Use Python to implement Baidu AI interface docking to make your program smarter and more powerful

Use Python to implement the docking of Baidu AI interface to make your program smarter and more powerful

With the rapid development of artificial intelligence, Baidu AI interface provides a series of Powerful functions, such as face recognition, text recognition, speech recognition, etc., can make our programs more intelligent and powerful. This article will introduce how to use Python to connect to Baidu AI interface to implement various functions.

First, we need to create a Baidu AI developer account and create an application. After creating the application, we can obtain the API Key and Secret Key, which will be used in subsequent code.

Next, we use Python’s requests library to send HTTP requests to call Baidu AI interface. We can achieve this through the following code:

import requests

def face_detection(image_path):
    access_token = "your_access_token"  # 替换成自己的access_token
    url = "https://aip.baidubce.com/rest/2.0/face/v3/detect?access_token=" + access_token
    headers = {'Content-Type': 'application/json'}
    data = {
        'image': '',
        'image_type': 'URL',
        'face_field': 'age,gender,beauty',
        'max_face_num': 10
    }
    try:
        with open(image_path, 'rb') as file:
            img = file.read()
            data['image'] = str(base64.b64encode(img), 'utf-8')
    except Exception as e:
        print("读取图片出错：" + str(e))

    try:
        response = requests.post(url, headers=headers, json=data)
        if response.status_code == requests.codes.ok:
            results = response.json()
            # 处理返回的结果
            print(results)
    except Exception as e:
        print("请求接口出错：" + str(e))

The above code is an example of face detection, which returns the age, gender, appearance and other information of the face to us. Before calling the interface, we need to replace your_access_token with our own access_token, which can be obtained from the Baidu AI Developer Platform.

In addition to face detection, Baidu AI interface also provides many other functions, such as text recognition, speech recognition, etc. The following is an example of text recognition:

def text_recognition(image_path):
    access_token = "your_access_token"  # 替换成自己的access_token
    url = "https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic?access_token=" + access_token
    headers = {'Content-Type': 'application/x-www-form-urlencoded'}
    data = {
        'image': ''
    }
    try:
        with open(image_path, 'rb') as file:
            img = file.read()
            data['image'] = str(base64.b64encode(img), 'utf-8')
    except Exception as e:
        print("读取图片出错：" + str(e))

    try:
        response = requests.post(url, headers=headers, data=data)
        if response.status_code == requests.codes.ok:
            results = response.json()
            # 处理返回的结果
            print(results)
    except Exception as e:
        print("请求接口出错：" + str(e))

Call the above code to recognize the text in the picture.

In addition to the above two examples, Baidu AI interface also has many other functions, such as speech synthesis, sentiment analysis, etc. By using Python to connect to Baidu AI interface, we can apply these powerful functions to our own programs, making the programs smarter and more powerful.

To sum up, this article introduces how to use Python to realize the docking of Baidu AI interface, and demonstrates the functions of face detection and text recognition through sample code. I hope readers can use these sample codes to apply Baidu AI interface to their own programs and achieve more cool functions. Baidu AI interface is very rich in functions. I hope readers can continue to study it in depth and discover more interesting and practical applications.

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