Share Python code to implement Baidu image recognition API docking tutorial

Python code to implement Baidu image recognition API docking tutorial

Introduction: Baidu image recognition API is a technology for intelligent recognition based on image content, which can classify images , detection, segmentation, recognition and other operations. This article will introduce how to use Python to connect to Baidu Image Recognition API, and provide code examples for reference.

1. Preparation

1.1 Register a Baidu Cloud account and create an image recognition application
First, you need to register an account on Baidu Cloud and create an image recognition application in the product service application. After creating the application, you will obtain an API Key and Secret Key.

1.2 Install Python and required libraries
Make sure you have installed Python and the following required libraries:

• requests: used to send HTTP requests

You can install the library through the pip command:

pip install requests

2. Send image recognition request

2.1 Import the required library
First, import requests in the Python code Library:

import requests

2.2 Set API Key and Secret Key
Set the API Key and Secret Key you obtained in the preparation work as global variables:

API_KEY = 'your_api_key'
SECRET_KEY = 'your_secret_key'

2.3 Build request parameters
Build a dictionary containing some necessary request parameters and the path of the image file to be recognized:

params = {
    'image': '',  # 待识别的图像文件路径
    'access_token': '',  # 注册应用获得的access_token
}

2.4 Obtain access_token
Use API Key and Secret Key to obtain access_token:

def get_access_token(api_key, secret_key):
    url = 'https://aip.baidubce.com/oauth/2.0/token'
    params = {
        'grant_type': 'client_credentials',
        'client_id': api_key,
        'client_secret': secret_key,
    }
    response = requests.get(url, params=params)
    if response.status_code == 200:
        access_token = response.json()['access_token']
        return access_token
    else:
        return None

params['access_token'] = get_access_token(API_KEY, SECRET_KEY)

2.5 Send an identification request
Construct the URL of the identification request and send an HTTP POST request:

def recognize_image(image_file):
    url = 'https://aip.baidubce.com/rest/2.0/image-classify/v2/advanced_general'
    files = {'image': open(image_file, 'rb')}
    response = requests.post(url, params=params, files=files)
    if response.status_code == 200:
        result = response.json()
        return result
    else:
        return None

result = recognize_image(params['image'])

3. Process the identification results

3.1 Parse the identification results
According to the JSON data returned by the interface Structure, analysis and recognition results:

def parse_result(result):
    if 'result' in result:
        for item in result['result']:
            print(item['keyword'])

3.2 Complete code example
Integrate the above codes together to form a complete code example:

import requests

API_KEY = 'your_api_key'
SECRET_KEY = 'your_secret_key'

params = {
    'image': '',  # 待识别的图像文件路径
    'access_token': '',  # 注册应用获得的access_token
}

def get_access_token(api_key, secret_key):
    ...

params['access_token'] = get_access_token(API_KEY, SECRET_KEY)

def recognize_image(image_file):
    ...

result = recognize_image(params['image'])

def parse_result(result):
    ...

parse_result(result)

4. Summary

This article introduces how to use Python to connect to Baidu Image Recognition API and provides a complete code example. By studying this tutorial, you can use Python to easily implement the docking operation with Baidu Image Recognition API. Hope this article helps you!

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