如何使用Google的视觉API在一次调用中为多张图像添加注释?蟒蛇

我最近开始使用Google的视觉API。我正在尝试批注图像,因此从其文档中发布了'batch image annotation offline'指南。

但是,我不清楚如何从一个API调用中注释多个图像。假设我在Google云端存储桶中存储了10张图片。如何立即注释所有这些图像并将它们存储在一个JSON文件中?现在,我编写了一个程序,调用它们的示例函数,并且可以运行,但是简单起见,为什么我不能说:“查看此文件夹并注释其中的所有图像。”

谢谢。

from batch_image_labeling import sample_async_batch_annotate_images
counter = 0
for file in os.listdir('my_directory'):
    filename = file
    sample_async_batch_annotate_images('gs://my_bucket/{}'.format(filename),'gs://my_bucket/{}'.format(counter))
    counter += 1


from google.cloud import vision_v1
from google.cloud.vision_v1 import enums
import six

def sample_async_batch_annotate_images(input_image_uri,output_uri):
  """Perform async batch image annotation"""

  client = vision_v1.ImageAnnotatorClient()

  if isinstance(input_image_uri,six.binary_type):
    input_image_uri = input_image_uri.decode('utf-8')
  if isinstance(output_uri,six.binary_type):
    output_uri = output_uri.decode('utf-8')
  source = {'image_uri': input_image_uri}
  image = {'source': source}
  type_ = enums.Feature.Type.LABEL_DETECTION
  features_element = {'type': type_}
  type_2 = enums.Feature.Type.IMAGE_PROPERTIES
  features_element_2 = {'type': type_2}
  features = [features_element,features_element_2]
  requests_element = {'image': image,'features': features}
  requests = [requests_element]
  gcs_destination = {'uri': output_uri}

  # The max number of responses to output in each JSON file
  batch_size = 2
  output_config = {'gcs_destination': gcs_destination,'batch_size': batch_size}

  operation = client.async_batch_annotate_images(requests,output_config)

  print('Waiting for operation to complete...')
  response = operation.result()

  # The output is written to GCS with the provided output_uri as prefix
  gcs_output_uri = response.output_config.gcs_destination.uri
  print('Output written to GCS with prefix: {}'.format(gcs_output_uri))
hanyujing 回答:如何使用Google的视觉API在一次调用中为多张图像添加注释?蟒蛇

从该示例中尚不清楚,但是您对async_batch_annotate_images的调用带有一个requests参数,该参数是多个请求的列表。因此,您可以执行以下操作:

rom google.cloud import vision_v1
from google.cloud.vision_v1 import enums
import six

def generate_request(input_image_uri):
  if isinstance(input_image_uri,six.binary_type):
    input_image_uri = input_image_uri.decode('utf-8')
  if isinstance(output_uri,six.binary_type):
    output_uri = output_uri.decode('utf-8')
  source = {'image_uri': input_image_uri}
  image = {'source': source}
  type_ = enums.Feature.Type.LABEL_DETECTION
  features_element = {'type': type_}
  type_2 = enums.Feature.Type.IMAGE_PROPERTIES
  features_element_2 = {'type': type_2}
  features = [features_element,features_element_2]
  requests_element = {'image': image,'features': features}

  return requests_element


def sample_async_batch_annotate_images(input_uri,output_uri):
  """Perform async batch image annotation"""

  client = vision_v1.ImageAnnotatorClient()

  requests = [
    generate_request(input_uri.format(filename))
    for filename in os.listdir('my_directory')
  ]

  gcs_destination = {'uri': output_uri}

  # The max number of responses to output in each JSON file
  batch_size = 1
  output_config = {'gcs_destination': gcs_destination,'batch_size': batch_size}

  operation = client.async_batch_annotate_images(requests,output_config)

  print('Waiting for operation to complete...')
  response = operation.result()

  # The output is written to GCS with the provided output_uri as prefix
  gcs_output_uri = response.output_config.gcs_destination.uri
  print('Output written to GCS with prefix: {}'.format(gcs_output_uri))


sample_async_batch_annotate_images('gs://my_bucket/{}','gs://my_bucket/results')

这可以在单个请求中注释多达2,000张图像。唯一的缺点是您只能指定一个output_uri作为目的地,因此您将无法使用counter将每个结果放在单独的文件中,但可以设置{{1 }},以确保在需要时分别编写每个响应。

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