from io import BytesIO
import os.path
from typing import Optional
import configparser

import cv2
from PIL import Image

FACE_DATA = next(filter(os.path.exists, [
    '/usr/share/opencv/haarcascades/haarcascade_frontalface_default.xml',
    '/usr/share/opencv4/haarcascades/haarcascade_frontalface_default.xml',
]))

face_cascade = cv2.CascadeClassifier(FACE_DATA)


def get_rotate_value(input_value):
    if input_value == '0':
        return None

    if input_value == '90':
        return cv2.ROTATE_90_CLOCKWISE
    if input_value == '-90' or input_value == '270':
        return cv2.ROTATE_90_COUNTERCLOCKWISE
    if input_value == '180':
        return cv2.ROTATE_180
    raise ValueError(f"Unsupported rotation value {input_value!r}")


class Camera:
    capture: cv2.VideoCapture

    def __init__(self):
        self.capture = cv2.VideoCapture(0)
        parser = configparser.ConfigParser()
        parser.read('config.ini')
        self.config = parser['camera']

        self.rotate = get_rotate_value(self.config['rotate'])

    def get_image(self) -> Optional[bytes]:
        return_code, image = self.capture.read()
        if not return_code:
            return None
        if self.rotate is not None:
            image = cv2.rotate(image, self.rotate)
        image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        faces = face_cascade.detectMultiScale(image_gray, 1.3, 5)
        for (x, y, w, h) in faces:
            image = cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)

        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        jpg = Image.fromarray(image_rgb)
        byte_stream = BytesIO()
        jpg.save(byte_stream, 'JPEG')
        return bytes(byte_stream.getbuffer())