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azure - 将批处理请求发送到用于 TEXT-OCR 的 Azure 认知 API

问题描述

我正在调用用于 OCR 文本识别的 Azure 认知 API，并且我同时传递 10 个图像（因为下面的代码一次只接受一个图像——即并行 10 个独立请求），这不是从处理的角度来看，对我来说效率很高，因为我需要使用额外的模块，即：Celery 和多处理。

那么，有没有办法在一个请求中发送所有 10 张图像并立即获取输出然后进行后期处理？

import time
from io import BytesIO

import cv2
import requests
from PIL import Image as PILImage
from PIL import Image
file_list = []

headers = {
    "Ocp-Apim-Subscription-Key": "<API-KEY>",
    'Content-Type': 'application/octet-stream'}

p = "symbol_sample.jpg"
print(p,"p")

def recognise_text(p):
    p = cv2.imread(p)
    cropped_image = PILImage.fromarray(p)
    buffer = BytesIO()
    cropped_image.save(buffer, format="JPEG")
    image_bytes = buffer.getvalue()
    try:
        response = requests.post(
            "https://centralindia.api.cognitive.microsoft.com/vision/v2.0/recognizeText?mode=Printed",
            headers=headers,
            data=image_bytes
        )
        header_link = str(response.headers['Operation-Location'])
        while (True):
            headers_get = {
                "Ocp-Apim-Subscription-Key": "<API-KEY>"",
                'Content-Type': 'application/json'
            }
            result = requests.get(
                url=header_link,
                headers=headers_get
            )
            response_r = result.json()
            if response_r["status"] == "Succeeded":
                return response_r
            else:
                time.sleep(4)
    except Exception as e:
        print(e)
        return ""

image1="symbol_sample.jpg"
o = recognise_text(image1)
print(o)

任何帮助将非常感激。

标签： azureocrbatch-processingazure-cognitive-services

解决方案

我猜你正在寻找Batch Read File

public class BatchReadFileSample
    {
        public static async Task RunAsync(string endpoint, string key)
        {
            ComputerVisionClient computerVision = new ComputerVisionClient(new ApiKeyServiceClientCredentials(key))
            {
                Endpoint = endpoint
            };
            const int numberOfCharsInOperationId = 36;

            string localImagePath = @"Images\handwritten_text.jpg";  // See this repo's readme.md for info on how to get these images. Alternatively, you can just set the path to any appropriate image on your machine.
            string remoteImageUrl = "https://github.com/Azure-Samples/cognitive-services-sample-data-files/raw/master/ComputerVision/Images/printed_text.jpg";

            Console.WriteLine("Text being batch read ...");
            await BatchReadFileFromStreamAsync(computerVision, localImagePath, numberOfCharsInOperationId); 
            await BatchReadFileFromUrlAsync(computerVision, remoteImageUrl, numberOfCharsInOperationId);
        }

        // Read text from a remote image
        private static async Task BatchReadFileFromUrlAsync(ComputerVisionClient computerVision, string imageUrl, int numberOfCharsInOperationId)
        {
            if (!Uri.IsWellFormedUriString(imageUrl, UriKind.Absolute))
            {
                Console.WriteLine("\nInvalid remote image url:\n{0} \n", imageUrl);
                return;
            }

            // Start the async process to read the text
            BatchReadFileHeaders textHeaders = await computerVision.BatchReadFileAsync(imageUrl);
            await GetTextAsync(computerVision, textHeaders.OperationLocation, numberOfCharsInOperationId);
        }

        // Recognize text from a local image
        private static async Task BatchReadFileFromStreamAsync(ComputerVisionClient computerVision, string imagePath, int numberOfCharsInOperationId)
        {
            if (!File.Exists(imagePath))
            {
                Console.WriteLine("\nUnable to open or read local image path:\n{0} \n", imagePath);
                return;
            }

            using (Stream imageStream = File.OpenRead(imagePath))
            {
                // Start the async process to recognize the text
                BatchReadFileInStreamHeaders textHeaders = await computerVision.BatchReadFileInStreamAsync(imageStream);
                await GetTextAsync(computerVision, textHeaders.OperationLocation, numberOfCharsInOperationId);
            }
        }

这是完整的代码

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