Azure Computer Vision 中的手写识别 API 来自本地存储的图像文件

Question

我正在尝试通过探索 Azure 来提高我的编码和云计算技能。我想自动化一些涉及破译大量手写文档和以电子方式存储文本的管理任务。

下面的 Python 代码是两个代码源的合并。

1. Taygan Rifat 的博客https://www.taygan.co/blog/2018/4/28/image-processing-with-cognitive-services

2. 微软自己的演示代码在https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/quickstarts/python-hand-text

import json
import os
import sys
import requests
import time
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from PIL import Image
from io import BytesIO

subscription_key = 'XX79fdc005d542XXXb5f29ce04ab1cXXX'
endpoint = 'https://handwritng.cognitiveservices.azure.com/'
analyze_url = endpoint + "vision/v3.0/analyze"
text_recognition_url = endpoint + "/vision/v3.0/read/analyze"

image_url = "https://3j2w6t1pktei3iwq0u47sym8-wpengine.netdna-ssl.com/wp-content/uploads/2014/08/Handwriting-sample-Katie.png"

headers = {'Ocp-Apim-Subscription-Key': subscription_key}
data = {'url': image_url}
response = requests.post(
    text_recognition_url, headers=headers, json=data)
response.raise_for_status()

# Extracting text requires two API calls: One call to submit the
# image for processing, the other to retrieve the text found in the image.

# Holds the URI used to retrieve the recognized text.
operation_url = response.headers["Operation-Location"]

# The recognized text isn't immediately available, so poll to wait for completion.
analysis = {}
poll = True
while (poll):
    response_final = requests.get(
        response.headers["Operation-Location"], headers=headers)
    analysis = response_final.json()

    print(json.dumps(analysis, indent=4))

    time.sleep(1)
    if ("analyzeResult" in analysis):
        poll = False
    if ("status" in analysis and analysis['status'] == 'failed'):
        poll = False

polygons = []
if ("analyzeResult" in analysis):
    # Extract the recognized text, with bounding boxes.
    polygons = [(line["boundingBox"], line["text"])
                for line in analysis["analyzeResult"]["readResults"][0]["lines"]]

# Display the image and overlay it with the extracted text.
image = Image.open(BytesIO(requests.get(image_url).content))
ax = plt.imshow(image)
for polygon in polygons:
    vertices = [(polygon[0][i], polygon[0][i + 1])
                for i in range(0, len(polygon[0]), 2)]
    text = polygon[1]
    print(text)
    patch = Polygon(vertices, closed=True, fill=False, linewidth=2, color='y')
    ax.axes.add_patch(patch)
    plt.text(vertices[0][0], vertices[0][1], text, fontsize=20, va="top")


plt.show()

我想做的是在修改脚本方面获得一些帮助，以便它可以处理本地存储的图像文件（而不是使用 URLs）。

目前，我正在通过在 Azure 虚拟机上启动 IIS 服务器并访问我想通过 HTML 分析的图像的 URL 来解决这个问题。它有点笨拙（对我来说有点不安全）。

谢谢，WL

Answer 1

给你，

...
# You could also read the image file name from command line
# as the first argument passed to your script:

# try:
#    input_image = sys.argv[1]
# except:
#    sys.exit('No input. Pass input image file name as first argument.')

input_image = "your_input_image.jpg"
with open(input_image, 'rb') as f:
    data = f.read()
    headers = {
        'Ocp-Apim-Subscription-Key': subscription_key,
        'Content-type': 'application/octet-stream'
    }
    response = requests.post(
        text_recognition_url, headers=headers, data=data)
    response.raise_for_status()
...

以后，

# Display the image and overlay it with the extracted text.
image = Image.open(input_image)
...

大多数接受图像 URL 的 Azure 认知服务也接受原始字节作为 Content-type: application/octet-stream 和二进制图像数据作为 POST 有效负载。

见Analyze image。

Supported input methods:

raw image binary or image URL.

Content-type:

Input requirements:

Supported image formats: JPEG, PNG, GIF, BMP.
Image file size must be less than 4MB.
Image dimensions must be at least 50 x 50.

顺便说一句，如果您需要一个快速的网络服务器来完成未来的任务，Python 会支持您：

# usage:
# python3 -m http.server [-h] [--cgi] [--bind ADDRESS]
#                        [--directory DIRECTORY] [port]

$ python3 -m http.server
Serving HTTP on :: port 8000 (http://[::]:8000/) ...