Source code for mmlspark.cognitive.DetectFace

# 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.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from mmlspark.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.common import inherit_doc
from mmlspark.core.schema.Utils import *
from mmlspark.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter

[docs]@inherit_doc class DetectFace(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: concurrency (int): max number of concurrent calls (default: 1) concurrentTimeout (double): max number seconds to wait on futures if concurrency >= 1 (default: 100.0) errorCol (str): column to hold http errors (default: [self.uid]_error) handler (object): Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None)) imageUrl (object): the url of the image to use outputCol (str): The name of the output column (default: [self.uid]_output) 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 (double): number of seconds to wait before closing the connection (default: 60.0) url (str): Url of the service """ @keyword_only def __init__(self, concurrency=1, concurrentTimeout=100.0, errorCol=None, handler=None, imageUrl=None, outputCol=None, returnFaceAttributes=None, returnFaceId=None, returnFaceLandmarks=None, subscriptionKey=None, timeout=60.0, url=None): super(DetectFace, self).__init__() self._java_obj = self._new_java_obj("com.microsoft.ml.spark.cognitive.DetectFace") self._cache = {} self.concurrency = Param(self, "concurrency", "concurrency: max number of concurrent calls (default: 1)") self._setDefault(concurrency=1) self.concurrentTimeout = Param(self, "concurrentTimeout", "concurrentTimeout: max number seconds to wait on futures if concurrency >= 1 (default: 100.0)") self._setDefault(concurrentTimeout=100.0) self.errorCol = Param(self, "errorCol", "errorCol: column to hold http errors (default: [self.uid]_error)") self._setDefault(errorCol=self.uid + "_error") self.handler = Param(self, "handler", "handler: Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None))", generateTypeConverter("handler", self._cache, complexTypeConverter)) self.imageUrl = Param(self, "imageUrl", "imageUrl: the url of the image to use") self.outputCol = Param(self, "outputCol", "outputCol: The name of the output column (default: [self.uid]_output)") self._setDefault(outputCol=self.uid + "_output") self.returnFaceAttributes = Param(self, "returnFaceAttributes", "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.returnFaceId = Param(self, "returnFaceId", "returnFaceId: Return faceIds of the detected faces or not. The default value is true") self.returnFaceLandmarks = Param(self, "returnFaceLandmarks", "returnFaceLandmarks: Return face landmarks of the detected faces or not. The default value is false.") self.subscriptionKey = Param(self, "subscriptionKey", "subscriptionKey: the API key to use") self.timeout = Param(self, "timeout", "timeout: number of seconds to wait before closing the connection (default: 60.0)") self._setDefault(timeout=60.0) self.url = Param(self, "url", "url: Url of the service") if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs self.setParams(**kwargs)
[docs] @keyword_only def setParams(self, concurrency=1, concurrentTimeout=100.0, errorCol=None, handler=None, imageUrl=None, outputCol=None, returnFaceAttributes=None, returnFaceId=None, returnFaceLandmarks=None, subscriptionKey=None, timeout=60.0, url=None): """ Set the (keyword only) parameters Args: concurrency (int): max number of concurrent calls (default: 1) concurrentTimeout (double): max number seconds to wait on futures if concurrency >= 1 (default: 100.0) errorCol (str): column to hold http errors (default: [self.uid]_error) handler (object): Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None)) imageUrl (object): the url of the image to use outputCol (str): The name of the output column (default: [self.uid]_output) 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 (double): number of seconds to wait before closing the connection (default: 60.0) url (str): Url of the service """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[docs] def setConcurrency(self, value): """ Args: concurrency (int): max number of concurrent calls (default: 1) """ self._set(concurrency=value) return self
[docs] def getConcurrency(self): """ Returns: int: max number of concurrent calls (default: 1) """ return self.getOrDefault(self.concurrency)
[docs] def setConcurrentTimeout(self, value): """ Args: concurrentTimeout (double): max number seconds to wait on futures if concurrency >= 1 (default: 100.0) """ self._set(concurrentTimeout=value) return self
