一.人脸分析

import requests, base64


def get_access_token():
    url = 'https://aip.baidubce.com/oauth/2.0/token'
    data = {
        'grant_type': 'client_credentials',  # 固定值
        'client_id': 'API Key',  # 在开放平台注册后所建应用的API Key
        'client_secret': 'Secret Key'  # 所建应用的Secret Key
    }
    res = requests.post(url, data=data)
    res = res.json()
    access_token = res['access_token']
    return access_token


def get_json(img):
    access_token=get_access_token()
    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
    file = open(img, 'rb')  # 二进制读取图片
    base64_data = base64.b64encode(file.read())  # 将图片进行base64编码
    base64_code = base64_data.decode()
    params = {
        'image': base64_code,
        'image_type': 'BASE64',
        'face_field': 'age,beauty,expression,face_shape,gender,glasses,landmark,landmark150,quality,eye_status,emotion,face_type,mask,spoofing'
    }
    request_url = request_url + "?access_token=" + access_token
    headers = {'Content-Type': 'application/json'}
    response = requests.post(request_url, data=params, headers=headers)
    if response:
        return response.json()

if __name__ == '__main__':
    img = './img/狗狗.jpg'
    json_data=get_json(img)

返回结果说明

二、人脸对比

import requests, base64


def get_access_token():
    url = 'https://aip.baidubce.com/oauth/2.0/token'
    data = {
        'grant_type': 'client_credentials',  # 固定值
        'client_id': 'API Key',  # 在开放平台注册后所建应用的API Key
        'client_secret': 'Secret Key'  # 所建应用的Secret Key
    }
    res = requests.post(url, data=data)
    res = res.json()
    access_token = res['access_token']
    return access_token

# 根据图片名读取图片，并转换成base64
def read_img(img):
    with open(img, 'rb') as f:
        base64_data = base64.b64encode(f.read())
        base64_code = base64_data.decode()
    return base64_code

def get_json(img1,img2):
    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/match"
    params = [
        {
            "image": img1,
            "image_type": "BASE64",
            "face_type": "LIVE",
            "quality_control": "LOW",
            "liveness_control": "HIGH"
        },
        {
            "image": img2,
            "image_type": "BASE64",
            "face_type": "LIVE",
            "quality_control": "LOW",
            "liveness_control": "HIGH"
        }
    ]
    access_token = get_access_token()
    request_url = request_url + "?access_token=" + access_token
    headers = {'content-type': 'application/json'}
    response = requests.post(request_url, json=params, headers=headers)
    if response:
        return response.json()


if __name__ == '__main__':
    img1 = read_img('img/mm2.jpeg')
    img2 = read_img('img/mjl.jpg')
    json_data=get_json(img1,img2)
    print(json_data)
    if json_data['error_msg'] == 'SUCCESS':
        score = json_data['result']['score']

        if score > 80:
            print("照片相似度为：" + str(score) + "基本确定是本人")
        else:
            print("照片相似度为：" + str(score) + "基本确定不是本人")
        print(score)
    else:
        print('错误信息：', json_data['error_msg'])

返回结果说明

三、人脸融合

import requests
import base64
import json



# 获取token
def get_access_token():
    url = 'https://aip.baidubce.com/oauth/2.0/token'
    data = {
        'grant_type': 'client_credentials',  # 固定值
        'client_id': 'API Key',  # 在开放平台注册后所建应用的API Key
        'client_secret': 'Secret Key'  # 所建应用的Secret Key
    }
    res = requests.post(url, data=data)
    res = res.json()
    access_token = res['access_token']
    return access_token


# 根据图片名读取图片，并转换成base64
def read_photo(name):
    with open(name, 'rb') as f:
        base64_data = base64.b64encode(f.read())
        base64_code = base64_data.decode()
    return base64_code


# 调用百度的接口，实现融合图片
def face_fusion(template, target):
    access_token = get_access_token()
    url = 'https://aip.baidubce.com/rest/2.0/face/v1/merge'
    request_url = url + '?access_token=' + access_token
    params = {
        "image_template": {
            "image": template,
            "image_type": "BASE64",
            "quality_control": "NONE"
        },
        "image_target": {
            "image": target,
            "image_type": "BASE64",
            "quality_control": "NONE"
        },
        "merge_degree": "NORMAL"
    }
    params = json.dumps(params)
    headers = {'content-type': 'application/json'}
    result = requests.post(request_url, data=params, headers=headers).json()
    if result['error_code'] == 0:
        res = result["result"]["merge_image"]
        down_photo(res)
    else:
        print(str(result['error_code'])+result['error_msg'])

# 下载融合后图片
def down_photo(data):
    imagedata = base64.b64decode(data)
    file = open('./result.jpg', "wb")
    file.write(imagedata)

# 主程序
if __name__ == '__main__':
    template = read_photo('img/狗狗.jpg')
    target = read_photo('img/毛毛.jpeg')
    face_fusion(template, target)

返回结果说明

四、人像动漫化

import requests, base64


# 百度AI开放平台鉴权函数
def get_access_token():
    url = 'https://aip.baidubce.com/oauth/2.0/token'
    data = {
        'grant_type': 'client_credentials',  # 固定值
        'client_id': 'API Key',  # 在开放平台注册后所建应用的API Key
        'client_secret': 'Secret Key'  # 所建应用的Secret Key
    }
    res = requests.post(url, data=data)
    res = res.json()
    access_token = res['access_token']
    return access_token


def image_process(img_before, img_after, how_to_deal):
    # 函数的三个参数，一个是转化前的文件名，一个是转化后的文件名，均在同一目录下，第三个是图像处理能力选择
    request_url = 'https://aip.baidubce.com/rest/2.0/image-process/v1/' + how_to_deal
    if how_to_deal == 'style_trans':  # 判断如果是 图像风格化，需要额外添加一个风格配置
        others = 'cartoon'  # 风格化参数，具体可设置范围参见下面注释
        '''
        cartoon：卡通画风格
        pencil：铅笔风格
        color_pencil：彩色铅笔画风格
        warm：彩色糖块油画风格
        wave：神奈川冲浪里油画风格
        lavender：薰衣草油画风格
        mononoke：奇异油画风格
        scream：呐喊油画风格
        gothic：哥特油画风格
        '''
    else:
        others = ''

    file = open(img_before, 'rb')  # 二进制读取图片
    origin_img = base64.b64encode(file.read())  # 将图片进行base64编码
    headers = {'Content-Type': 'application/x-www-form-urlencoded'}
    data = {
        'access_token': get_access_token(),
        'image': origin_img,
        "type":'anime_mask',
        "mask_id":"2"
    }

    res = requests.post(request_url, data=data, headers=headers)

    res = res.json()
    print(res)
    if res:
        f = open(img_after, 'wb')
        after_img = res['image']
        after_img = base64.b64decode(after_img)
        f.write(after_img)
        f.close()


if __name__ == '__main__':
    img_before = 'img/mm1.jpg'  # 当前目录下的图片
    img_after = img_before.split('.')  # 将原文件名分成列表
    img_after = img_after[0] + '_2.' + img_after[1]  # 新生成的文件名为原文件名上加 _1

    image_process(img_before, img_after, 'selfie_anime')
    # 第三个参数： selfie_anime 为人像动漫化，colourize 图像上色，style_trans 为图像风格化
    print('done!')

返回结果说明