Source code for shapeflow.plugins.PerspectiveTransform
from typing import Optional, Tuple
import cv2
import numpy as np
from pydantic import Field, validator
from shapeflow import get_logger
from shapeflow.config import extend, ConfigType
from shapeflow.core.interface import TransformConfig, TransformInterface, TransformType
from shapeflow.maths.coordinates import ShapeCoo, Roi
log = get_logger(__name__)
[docs]@extend(TransformType, True)
class _Transform(TransformInterface):
"""Wraps ``OpenCV``’s `getPerspectiveTransform <https://docs.opencv.org/2.4.13.7/modules/imgproc/doc/geometric_transformations.html?#getperspectivetransform>`_
function to estimate the transformation matrix and `warpPerspective <https://docs.opencv.org/2.4.13.7/modules/imgproc/doc/geometric_transformations.html?#warpperspective>`_
to apply it to a video frame or a coordinate.
"""
_config_class = _Config
[docs] def validate(self, matrix: Optional[np.ndarray]) -> bool:
if matrix is not None:
return matrix.shape == (3, 3) and np.isfinite(np.linalg.cond(matrix))
else:
return False
[docs] def from_coordinates(self, roi: Roi, from_shape: tuple) -> np.ndarray:
return np.array(
[[relative * total
for relative, total in zip(
getattr(roi, corner).list, from_shape
)]
for corner in ['BL', 'TL', 'TR', 'BR']],
dtype=np.float32
)
[docs] def to_coordinates(self, to_shape: tuple) -> np.ndarray:
return np.array( # selection rectangle: bottom left to top right
[
[0, to_shape[1]], # BL: (x,y)
[0, 0], # TL
[to_shape[0], 0], # TR
[to_shape[0], to_shape[1]], # BR
],
dtype=np.float32
)
[docs] def estimate(self, roi: Roi, from_shape: tuple, to_shape: tuple) -> Optional[np.ndarray]:
log.debug(f'Estimating transform ~ coordinates {roi} & shape {to_shape}')
matrix = cv2.getPerspectiveTransform(
self.from_coordinates(roi, from_shape),
self.to_coordinates(to_shape)
)
if self.validate(matrix):
return matrix
else:
log.warning(f'Cannot estimate a valid matrix from {roi} and {to_shape}')
return None
[docs] def transform(self, matrix: np.ndarray, img: np.ndarray, shape: tuple) -> np.ndarray:
return cv2.warpPerspective(
img, matrix, shape, # can't set destination image here! it's the wrong shape!
borderValue=(255,255,255), # makes the border white instead of black ~https://stackoverflow.com/questions/30227979/
)
[docs] def coordinate(self, inverse: np.ndarray, coordinate: ShapeCoo, shape: Tuple[int, int]) -> ShapeCoo:
coordinate.transform(inverse, shape)
return coordinate