from typing import Optional

from pydantic import BaseModel
import numpy as np
import cv2


class KnownImagePoint(BaseModel):
    width: float
    height: float

    @classmethod
    def from_vec(cls, vec: tuple[float, float]) -> 'KnownImagePoint':
        return cls(width=vec[0], height=vec[1])


class BirdViewPoint(BaseModel):
    x: float
    y: float

    @classmethod
    def from_vec(cls, vec: tuple[float, float]) -> 'BirdViewPoint':
        return cls(x=vec[0], y=vec[1])


class KnownPoint(BaseModel):
    image: KnownImagePoint
    bird_view: BirdViewPoint


class VideoMetadata(BaseModel):
    knownPoints: list[KnownPoint]

    def get_view_perspective_matrix(self) -> Optional[np.array]:
        if len(self.knownPoints) < 4:
            return None

        empirical_source = np.float32(
            [[k.image.width, k.image.height] for k in self.knownPoints])
        empirical_target = np.float32(
            [[k.bird_view.x, k.bird_view.y] for k in self.knownPoints])
        pixel_per_meter = 100
        return cv2.getPerspectiveTransform(empirical_source,
                                           empirical_target * pixel_per_meter)