| """Hugging Face Inference Endpoints entry point — deploy this repo as a CPU/GPU API. | |
| Request: {"inputs": <image>} where <image> is a base64 string (optionally a data: URI) or, when the | |
| endpoint receives raw image bytes (Content-Type: image/*), the PIL image the toolkit decodes. | |
| Optional {"parameters": {"top_k": 5}}. Response: the `Predictor.predict` dict ({"faces": [...], "n_faces": n}). | |
| """ | |
| import sys | |
| from pathlib import Path | |
| HERE = Path(__file__).resolve().parent | |
| sys.path.insert(0, str(HERE)) | |
| import model as M # noqa: E402 | |
| class EndpointHandler: | |
| def __init__(self, path: str = ""): | |
| self.predictor = M.load(path or HERE, "cuda" if M.cuda_available() else "cpu") | |
| def __call__(self, data: dict): | |
| inputs = data.pop("inputs", data) | |
| parameters = data.pop("parameters", None) or {} | |
| return self.predictor.predict(inputs, **parameters) | |