Home > Article > Backend Development > Learn Python to implement Qiniu Cloud interface docking and image text extraction
Learn Python to implement Qiniu Cloud interface docking and image text extraction
Introduction:
In the modern information technology era, the image text extraction function has gradually become a widely used technology. Qiniu Cloud is a well-known cloud storage service provider that provides developers with a rich API interface, including the function of image text extraction. This article will introduce how to use Python language to connect to the Qiniu Cloud interface and implement the image text extraction function.
1. Introduction to Qiniu Cloud
Qiniu Cloud is a leading cloud computing service provider in China, providing a series of services such as cloud storage, CDN acceleration, file transcoding, and Baidu Cloud. For developers, Qiniu Cloud provides complete development documents and rich API interfaces to facilitate developers to quickly realize various business needs.
2. Image text extraction interface
Qiniu Cloud provides a rich image processing interface, including the function of image text extraction. Developers can use this interface to extract text from images to facilitate subsequent text analysis, recognition and other operations.
3. Install dependent libraries
Before using Python to connect to Qiniu Cloud interface, you need to install the corresponding dependent libraries first. You can use the pip command to install dependent libraries. The specific steps are as follows:
Install Qiniu Cloud SDK
pip install qiniu
Install text recognition library
pip install baidu-aip
4. Connecting to the Qiniu Cloud interface
The following is a sample code for using Python to connect to the Qiniu Cloud interface:
import qiniu from aip import AipOcr # 配置七牛云的Access Key和Secret Key access_key = 'your-access-key' secret_key = 'your-secret-key' # 配置百度云的APP ID、API Key和Secret Key app_id = 'your-app-id' api_key = 'your-api-key' secret_key = 'your-secret-key' # 配置七牛云的Bucket名称和图片名称 bucket_name = 'your-bucket-name' image_name = 'your-image-name' # 构建七牛云的认证对象 q = qiniu.Auth(access_key, secret_key) # 获取七牛云的图片URL image_url = 'http://your-domain-name/' + image_name # 调用七牛云的接口,获取图片内容 image_data = qiniu.urlopen(image_url).read() # 创建百度云的文字识别对象 ocr = AipOcr(app_id, api_key, secret_key) # 调用百度云的接口,进行文字识别 result = ocr.basicGeneral(image_data) # 输出文字识别结果 for word in result['words_result']: print(word['words'])
It should be noted that Access in the sample code Key, Secret Key, App ID, API Key, Secret Key, Bucket name, image name and domain name need to be configured according to your actual situation.
5. Summary
This article introduces how to use Python to connect to Qiniu Cloud interface to realize the function of image text extraction. Through Qiniu Cloud's rich interfaces and convenient development tools, developers can easily realize various business needs. We hope that the introduction of this article can help readers better understand the basic principles and usage of Qiniu Cloud interface docking and image text extraction.
The above is the detailed content of Learn Python to implement Qiniu Cloud interface docking and image text extraction. For more information, please follow other related articles on the PHP Chinese website!