers": 12, "width": 768, "patch_size": 32},
        "text_cfg": {"context_length": 77, "vocab_size": 49408, "width": 512, "heads": 8, "layers": 12},
    }


@pytest.fixture(scope="session")
def clip_preprocess_cfg() -> dict[str, Any]:
    return {
        "size": [224, 224],
        "mode": "RGB",
        "mean": [0.48145466, 0.4578275, 0.40821073],
        "std": [0.26862954, 0.26130258, 0.27577711],
        "interpolation": "bicubic",
        "resize_mode": "shortest",
        "fill_color": 0,
    }