本文整理汇总了Python中airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook.label_detection方法的典型用法代码示例。如果您正苦于以下问题：Python CloudVisionHook.label_detection方法的具体用法？Python CloudVisionHook.label_detection怎么用？Python CloudVisionHook.label_detection使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook的用法示例。
在下文中一共展示了CloudVisionHook.label_detection方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: execute
# 需要导入模块: from airflow.contrib.hooks.gcp_vision_hook import CloudVisionHook [as 别名]
# 或者: from airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook import label_detection [as 别名]
def execute(self, context):
hook = CloudVisionHook(gcp_conn_id=self.gcp_conn_id)
return hook.label_detection(
image=self.image,
max_results=self.max_results,
retry=self.retry,
timeout=self.timeout,
additional_properties=self.additional_properties,
)示例2: TestGcpVisionHook
# 需要导入模块: from airflow.contrib.hooks.gcp_vision_hook import CloudVisionHook [as 别名]
# 或者: from airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook import label_detection [as 别名]
#.........这里部分代码省略.........
def test_document_text_detection_with_additional_properties(self, annotator_client_mock):
# Given
document_text_detection_method = annotator_client_mock.document_text_detection
document_text_detection_method.return_value = AnnotateImageResponse(
text_annotations=[EntityAnnotation(description="test", score=0.5)]
)
# When
self.hook.document_text_detection(
image=DETECT_TEST_IMAGE, additional_properties={"prop1": "test1", "prop2": "test2"}
)
# Then
document_text_detection_method.assert_called_once_with(
image=DETECT_TEST_IMAGE, max_results=None, retry=None, timeout=None, prop1="test1", prop2="test2"
)
@mock.patch("airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook.annotator_client")
def test_detect_document_text_with_error_response(self, annotator_client_mock):
# Given
detect_text_method = annotator_client_mock.document_text_detection
detect_text_method.return_value = AnnotateImageResponse(
error={"code": 3, "message": "test error message"}
)
# When
with self.assertRaises(AirflowException) as msg:
self.hook.document_text_detection(image=DETECT_TEST_IMAGE)
err = msg.exception
self.assertIn("test error message", str(err))
@mock.patch("airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook.annotator_client")
def test_label_detection(self, annotator_client_mock):
# Given
label_detection_method = annotator_client_mock.label_detection
label_detection_method.return_value = AnnotateImageResponse(
label_annotations=[EntityAnnotation(description="test", score=0.5)]
)
# When
self.hook.label_detection(image=DETECT_TEST_IMAGE)
# Then
label_detection_method.assert_called_once_with(
image=DETECT_TEST_IMAGE, max_results=None, retry=None, timeout=None
)
@mock.patch("airflow.contrib.hooks.gcp_vision_hook.CloudVisionHook.annotator_client")
def test_label_detection_with_additional_properties(self, annotator_client_mock):
# Given
label_detection_method = annotator_client_mock.label_detection
label_detection_method.return_value = AnnotateImageResponse(
label_annotations=[EntityAnnotation(description="test", score=0.5)]
)
# When
self.hook.label_detection(
image=DETECT_TEST_IMAGE, additional_properties={"prop1": "test1", "prop2": "test2"}
)
# Then
label_detection_method.assert_called_once_with(
image=DETECT_TEST_IMAGE, max_results=None, retry=None, timeout=None, prop1="test1", prop2="test2"
)