import os
import numpy as np
import cv2 as cv
import gdown

from deepface.commons import functions

# pylint: disable=line-too-long, too-few-public-methods


class _Layer:
    input_shape = (None, 112, 112, 3)
    output_shape = (None, 1, 128)


class SFaceModel:
    def __init__(self, model_path):

        self.model = cv.FaceRecognizerSF.create(
            model=model_path, config="", backend_id=0, target_id=0
        )

        self.layers = [_Layer()]

    def predict(self, image):
        # Preprocess
        input_blob = (image[0] * 255).astype(
            np.uint8
        )  # revert the image to original format and preprocess using the model

        # Forward
        embeddings = self.model.feature(input_blob)

        return embeddings


def load_model(
    url="https://github.com/opencv/opencv_zoo/raw/master/models/face_recognition_sface/face_recognition_sface_2021dec.onnx",
):

    home = functions.get_deepface_home()

    file_name = home + "/.deepface/weights/face_recognition_sface_2021dec.onnx"

    if not os.path.isfile(file_name):

        print("sface weights will be downloaded...")

        gdown.download(url, file_name, quiet=False)

    model = SFaceModel(model_path=file_name)

    return model