首页 > 解决方案 > IndexError:带有 Google Cloud Vision API 的字节数组

问题描述

我正在尝试使用 Google Cloud Vision API 来检测图像中的文本。我遵循以下教程中的代码:https ://cloud.google.com/vision/docs/fulltext-annotations

完整代码如下:

import argparse
from enum import Enum
import io

from google.cloud import vision
from PIL import Image, ImageDraw

class FeatureType(Enum):
    PAGE = 1
    BLOCK = 2
    PARA = 3
    WORD = 4
    SYMBOL = 5


def draw_boxes(image, bounds, color):
    """Draw a border around the image using the hints in the vector list."""
    draw = ImageDraw.Draw(image)

    for bound in bounds:
        draw.polygon([
            bound.vertices[0].x, bound.vertices[0].y,
            bound.vertices[1].x, bound.vertices[1].y,
            bound.vertices[2].x, bound.vertices[2].y,
            bound.vertices[3].x, bound.vertices[3].y], None, color)
    return image


def get_document_bounds(image_file, feature):
    """Returns document bounds given an image."""
    client = vision.ImageAnnotatorClient()

    bounds = []

    with io.open(image_file, 'rb') as image_file:
        content = image_file.read()

    image = vision.Image(content=content)

    response = client.document_text_detection(image=image)
    document = response.full_text_annotation

    # Collect specified feature bounds by enumerating all document features
    for page in document.pages:
        for block in page.blocks:
            for paragraph in block.paragraphs:
                for word in paragraph.words:
                    for symbol in word.symbols:
                        if (feature == FeatureType.SYMBOL):
                            bounds.append(symbol.bounding_box)

                    if (feature == FeatureType.WORD):
                        bounds.append(word.bounding_box)

                if (feature == FeatureType.PARA):
                    bounds.append(paragraph.bounding_box)

            if (feature == FeatureType.BLOCK):
                bounds.append(block.bounding_box)

    # The list `bounds` contains the coordinates of the bounding boxes.
    return bounds


def render_doc_text(filein, fileout):
    image = Image.open(filein)
    bounds = get_document_bounds(filein, FeatureType.BLOCK)
    draw_boxes(image, bounds, 'red')
    bounds = get_document_bounds(filein, FeatureType.PARA)
    draw_boxes(image, bounds, 'red')
    bounds = get_document_bounds(filein, FeatureType.WORD)
    draw_boxes(image, bounds, 'red')

    if fileout != 0:
        image.save(fileout)
    else:
        image.show()


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('detect_file', help='The image for text detection.')
    parser.add_argument('-out_file', help='Optional output file', default=0)
    args = parser.parse_args()

    render_doc_text(args.detect_file, args.out_file)

我正在使用带有 Python 3.7 的 Windows 10,并在命令提示符下使用以下代码:

C:\Users\ariel\Dropbox\Research\Mestizo\Code>python doctext.py censo_19940_tab_corta-30.png -out_file out.jpg

我收到以下错误和回溯:

Traceback (most recent call last):
  File "C:\ProgramData\Anaconda3\lib\site-packages\PIL\ImagePalette.py", line 99, in getcolor
    return self.colors[color]
KeyError: (255, 0, 0)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "doctext.py", line 96, in <module>
    render_doc_text(args.detect_file, args.out_file)
  File "doctext.py", line 78, in render_doc_text
    draw_boxes(image, bounds, 'red')
  File "doctext.py", line 35, in draw_boxes
    bound.vertices[3].x, bound.vertices[3].y], None, color)
  File "C:\ProgramData\Anaconda3\lib\site-packages\PIL\ImageDraw.py", line 239, in polygon
    ink, fill = self._getink(outline, fill)
  File "C:\ProgramData\Anaconda3\lib\site-packages\PIL\ImageDraw.py", line 113, in _getink
    ink = self.palette.getcolor(ink)
  File "C:\ProgramData\Anaconda3\lib\site-packages\PIL\ImagePalette.py", line 109, in getcolor
    self.palette[index + 256] = color[1]
IndexError: bytearray index out of range

我已经查看了有关此错误的先前帖子,但我无法弄清楚这是从哪里来的。

标签: pythonarraysimage-processingocrgoogle-cloud-vision

解决方案


问题是我应该使用 jpg 时使用的是 png 文件。代码/教程的文档使用 jpg 文件作为输入:

https://cloud.google.com/vision/docs/fulltext-annotations

转换为 jpg 后,代码运行没有问题并产生了预期的输出。


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