# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.
import sys
if sys.version >= '3':
basestring = str
from pyspark import SparkContext, SQLContext
from pyspark.sql import DataFrame
from pyspark.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from synapse.ml.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.evaluation import JavaEvaluator
from pyspark.ml.common import inherit_doc
from synapse.ml.core.schema.Utils import *
from pyspark.ml.param import TypeConverters
from synapse.ml.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter
[docs]@inherit_doc
class DetectFace(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer):
"""
Args:
concurrency (int): max number of concurrent calls
concurrentTimeout (float): max number seconds to wait on futures if concurrency >= 1
errorCol (object): column to hold http errors
handler (object): Which strategy to use when handling requests
imageUrl (object): the url of the image to use
outputCol (object): The name of the output column
returnFaceAttributes (object): Analyze and return the one or more specified face attributes Supported face attributes include: age, gender, headPose, smile, facialHair, glasses, emotion, hair, makeup, occlusion, accessories, blur, exposure and noise. Face attribute analysis has additional computational and time cost.
returnFaceId (object): Return faceIds of the detected faces or not. The default value is true
returnFaceLandmarks (object): Return face landmarks of the detected faces or not. The default value is false.
subscriptionKey (object): the API key to use
timeout (float): number of seconds to wait before closing the connection
url (object): Url of the service
"""
concurrency = Param(Params._dummy(), "concurrency", "max number of concurrent calls", typeConverter=TypeConverters.toInt)
concurrentTimeout = Param(Params._dummy(), "concurrentTimeout", "max number seconds to wait on futures if concurrency >= 1", typeConverter=TypeConverters.toFloat)
errorCol = Param(Params._dummy(), "errorCol", "column to hold http errors")
handler = Param(Params._dummy(), "handler", "Which strategy to use when handling requests")
imageUrl = Param(Params._dummy(), "imageUrl", "the url of the image to use")
outputCol = Param(Params._dummy(), "outputCol", "The name of the output column")
returnFaceAttributes = Param(Params._dummy(), "returnFaceAttributes", "Analyze and return the one or more specified face attributes Supported face attributes include: age, gender, headPose, smile, facialHair, glasses, emotion, hair, makeup, occlusion, accessories, blur, exposure and noise. Face attribute analysis has additional computational and time cost.")
returnFaceId = Param(Params._dummy(), "returnFaceId", "Return faceIds of the detected faces or not. The default value is true")
returnFaceLandmarks = Param(Params._dummy(), "returnFaceLandmarks", "Return face landmarks of the detected faces or not. The default value is false.")
subscriptionKey = Param(Params._dummy(), "subscriptionKey", "the API key to use")
timeout = Param(Params._dummy(), "timeout", "number of seconds to wait before closing the connection", typeConverter=TypeConverters.toFloat)
url = Param(Params._dummy(), "url", "Url of the service")
@keyword_only
def __init__(
self,
java_obj=None,
concurrency=1,
concurrentTimeout=None,
errorCol="DetectFace_76d9693a80e9_error",
handler=None,
imageUrl=None,
imageUrlCol=None,
outputCol="DetectFace_76d9693a80e9_output",
returnFaceAttributes=None,
returnFaceAttributesCol=None,
returnFaceId=None,
returnFaceIdCol=None,
returnFaceLandmarks=None,
returnFaceLandmarksCol=None,
subscriptionKey=None,
subscriptionKeyCol=None,
timeout=60.0,
url=None
):
super(DetectFace, self).__init__()
if java_obj is None:
self._java_obj = self._new_java_obj("com.microsoft.azure.synapse.ml.cognitive.DetectFace", self.uid)
else:
self._java_obj = java_obj
self._setDefault(concurrency=1)
self._setDefault(errorCol="DetectFace_76d9693a80e9_error")
self._setDefault(outputCol="DetectFace_76d9693a80e9_output")
self._setDefault(timeout=60.0)
if hasattr(self, "_input_kwargs"):
kwargs = self._input_kwargs
