Tutorial: Python connects to Huawei Cloud interface to implement image content recognition and search functions

Tutorial: Python connects to Huawei Cloud interface to implement image content recognition and search functions

In daily life, image content recognition and search functions are increasingly used, such as face recognition, image classification, etc. . Huawei Cloud provides a powerful image content recognition service. This article will introduce how to use Python to connect to the Huawei Cloud interface to implement image content recognition and search functions.

Step 1: Register a Huawei Cloud account

First, we need to register a Huawei Cloud account. Open the official Huawei Cloud website (https://www.huaweicloud.com/), click the "Register" button, and fill in the information according to the process to complete the registration.

Step 2: Create a Huawei Cloud image content recognition service

Log in to the Huawei Cloud backend, select "Artificial Intelligence AI" in the console, and enter "Big Data and AI Services".

In "Big Data and AI Services", select "Image Content Recognition" and then click "Create Service".

Fill in the relevant information, such as service name, region, etc., and click "Create Service".

After the creation is completed, on the "Image Content Recognition" service details page, we can see the "API Key", "URL Address" and other information. We need to record this so that we can use it later in our Python code.

Step 3: Install dependent libraries

Run the following command in the terminal to install the required Python dependent libraries.

pip install requests
pip install json

Step 4: Write Python code

Next, we connect the Huawei Cloud interface through the Python code to implement image content recognition and search functions.

import requests
import json

def image_content_recognition(image_path):
    # 图像内容识别接口URL
    url = "URL地址"

    # API密钥
    api_key = "API密钥"

    # 将图像转换为Base64编码
    with open(image_path, "rb") as f:
        image_base64 = str(base64.b64encode(f.read()), "utf-8")

    # 构建请求参数
    payload = {
        "image": image_base64,
    }
    headers = {
        "Content-Type": "application/json",
        "X-Auth-Token": api_key,
    }

    # 发送POST请求
    response = requests.post(url, data=json.dumps(payload), headers=headers)

    # 解析响应数据
    result = response.json()

    # 输出识别结果
    print(result)

# 测试代码
image_path = "test.jpg"
image_content_recognition(image_path)

In the above code, we first define a function image_content_recognition, which receives an image path as a parameter. In the function, we read the image file and convert it to Base64 encoding. Next, we constructed the request parameters and request headers, and sent a POST request to send the image data to the Huawei Cloud interface. Finally, we parse and output the recognition results.

Step 5: Test code

Put the image file to be recognized in the same directory as the Python code and name it test.jpg. Then run the Python code to perform image content recognition and search.

Summary

Through this tutorial, we learned how to use Python to connect to the Huawei Cloud interface to implement image content recognition and search functions. Huawei Cloud's image content recognition service has powerful algorithms and rich functions, and can be widely used in fields such as image recognition and classification. You can further expand and optimize the code according to your own needs to meet more application scenarios. I wish everyone a happy use!

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