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Coordinated Image

Bases: NamedTuple

Each filtered item can be wrapped around this data structure where each will have its own dimensions, that can be used in relation to the original image (im):

raw dimension definition
x x-axis position marking the start of the filtered item
y y-axis position marking the start of the filtered item
w x-axis based _w_idth of the filtered item
h y-axis based _h_eight of the filtered item

This "coordinates" setup enables the calculation of the end positions (of the filtered items) as properties, e.g.:

calculated dimension calculation definition
x1 x + w x-axis position marking the end of the filtered item
y1 y + h y-axis position marking the end of the filtered item
Source code in src/start_ocr/coordinates.py
Python
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class CoordinatedImage(NamedTuple):
    """Each filtered item can be wrapped around this data structure where each will have its own
    dimensions, that can be used in relation to the original image (`im`):

    raw dimension | definition
    --:|:--
    `x` | _x_-axis position marking the start of the filtered item
    `y` | _y_-axis position marking the start of the filtered item
    `w` | x-axis based _w_idth of the filtered item
    `h` | y-axis based _h_eight of the filtered item

    This "coordinates" setup enables the calculation of the end positions (of the
    filtered items) as properties, e.g.:

    calculated dimension | calculation | definition
    --:|:--:|:--
    `x1` | `x + w` | x-axis position marking the end of the filtered item
    `y1` | `y + h` | y-axis position marking the end of the filtered item
    """  # noqa: E501

    im: ndarray
    x: float
    y: float
    w: float
    h: float

    @property
    def x1(self):
        """X-axis position marking end of filtered item."""
        return self.x + self.w

    @property
    def y1(self):
        """Y-axis position marking end of filtered item."""
        return self.y + self.h

    @property
    def upper_left_point(self) -> tuple[float, float]:
        """The upper left point of a rectangle."""
        return (self.x, self.y)

    @property
    def lower_right_point(self) -> tuple[float, float]:
        """The lower right point of a rectangle."""
        return (self.x1, self.y1)

    @property
    def fragment(self) -> ndarray:
        """The slice of an image with the filtered coordinates in the format:
        image [pt1, pt2] where:

        1. pt1 = from point y to point y1
        1. pt2 = from point x to point x1
        """
        return self.im[self.y : self.y1, self.x : self.x1]

    def greenbox(self):
        """Add a "green box" to the image where the box area is represented by the
        diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being
        the lower right point of the rectangle."""
        return cv2.rectangle(
            img=self.im,
            pt1=self.upper_left_point,
            pt2=self.lower_right_point,
            color=GREEN,
            thickness=2,
        )

    def redbox(self):
        """Add a "green box" to the image where the box area is represented by the
        diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being
        the lower right point of the rectangle."""
        return cv2.rectangle(
            img=self.im,
            pt1=self.upper_left_point,
            pt2=self.lower_right_point,
            color=PURPLE,
            thickness=1,
        )

Attributes

fragment: ndarray property

The slice of an image with the filtered coordinates in the format: image [pt1, pt2] where:

  1. pt1 = from point y to point y1
  2. pt2 = from point x to point x1

lower_right_point: tuple[float, float] property

The lower right point of a rectangle.

upper_left_point: tuple[float, float] property

The upper left point of a rectangle.

x1 property

X-axis position marking end of filtered item.

y1 property

Y-axis position marking end of filtered item.

Functions

greenbox()

Add a "green box" to the image where the box area is represented by the diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being the lower right point of the rectangle.

Source code in src/start_ocr/coordinates.py
Python
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def greenbox(self):
    """Add a "green box" to the image where the box area is represented by the
    diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being
    the lower right point of the rectangle."""
    return cv2.rectangle(
        img=self.im,
        pt1=self.upper_left_point,
        pt2=self.lower_right_point,
        color=GREEN,
        thickness=2,
    )

redbox()

Add a "green box" to the image where the box area is represented by the diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being the lower right point of the rectangle.

Source code in src/start_ocr/coordinates.py
Python
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def redbox(self):
    """Add a "green box" to the image where the box area is represented by the
    diagonal of pt1 and pt2: pt1 being the upper left point and pt2 being
    the lower right point of the rectangle."""
    return cv2.rectangle(
        img=self.im,
        pt1=self.upper_left_point,
        pt2=self.lower_right_point,
        color=PURPLE,
        thickness=1,
    )