Azure Computer Vision API 中的手写识别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解密大量手写文档并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 URL）。

目前，我正在通过在 Azure 虚拟机上启动 IIS 服务器并访问要通过 HTML 分析的图像的 URL 来解决此问题。它有点笨拙（而且对我的目的来说有点不安全）。

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 认知服务也接受作为 Content-type: application/octet-stream 的原始字节和作为 POST 有效负载的二进制图像数据。

见Analyze image。

支持的输入法：

原始图像二进制或图像 URL。

内容类型：

输入要求：

支持的图像格式：JPEG、PNG、GIF、BMP。
图片文件大小必须小于 4MB。
图片尺寸必须至少为 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 可以为您提供支持：

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

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

Answer 2

如何从文件系统传递图像而不是 https 图像？

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

而不是使用 file = "/user/project/product_info.jpg"