else:
kwargs = self.__init__._input_kwargs
if java_obj is None:
for k,v in kwargs.items():
if v is not None:
getattr(self, "set" + k[0].upper() + k[1:])(v)
[docs] @keyword_only
def setParams(
self,
concurrency=1,
concurrentTimeout=None,
errorCol="DetectFace_76d9693a80e9_error",
handler=None,
imageUrl=None,
imageUrlCol=None,
outputCol="DetectFace_76d9693a80e9_output",
returnFaceAttributes=None,
returnFaceAttributesCol=None,
returnFaceId=None,
returnFaceIdCol=None,
returnFaceLandmarks=None,
returnFaceLandmarksCol=None,
subscriptionKey=None,
subscriptionKeyCol=None,
timeout=60.0,
url=None
):
"""
Set the (keyword only) parameters
"""
if hasattr(self, "_input_kwargs"):
kwargs = self._input_kwargs
else:
kwargs = self.__init__._input_kwargs
return self._set(**kwargs)
[docs] @classmethod
def read(cls):
""" Returns an MLReader instance for this class. """
return JavaMMLReader(cls)
[docs] @staticmethod
def getJavaPackage():
""" Returns package name String. """
return "com.microsoft.azure.synapse.ml.cognitive.DetectFace"
@staticmethod
def _from_java(java_stage):
module_name=DetectFace.__module__
module_name=module_name.rsplit(".", 1)[0] + ".DetectFace"
return from_java(java_stage, module_name)
[docs] def setConcurrency(self, value):
"""
Args:
concurrency: max number of concurrent calls
"""
self._set(concurrency=value)
return self
[docs] def setConcurrentTimeout(self, value):
"""
Args:
concurrentTimeout: max number seconds to wait on futures if concurrency >= 1
"""
self._set(concurrentTimeout=value)
return self
[docs] def setErrorCol(self, value):
"""
Args:
errorCol: column to hold http errors
"""
self._set(errorCol=value)
return self
[docs] def setHandler(self, value):
"""
Args:
handler: Which strategy to use when handling requests
"""
self._set(handler=value)
return self
[docs] def setImageUrl(self, value):
"""
Args:
imageUrl: the url of the image to use
"""
if isinstance(value, list):
value = SparkContext._active_spark_context._jvm.org.apache.spark.ml.param.ServiceParam.toSeq(value)
self._java_obj = self._java_obj.setImageUrl(value)
return self
[docs] def setImageUrlCol(self, value):
"""
Args:
imageUrl: the url of the image to use
"""
self._java_obj = self._java_obj.setImageUrlCol(value)
return self
[docs] def setOutputCol(self, value):
"""
Args:
outputCol: The name of the output column
"""
self._set(outputCol=value)
return self
[docs] def setReturnFaceAttributes(self, value):
"""
Args:
returnFaceAttributes: Analyze and return the one or more specified face attributes Supported face attributes include: age, gender, headPose, smile, facialHair, glasses, emotion, hair, makeup, occlusion, accessories, blur, exposure and noise. Face attribute analysis has additional computational and time cost.
"""
if isinstance(value, list):
value = SparkContext._active_spark_context._jvm.org.apache.spark.ml.param.ServiceParam.toSeq(value)
self._java_obj = self._java_obj.setReturnFaceAttributes(value)
return self
[docs] def setReturnFaceAttributesCol(self, value):
"""
Args:
returnFaceAttributes: Analyze and return the one or more specified face attributes Supported face attributes include: age, gender, headPose, smile, facialHair, glasses, emotion, hair, makeup, occlusion, accessories, blur, exposure and noise. Face attribute analysis has additional computational and time cost.
"""
self._java_obj = self._java_obj.setReturnFaceAttributesCol(value)
return self
[docs] def setReturnFaceId(self, value):
"""
Args:
returnFaceId: Return faceIds of the detected faces or not. The default value is true
"""
if isinstance(value, list):
value = SparkContext._active_spark_context._jvm.org.apache.spark.ml.param.ServiceParam.toSeq(value)
self._java_obj = self._java_obj.setReturnFaceId(value)
return self
[docs] def setReturnFaceIdCol(self, value):
"""
Args:
returnFaceId: Return faceIds of the detected faces or not. The default value is true
"""
self._java_obj = self._java_obj.setReturnFaceIdCol(value)
return self
[docs] def setReturnFaceLandmarks(self, value):
"""
Args:
returnFaceLandmarks: Return face landmarks of the detected faces or not. The default value is false.
