来自Google Vision API的OCR置信度得分

Question

我正在使用Google Vision OCR从python中的图像中提取文本。

使用下面的代码片段。

但是，置信度得分总是显示0.0，这肯定是不正确的。

如何从Google响应中提取单个字符或单词的OCR置信度得分？

 content = cv2.imencode('.jpg', cv2.imread(file_name))[1].tostring()
 img = types.Image(content=content)
 response1 = client.text_detection(image=img, image_context={"language_hints": ["en"]})
 response_annotations = response1.text_annotations
 for x in response1.text_annotations:
      print(x)
      print(f'confidence:{x.confidence}')

示例:迭代的输出

description: "Date:"
bounding_poly {
  vertices {
    x: 127
    y: 11
  }
  vertices {
    x: 181
    y: 10
  }
  vertices {
    x: 181
    y: 29
  }
  vertices {
    x: 127
    y: 30
  }
}

confidence:0.0

Answer 1

我设法重现了你的问题。我使用了以下函数，并获得了所有项目的置信度0.0。

from google.cloud import vision

def detect_text_uri(uri):
    client = vision.ImageAnnotatorClient()
    image = vision.types.Image()
    image.source.image_uri = uri

    response = client.text_detection(image=image)
    texts = response.text_annotations
    print('Texts:')

    for text in texts:
        print('\n"{}"'.format(text.description))

        vertices = (['({},{})'.format(vertex.x, vertex.y)
                    for vertex in text.bounding_poly.vertices])

        print('bounds: {}'.format(','.join(vertices)))
        print("confidence: {}".format(text.confidence))

    if response.error.message:
        raise Exception(
            '{}\nFor more info on error messages, check: '
            'https://cloud.google.com/apis/design/errors'.format(
                response.error.message))

然而，当在documentation中使用带有"Try the API“选项的相同图像时，我得到了置信度为0的结果。当从本地图像中检测文本时，也会发生这种情况。

人们应该期望使用这两种方法的置信度具有相同的价值。我已经打开了一个问题追踪器，检查它here。

Answer 2

检索正确的GOCR响应置信度值的工作代码。

(使用document_text_detection()而不是text_detection())

def detect_document(path):
    """Detects document features in an image."""
    from google.cloud import vision
    import io
    client = vision.ImageAnnotatorClient()

    # [START vision_python_migration_document_text_detection]
    with io.open(path, 'rb') as image_file:
        content = image_file.read()

    image = vision.types.Image(content=content)

    response = client.document_text_detection(image=image)

    for page in response.full_text_annotation.pages:
        for block in page.blocks:
            print('\nBlock confidence: {}\n'.format(block.confidence))

            for paragraph in block.paragraphs:
                print('Paragraph confidence: {}'.format(
                    paragraph.confidence))

                for word in paragraph.words:
                    word_text = ''.join([
                        symbol.text for symbol in word.symbols
                    ])
                    print('Word text: {} (confidence: {})'.format(
                        word_text, word.confidence))

                    for symbol in word.symbols:
                        print('\tSymbol: {} (confidence: {})'.format(
                            symbol.text, symbol.confidence))

    if response.error.message:
        raise Exception(
            '{}\nFor more info on error messages, check: '
            'https://cloud.google.com/apis/design/errors'.format(
                response.error.message))
    # [END vision_python_migration_document_text_detection]
# [END vision_fulltext_detection]

# add your own path
path = "gocr_vision.png"
detect_document(path)