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