Write code in Python to implement Baidu face recognition API docking and implement facial feature analysis

Writing code in Python to implement Baidu face recognition API docking and facial feature analysis

Face recognition technology has developed rapidly in recent years and is widely used in security monitoring and user Authentication, face search and other fields. Baidu Face Recognition API is a powerful tool that provides rich facial feature analysis functions. This article will introduce how to use Python to write code to implement facial feature analysis by docking Baidu Face Recognition API.

First, we need to prepare the Python development environment. It is recommended to use Python 3.x version and install the necessary dependent libraries. In this example, we will use the following libraries:

• requests: used to send HTTP requests and receive API responses;
• json: used to parse JSON format data of API responses;
• base64: used to encode images.

After installing the above libraries, we also need to create an application on the Baidu AI open platform and obtain the access key (API Key) and secret key (Secret Key). Next, we can start writing code to implement facial feature analysis.

First, import the required libraries:

import requests
import json
import base64

Next, define a function get_face_features(image), which receives the path of a face photo as a parameter , and returns the feature vector of the face in the photo. The specific code is as follows:

def get_face_features(image_path):
    # 读取图片文件
    with open(image_path, 'rb') as f:
        image_data = f.read()

    # 对图片进行base64编码
    image_base64 = base64.b64encode(image_data).decode('utf-8')

    # 构造请求URL
    url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"

    # 构造请求参数
    params = {
        "image": image_base64,
        "image_type": "BASE64",
        "face_field": "face_shape,gender,age" # 获取人脸形状、性别和年龄信息
    }

    # 构造请求头部
    headers = {
        "Content-Type": "application/json"
    }

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

    # 解析API响应结果
    result = json.loads(response.text)

    # 提取人脸特征向量
    face_features = []
    if result['error_code'] == 0:
        face_features = result['result']['face_list'][0]['feature']
    
    return face_features

In the above code, we first read the image file, and then use base64 to encode the image. Next, we construct a request URL and set the request parameters image, image_type and face_field, which respectively represent the image base64 data, image type and person who needs to be returned. Facial feature field. Finally, we send a POST request and parse the API response to obtain the face feature vector.

Next, we can write a simple program to test this function. The sample code is as follows:

if __name__ == '__main__':
    # 测试图片路径
    image_path = "test.jpg"

    # 获取人脸特征向量
    face_features = get_face_features(image_path)

    # 打印人脸特征向量
    print(face_features)

In the above code, we specify the path of a test image, and then call the get_face_features function to obtain the face feature vector and print it out.

When we run this code, we will get output similar to the following:

[0.234, 0.456, 0.678, ...] # 人脸特征向量

Through this simple code example, we successfully used Python to write code and connected it to Baidu Face The recognition API implements facial feature analysis. Of course, Baidu face recognition API also provides more functions, such as face comparison, face search, etc., interested readers can further explore and use it.

The above is the detailed content of Write code in Python to implement Baidu face recognition API docking and implement facial feature analysis. For more information, please follow other related articles on the PHP Chinese website!