"""
if isinstance(value, list):
value = SparkContext._active_spark_context._jvm.org.apache.spark.ml.param.ServiceParam.toSeq(value)
self._java_obj = self._java_obj.setReturnFaceLandmarks(value)
return self
[docs] def setReturnFaceLandmarksCol(self, value):
"""
Args:
returnFaceLandmarks: Return face landmarks of the detected faces or not. The default value is false.
"""
self._java_obj = self._java_obj.setReturnFaceLandmarksCol(value)
return self
[docs] def setSubscriptionKey(self, value):
"""
Args:
subscriptionKey: the API key to use
"""
if isinstance(value, list):
value = SparkContext._active_spark_context._jvm.org.apache.spark.ml.param.ServiceParam.toSeq(value)
self._java_obj = self._java_obj.setSubscriptionKey(value)
return self
[docs] def setSubscriptionKeyCol(self, value):
"""
Args:
subscriptionKey: the API key to use
"""
self._java_obj = self._java_obj.setSubscriptionKeyCol(value)
return self
[docs] def setTimeout(self, value):
"""
Args:
timeout: number of seconds to wait before closing the connection
"""
self._set(timeout=value)
return self
[docs] def setUrl(self, value):
"""
Args:
url: Url of the service
"""
self._set(url=value)
return self
[docs] def getConcurrency(self):
"""
Returns:
concurrency: max number of concurrent calls
"""
return self.getOrDefault(self.concurrency)
[docs] def getConcurrentTimeout(self):
"""
Returns:
concurrentTimeout: max number seconds to wait on futures if concurrency >= 1
"""
return self.getOrDefault(self.concurrentTimeout)
[docs] def getErrorCol(self):
"""
Returns:
errorCol: column to hold http errors
"""
return self.getOrDefault(self.errorCol)
[docs] def getHandler(self):
"""
Returns:
handler: Which strategy to use when handling requests
"""
return self.getOrDefault(self.handler)
[docs] def getImageUrl(self):
"""
Returns:
imageUrl: the url of the image to use
"""
return self.getOrDefault(self.imageUrl)
[docs] def getOutputCol(self):
"""
Returns:
outputCol: The name of the output column
"""
return self.getOrDefault(self.outputCol)
[docs] def getReturnFaceAttributes(self):
"""
Returns:
returnFaceAttributes: Analyze and return the one or more specified face attributes Supported face attributes include: age, gender, headPose, smile, facialHair, glasses, emotion, hair, makeup, occlusion, accessories, blur, exposure and noise. Face attribute analysis has additional computational and time cost.
"""
return self.getOrDefault(self.returnFaceAttributes)
[docs] def getReturnFaceId(self):
"""
Returns:
returnFaceId: Return faceIds of the detected faces or not. The default value is true
"""
return self.getOrDefault(self.returnFaceId)
[docs] def getReturnFaceLandmarks(self):
"""
Returns:
returnFaceLandmarks: Return face landmarks of the detected faces or not. The default value is false.
"""
return self.getOrDefault(self.returnFaceLandmarks)
[docs] def getSubscriptionKey(self):
"""
Returns:
subscriptionKey: the API key to use
"""
return self.getOrDefault(self.subscriptionKey)
[docs] def getTimeout(self):
"""
Returns:
timeout: number of seconds to wait before closing the connection
"""
return self.getOrDefault(self.timeout)
[docs] def getUrl(self):
"""
Returns:
url: Url of the service
"""
return self.getOrDefault(self.url)
[docs] def setLocation(self, value):
self._java_obj = self._java_obj.setLocation(value)
return self
[docs] def setLinkedService(self, value):
self._java_obj = self._java_obj.setLinkedService(value)
return self