[docs] def getConcurrentTimeout(self): """ Returns: double: max number seconds to wait on futures if concurrency >= 1 (default: 100.0) """ return self.getOrDefault(self.concurrentTimeout)
[docs] def setErrorCol(self, value): """ Args: errorCol (str): column to hold http errors (default: [self.uid]_error) """ self._set(errorCol=value) return self
[docs] def getErrorCol(self): """ Returns: str: column to hold http errors (default: [self.uid]_error) """ return self.getOrDefault(self.errorCol)
[docs] def setHandler(self, value): """ Args: handler (object): Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None)) """ self._set(handler=value) return self
[docs] def getHandler(self): """ Returns: object: Which strategy to use when handling requests (default: UserDefinedFunction(<function2>,StringType,None)) """ return self._cache.get("handler", None)
[docs] def setImageUrl(self, value): """ Args: imageUrl (object): the url of the image to use """ self._java_obj = self._java_obj.setImageUrl(value) return self
[docs] def setImageUrlCol(self, value): """ Args: imageUrl (object): the url of the image to use """ self._java_obj = self._java_obj.setImageUrlCol(value) return self
[docs] def getImageUrl(self): """ Returns: object: the url of the image to use """ return self._cache.get("imageUrl", None)
[docs] def setOutputCol(self, value): """ Args: outputCol (str): The name of the output column (default: [self.uid]_output) """ self._set(outputCol=value) return self
[docs] def getOutputCol(self): """ Returns: str: The name of the output column (default: [self.uid]_output) """ return self.getOrDefault(self.outputCol)
[docs] def setReturnFaceAttributes(self, value): """ Args: 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. """ self._java_obj = self._java_obj.setReturnFaceAttributes(value) return self
[docs] def setReturnFaceAttributesCol(self, value): """ Args: 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. """ self._java_obj = self._java_obj.setReturnFaceAttributesCol(value) return self
[docs] def getReturnFaceAttributes(self): """ Returns: 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. """ return self._cache.get("returnFaceAttributes", None)
[docs] def setReturnFaceId(self, value): """ Args: returnFaceId (object): Return faceIds of the detected faces or not. The default value is true """ self._java_obj = self._java_obj.setReturnFaceId(value) return self
[docs] def setReturnFaceIdCol(self, value): """ Args: returnFaceId (object): 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 getReturnFaceId(self): """ Returns: object: Return faceIds of the detected faces or not. The default value is true """ return self._cache.get("returnFaceId", None)
[docs] def setReturnFaceLandmarks(self, value): """ Args: returnFaceLandmarks (object): Return face landmarks of the detected faces or not. The default value is false. """ self._java_obj = self._java_obj.setReturnFaceLandmarks(value) return self
[docs] def setReturnFaceLandmarksCol(self, value): """ Args: returnFaceLandmarks (object): 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 getReturnFaceLandmarks(self): """ Returns: object: Return face landmarks of the detected faces or not. The default value is false. """ return self._cache.get("returnFaceLandmarks", None)
[docs] def setSubscriptionKey(self, value): """ Args: subscriptionKey (object): the API key to use """ self._java_obj = self._java_obj.setSubscriptionKey(value) return self
[docs] def setSubscriptionKeyCol(self, value): """ Args: subscriptionKey (object): the API key to use """ self._java_obj = self._java_obj.setSubscriptionKeyCol(value) return self
[docs] def getSubscriptionKey(self): """ Returns: object: the API key to use """ return self._cache.get("subscriptionKey", None)
[docs] def setTimeout(self, value): """ Args: timeout (double): number of seconds to wait before closing the connection (default: 60.0) """ self._set(timeout=value) return self
[docs] def getTimeout(self): """ Returns: double: number of seconds to wait before closing the connection (default: 60.0) """ return self.getOrDefault(self.timeout)
[docs] def setUrl(self, value): """ Args: url (str): Url of the service """ self._set(url=value) return self
[docs] def getUrl(self): """ Returns: str: 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] @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.ml.spark.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)