Module brevettiai.data.image.image_processor
Expand source code
import numpy as np
from pydantic import BaseModel
class ImageProcessor(BaseModel):
"""
Baseclass for implementing interface for image proccessors
"""
type: str
def process(self, image):
"""Process image according to processor"""
raise NotImplementedError("process(image)-> image should be implemented")
# noinspection PyUnreachableCode
return image
@staticmethod
def affine_transform(input_height, input_width):
return np.eye(3)
Classes
class ImageProcessor (**data: Any)
-
Baseclass for implementing interface for image proccessors
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
Expand source code
class ImageProcessor(BaseModel): """ Baseclass for implementing interface for image proccessors """ type: str def process(self, image): """Process image according to processor""" raise NotImplementedError("process(image)-> image should be implemented") # noinspection PyUnreachableCode return image @staticmethod def affine_transform(input_height, input_width): return np.eye(3)
Ancestors
- pydantic.main.BaseModel
- pydantic.utils.Representation
Subclasses
Class variables
var type : str
Static methods
def affine_transform(input_height, input_width)
-
Expand source code
@staticmethod def affine_transform(input_height, input_width): return np.eye(3)
Methods
def process(self, image)
-
Process image according to processor
Expand source code
def process(self, image): """Process image according to processor""" raise NotImplementedError("process(image)-> image should be implemented") # noinspection PyUnreachableCode return image