我們目前正在使用 google vision API 做一個(gè) ocr 項(xiàng)目，其中圖像返回一個(gè)文本值......但到目前為止我們只能做 1 張圖像，是否可以做 10 張圖像？我使用 python 并且此代碼僅運(yùn)行一個(gè)圖像..謝謝import os, iofrom google.cloud import visionfrom google.cloud.vision import typesimport pandas as pdos.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_annotationsdf = 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])
1 回答
躍然一笑
TA貢獻(xiàn)1826條經(jīng)驗(yàn) 獲得超6個(gè)贊
由于異步模式支持“TEXT_DETECTION”功能，因此可以離線使用批量圖像注釋。您可以在此處找到 Python 的示例代碼，如您所見(jiàn)，需要為每個(gè)圖像創(chuàng)建一個(gè)請(qǐng)求元素并將其添加到請(qǐng)求數(shù)組中：
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)
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