Source code for azure.cognitiveservices.vision.customvision.prediction.operations._custom_vision_prediction_client_operations

# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------

from msrest.pipeline import ClientRawResponse
from .. import models


[docs]class CustomVisionPredictionClientOperationsMixin(object):
[docs] def classify_image( self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config): """Classify an image and saves the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param image_data: Binary image data. Supported formats are JPEG, GIF, PNG, and BMP. Supports images up to 4MB. :type image_data: Generator :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ # Construct URL url = self.classify_image.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'multipart/form-data' if custom_headers: header_parameters.update(custom_headers) # Construct form data form_data_content = { 'imageData': image_data, } # Construct and send request request = self._client.post(url, query_parameters, header_parameters, form_content=form_data_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
classify_image.metadata = {'url': '/{projectId}/classify/iterations/{publishedName}/image'}
[docs] def classify_image_with_no_store( self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config): """Classify an image without saving the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param image_data: Binary image data. Supported formats are JPEG, GIF, PNG, and BMP. Supports images up to 4MB. :type image_data: Generator :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ # Construct URL url = self.classify_image_with_no_store.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'multipart/form-data' if custom_headers: header_parameters.update(custom_headers) # Construct form data form_data_content = { 'imageData': image_data, } # Construct and send request request = self._client.post(url, query_parameters, header_parameters, form_content=form_data_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
classify_image_with_no_store.metadata = {'url': '/{projectId}/classify/iterations/{publishedName}/image/nostore'}
[docs] def classify_image_url( self, project_id, published_name, url, application=None, custom_headers=None, raw=False, **operation_config): """Classify an image url and saves the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param url: Url of the image. :type url: str :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ image_url = models.ImageUrl(url=url) # Construct URL url = self.classify_image_url.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'application/json; charset=utf-8' if custom_headers: header_parameters.update(custom_headers) # Construct body body_content = self._serialize.body(image_url, 'ImageUrl') # Construct and send request request = self._client.post(url, query_parameters, header_parameters, body_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
classify_image_url.metadata = {'url': '/{projectId}/classify/iterations/{publishedName}/url'}
[docs] def classify_image_url_with_no_store( self, project_id, published_name, url, application=None, custom_headers=None, raw=False, **operation_config): """Classify an image url without saving the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param url: Url of the image. :type url: str :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ image_url = models.ImageUrl(url=url) # Construct URL url = self.classify_image_url_with_no_store.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'application/json; charset=utf-8' if custom_headers: header_parameters.update(custom_headers) # Construct body body_content = self._serialize.body(image_url, 'ImageUrl') # Construct and send request request = self._client.post(url, query_parameters, header_parameters, body_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
classify_image_url_with_no_store.metadata = {'url': '/{projectId}/classify/iterations/{publishedName}/url/nostore'}
[docs] def detect_image( self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config): """Detect objects in an image and saves the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param image_data: Binary image data. Supported formats are JPEG, GIF, PNG, and BMP. Supports images up to 4MB. :type image_data: Generator :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ # Construct URL url = self.detect_image.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'multipart/form-data' if custom_headers: header_parameters.update(custom_headers) # Construct form data form_data_content = { 'imageData': image_data, } # Construct and send request request = self._client.post(url, query_parameters, header_parameters, form_content=form_data_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
detect_image.metadata = {'url': '/{projectId}/detect/iterations/{publishedName}/image'}
[docs] def detect_image_with_no_store( self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config): """Detect objects in an image without saving the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param image_data: Binary image data. Supported formats are JPEG, GIF, PNG, and BMP. Supports images up to 4MB. :type image_data: Generator :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ # Construct URL url = self.detect_image_with_no_store.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'multipart/form-data' if custom_headers: header_parameters.update(custom_headers) # Construct form data form_data_content = { 'imageData': image_data, } # Construct and send request request = self._client.post(url, query_parameters, header_parameters, form_content=form_data_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
detect_image_with_no_store.metadata = {'url': '/{projectId}/detect/iterations/{publishedName}/image/nostore'}
[docs] def detect_image_url( self, project_id, published_name, url, application=None, custom_headers=None, raw=False, **operation_config): """Detect objects in an image url and saves the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param url: Url of the image. :type url: str :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ image_url = models.ImageUrl(url=url) # Construct URL url = self.detect_image_url.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'application/json; charset=utf-8' if custom_headers: header_parameters.update(custom_headers) # Construct body body_content = self._serialize.body(image_url, 'ImageUrl') # Construct and send request request = self._client.post(url, query_parameters, header_parameters, body_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
detect_image_url.metadata = {'url': '/{projectId}/detect/iterations/{publishedName}/url'}
[docs] def detect_image_url_with_no_store( self, project_id, published_name, url, application=None, custom_headers=None, raw=False, **operation_config): """Detect objects in an image url without saving the result. :param project_id: The project id. :type project_id: str :param published_name: Specifies the name of the model to evaluate against. :type published_name: str :param url: Url of the image. :type url: str :param application: Optional. Specifies the name of application using the endpoint. :type application: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: ImagePrediction or ClientRawResponse if raw=true :rtype: ~azure.cognitiveservices.vision.customvision.prediction.models.ImagePrediction or ~msrest.pipeline.ClientRawResponse :raises: :class:`CustomVisionErrorException<azure.cognitiveservices.vision.customvision.prediction.models.CustomVisionErrorException>` """ image_url = models.ImageUrl(url=url) # Construct URL url = self.detect_image_url_with_no_store.metadata['url'] path_format_arguments = { 'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True), 'projectId': self._serialize.url("project_id", project_id, 'str'), 'publishedName': self._serialize.url("published_name", published_name, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} if application is not None: query_parameters['application'] = self._serialize.query("application", application, 'str') # Construct headers header_parameters = {} header_parameters['Accept'] = 'application/json' header_parameters['Content-Type'] = 'application/json; charset=utf-8' if custom_headers: header_parameters.update(custom_headers) # Construct body body_content = self._serialize.body(image_url, 'ImageUrl') # Construct and send request request = self._client.post(url, query_parameters, header_parameters, body_content) response = self._client.send(request, stream=False, **operation_config) if response.status_code not in [200]: raise models.CustomVisionErrorException(self._deserialize, response) deserialized = None if response.status_code == 200: deserialized = self._deserialize('ImagePrediction', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized
detect_image_url_with_no_store.metadata = {'url': '/{projectId}/detect/iterations/{publishedName}/url/nostore'}