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Images

Image Objects

np_arr_img_to_bytes​

def np_arr_img_to_bytes(arr, format: str = 'JPEG') -> bytes

Convert a NumPy array to bytes

Arguments:

  • arr - The NumPy array to convert
  • format - The format of the image. Defaults to "JPEG".

Returns:

  • bytes - The image as bytes

image_to_bytes​

def image_to_bytes(image: Image, format: str = "JPEG") -> bytes

Convert an image to bytes

Arguments:

  • image PIL.Image - The image to convert
  • format str, optional - The format of the image. Defaults to "JPEG".

Returns:

  • bytes - The image as bytes

rotate​

def rotate(points, angle, c_x=0, c_y=0)

Rotate a set of points around a center

Arguments:

  • points - The points to rotate; iterable of (x, y) pairs
  • angle - The angle of counterclockwise rotation in degrees
  • c_x - The x coordinate of the center of rotation
  • c_y - The y coordinate of the center of rotation

Returns:

  • points - The rotated points as a NumPy array of shape (n,2) and type int

resolve​

def resolve(points: np.array, image_meta, operations) -> np.array

Resolve the coordinates of a bounding box to the original image size

Given an array of (x,y) points with respect to the coordinates of an image, returns the corresponding coordinates with respect to a the resized or rotated image that resulted from a series of operations.

Arguments:

  • points NumPy array - The coordinates of the bounding box; shape (...,2)
  • image dict - The image properties
  • operations list - The operations applied to the image

Returns:

  • resolved_points NumPy array - The resolved coordinates, same shape as points

Images Objects​

class Images(Entities)

The python wrapper of images in ApertureDB.

This class serves 2 purposes:

This class is a layer on top of the native query.

It facilitate interactions with images in the database in a pythonic way. Abstracts the complexity of the query language and the communication with the database.

It includes utility methods to visualize image and annotations

Inter convert the representation into NumPy matrices and find similar images, related bounding boxes, etc.

Arguments:

  • client - The database connector, perhaps as returned by CommonLibrary.create_connector

total_results​

def total_results() -> int

Returns the total number of images that matched the query

Returns:

  • int - Count of images that match the query.

get_image_by_index​

def get_image_by_index(index: int)

Get a single image by its index in the array of retrieved ids

Arguments:

  • index int - Position in the image ids retrieved.

get_np_image_by_index​

def get_np_image_by_index(index: int)

Retrieves the NumPy representation of image from database

Arguments:

  • index int - Position in the image ids retrieved.

get_bboxes_by_index​

def get_bboxes_by_index(index: int)

Get related bounding box for the image

Arguments:

  • index int - Position in the image ids retrieved.

Returns:

  • _type_ - description
def search(constraints=None,
           operations=None,
           format=None,
           limit=None,
           sort=None)

Sets a new query to retrieve images parameters as described below

Arguments:

  • constraints dict, optional - Constraints. Defaults to None.
  • operations dict, optional - Operations. Defaults to None.
  • format str, optional - Format of the returned images. Without this, the images are returned as they are stored. Defaults to None.
  • limit int, optional - number of values to restrict results to. Defaults to None.
  • sort dict, optional - Sort. Defaults to None.

search_by_property​

def search_by_property(prop_key: str, prop_values: list)

Constructs a constraints block and does a new search

Arguments:

  • prop_key str - Key on which to search
  • prop_values list - The values that must match for the key.

display​

def display(show_bboxes: bool = False,
            bbox_constraints: Constraints = None,
            show_polygons: bool = False,
            limit: Union[int, object] = None,
            polygon_constraints: Constraints = None,
            polygon_tag_key: str = "_label",
            polygon_tag_format: str = "{}") -> None

Display images with annotations

Arguments:

  • show_bboxes - bool, optional Show bounding boxes, by default False
  • bbox_constraints - Constraints, optional Constraints for bounding boxes, by default None
  • show_polygons - bool, optional Show polygons, by default False
  • limit - Union[int, object], optional Number of images to display, by default None
  • polygon_constraints - Constraints, optional Constraints for polygons, by default None
  • polygon_tag_key - str, optional Key for the polygon tag, by default "_label"
  • polygon_tag_format - str, optional Format for the polygon tag, by default "{}"

get_props_names​

def get_props_names() -> List[str]

Get the names of the properties that apply to images

Returns:

  • properties List[str] - The names of the properties of the images

get_properties​

def get_properties(prop_list: Iterable[str] = []) -> Dict[str, Any]

Get the properties of the images

Arguments:

  • prop_list List[str], optional - The list of properties to retrieve. Defaults to [].

Returns:

property_values Dict[str, Any]: The properties of the images

Frames Objects​

class Frames(Images)

The python wrapper of frame images in ApertureDB.

Frames in ApertureDB are quite similar to images and so are modeled in python as a subclass.

Arguments:

  • client - The database connector, perhaps as returned by CommonLibrary.create_connector