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