Source code for synapse.ml.opencv.ImageTransformer

# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.

import sys
from typing import List

if sys.version >= "3":
    basestring = str

import pyspark
from pyspark import SparkContext
from pyspark.ml.common import inherit_doc
from pyspark.sql.types import *
from pyspark.sql.types import Row, _create_row
import numpy as np
from synapse.ml.opencv._ImageTransformer import _ImageTransformer

ImageFields = ["origin", "height", "width", "nChannels", "mode", "data"]

ImageSchema = StructType(
    [
        StructField(ImageFields[0], StringType(), True),
        StructField(ImageFields[1], IntegerType(), True),
        StructField(ImageFields[2], IntegerType(), True),
        StructField(ImageFields[3], IntegerType(), True),
        StructField(ImageFields[4], IntegerType(), True),  # OpenCV type: CV_8U in most cases
        StructField(ImageFields[5], BinaryType(), True),
    ]
)  # OpenCV bytes: row-wise BGR in most cases


[docs]def toNDArray(image): """ Converts an image to a 1-dimensional array Args: image (object): The image to be converted Returns: array: The image as a 1-dimensional array """ return np.asarray(image.data, dtype=np.uint8).reshape((image.height, image.width, 3))[:, :, (2, 1, 0)]
[docs]def toImage(array, path="", mode=16): """ Converts a one-dimensional array to a 2 dimensional image Args: array (array): path (str): ocvType (int): Returns: object: 2 dimensional image """ length = np.prod(array.shape) data = bytearray(array.astype(dtype=np.int8)[:, :, (2, 1, 0)].reshape(length)) height = array.shape[0] width = array.shape[1] # Creating new Row with _create_row(), because Row(name = value, ... ) orders fields by name, # which conflicts with expected ImageSchema order when the new DataFrame is created by UDF return _create_row(ImageFields, [path, height, width, 3, mode, data])
from pyspark.ml.common import inherit_doc
[docs]@inherit_doc class ImageTransformer(_ImageTransformer): """ Transformer for common image processing stages. """
[docs] def resize(self, size, keep_aspect_ratio=True): """ Resizes the image to the given size. Args: size (int or tuple(width, height)): The size to resize to (>=0). keep_aspect_ratio (bool): Whether to keep aspect ratio. If true, the shorter side of the image will be resized to the specified size. """ if type(size) is tuple: height, width = (size[1], size[0]) self._java_obj.resize(height, width) return self else: self._java_obj.resize(size, keep_aspect_ratio) return self
[docs] def crop(self, x, y, height, width): """ Crops the image given the starting x,y coordinates and the width and height Args: x (int): The initial x coordinate (>=0) y (int): The initial y coordinate (>=0) height (int): The height to crop to (>=0) width (int): The width to crop to (>=0) """ self._java_obj.crop(x, y, height, width) return self
[docs] def centerCrop(self, height, width): """ Center crops the image given the width and height. Args: height (int): The height to crop to (>= 0) width (int): The width to crop to (>= 0) """ self._java_obj.centerCrop(height, width) return self
[docs] def colorFormat(self, format): """ Formats the image to the given image format Args: format (int): The format to convert to, please see OpenCV cvtColor function documentation for all formats """ self._java_obj.colorFormat(format) return self
[docs] def blur(self, height, width): """ Blurs the image using a normalized box filter Args: height (double): The height of the box filter (>= 0) width (double): The width of the box filter (>= 0) """ self._java_obj.blur(height, width) return self
[docs] def threshold(self, threshold, max_val, threshold_type): """ Thresholds the image, please see OpenCV threshold function documentation for more information Args: threshold: (double) The threshold value max_val (double): The maximum value to use threshold_type (double): The type of threshold, can be binary, binary_inv, trunc, zero, zero_inv """ self._java_obj.threshold(threshold, max_val, threshold_type) return self
[docs] def gaussianKernel(self, aperture_size, sigma): """ Blurs the image by applying a gaussian kernel Args: aperture_size (double): The aperture size, which should be odd and positive sigma (double): The standard deviation of the gaussian """ self._java_obj.gaussianKernel(aperture_size, sigma) return self
[docs] def flip(self, flip_code=1): """ Flips the image :param int flip_code: a flag to specify how to flip the image - 0 means flipping around the x-axis (up-down) - positive value (for example, 1) means flipping around y-axis (left-right, default) - negative value (for example, -1) means flipping around both axes (diagonally) See OpenCV documentation for details. """ self._java_obj.flip(flip_code) return self
[docs] def normalize(self, mean, std, color_scale_factor): """ Normalizes the image by multiplying the color_scale_factor, substracting mean and dividing by std """ self._java_obj.normalize(mean, std, color_scale_factor) return self