是否可以使用 google vision api 一次扫描 10 张图像 ocr？到目前为止只做了1

Question

我们目前正在使用谷歌视觉 API 做一个 ocr 项目，其中图像返回一个文本值......但到目前为止我们只制作了 1 张图像，是否可以制作 10 张图像？我使用python，这段代码只运行一张图片..谢谢

import os, io
from google.cloud import vision
from google.cloud.vision import types
import pandas as pd

os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = r'anjir.json'

client = vision.ImageAnnotatorClient()

FILE_NAME = 'receipttest2.jpg'
FOLDER_PATH = r'C:\Users\Fadhlan\Desktop\Python venv\image\text'

with io.open(os.path.join(FOLDER_PATH, FILE_NAME), 'rb') as image_file:
    content = image_file.read()

image = vision.types.Image(content=content)
response = client.text_detection(image=image)
texts = response.text_annotations

df = pd.DataFrame(columns=['locale', 'description'])
for text in texts:
    df = df.append(
        dict(
            locale=text.locale,
            description=text.description
        ),
        ignore_index=True

    )
print(df['description'][0])

Answer 1

可以使用batch image annotation offline，因为异步模式支持"TEXT_DETECTION" feature。您可以找到 Python in here 的示例代码，如您所见，需要为每个图像创建一个请求元素并将其添加到请求数组中：

client = vision_v1.ImageAnnotatorClient()

//image one
source1 = {"image_uri": image_uri_1}
image1 = {"source": source1}
features1 = [
    {"type": enums.Feature.Type.LABEL_DETECTION},
    {"type": enums.Feature.Type.IMAGE_PROPERTIES}
]

//image two
source2 = {"image_uri": image_uri_2}
image2 = {"source": source2}
features2 = [
    {"type": enums.Feature.Type.LABEL_DETECTION}
]

# Each requests element corresponds to a single image
requests = [{"image": image1, "features": features1}, {"image": image2, "features": features2}]
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)