Python 人脸离线识别SDK(Baidu)

关注

原创 2022-03-24 07:01:20 3k 阅读 AI 写同款· GEO 优化 ›

几十行代码轻松实现人脸识别、人脸检测人脸识别最近几年变得很火，技术也已经相对成熟，应用场景也很多。下面将介绍简单几种实现人脸检测人脸识别的简单方法我博客中也写了几篇有人脸识别应用的文章现在分类总结下人脸识别技术介绍已经近况以及应用 https://blog.youkuaiyun.com/Nirvana_6174/article/details/84984450 使用Python现有的库 face_recognition fac... 阅读详情

由于本地有一大批数据需要处理，虽然百度开放了在线人脸识别接口，但实际测试，10个QPS+50M上行带宽，仅仅三十多万张图就花了40小时左右, 后面还有大量的视频，抽帧检测更是难搞，因此申请离线识别SDK走起。。。。

狗血的是，百度的人脸识别SDK分为两种，离线采集(仅支持移动端)和离线识别，还有单设备90天和5台设备的限制，（吐槽归吐槽，后面还是得掏钱买的，还TM一百个授权码起购。。。）

到下载页面一看，傻眼了，没有python版本的，只有Java和C++.

我的java就是入了门，直接搞kotlin+Android(当然也是非常烂); C++就更不用说了，就会写个hello world
于是我萌生了一个大胆的想法——python调用Java！！！

正文

一、环境配置

python3.7 依赖库: pyjnius
jdk18 亲测此版本可用

不要问我为什么用这么新的jdk，因为我找不到当时的安装路径了，懒得找了，直接现场下。
python 仅仅需要 pip install pyjnius 即可食用。

二、jnius使用

理论上，应该下载C++版本的，直接编译成dll与python供python调用是最完美的方案，无奈我看不懂。
因此调用流程就是：python 调用 java , java在调用dll，然后再通过java传递给python。
jnius用法很简单，但有点小坑，因此我直接简单封装了个jvm 包，方便以后使用。

如果要修改jvm的封装，请注意: 导入顺序千万不能错，先配置环境变量，再调用jnius_config, 最后再导入autoclass，因为autoclass导入后，虚拟机已经启动了，再配置jnius_config就不生效了(当然也有解决方案，但不做赘述，能跑就行)

# jvm.__init__.py

import os
import jnius_config
env = []
jar2classPaths = []


def run():
    os.environ['path'] = ';'.join(env)
    jnius_config.add_classpath(*jar2classPaths)

# jvm.com.py
# 可以在这个文件中定义一些常用的Java类的映射与类型标注，方便IDE进行代码提示。
from jnius import autoclass


class __System:

    @staticmethod
    def getProperty(key: str) -> str: ...

    @staticmethod
    def loadLibrary(name: str) -> str: ...

    @staticmethod
    def load(path: str) -> str: ...

    class out:
        def println(self, *args): ...


System: __System = autoclass("java.lang.System")

# main.py
# 运行测试
import jvm
# --- jvm初始化 ---
jvm.env.extend([
    r"C:\Program Files\Java\jdk-18\bin\server", # jvm地址
    # 各种dll路径，我将相关的dll全部复制到这个目录了，也可以直接填百度SDK的主目录
    r"E:\projects\Python\tempitem\mada_emotion\lib"])  
jvm.jar2classPaths.extend([
    r"E:\projects\kotlin\BaiduFaceSDK\bin", # java编译后的目录
    # jar包, 如果有其他依赖，继续往这儿加，本质上都是.class文件
    r"E:\projects\Python\tempitem\mada_emotion\lib\opencv-320"]) 
jvm.run()
# --- jvm初始化完成 ---

# 尝试初始化百度SDK的Face类
api = autoclass("com.jni.face.Face")()
print(api.sdkInit("xxxxx")) # 初始化成功返回0

至此，就可以勉强使用了

三、BaiduFaceSDK 封装

可是，作为有强迫症的我，没有代码提示简直没法下手敲，因此，肝了一小时，拿去用吧各位，不用谢。共三个文件，封装成了baiduFaceSDK，后面打包整理传github再更新。

# baiduFaceSDK.__init__.py
from jnius import autoclass
from result import *

class Api:
    def __new__(cls, **kwargs):
        return autoclass("com.jni.face.Face")()

    def __init__(self): ...

    def readImage(self, f: Union[bytes, bytearray]) -> Mat: ...

    def sdkInit(self, modelPath) -> int: ...

    def sdkDestroy(self): ...

    def isAuth(self) -> bool: ...

    def getDeviceId(self) -> str: ...

    def sdkVersion(self) -> str: ...

    def detect(self, addr: int, _type: int) -> detectResult: ...

    def track(self, addr: int, _type: int) -> trackResult: ...

    def clearTrackHistory(self) -> int:

    def faceAttr(self, addr: int) -> faceAttrResult: ...

    def faceEyeClose(self, addr: int) -> faceEyeCloseResult: ...

    def faceGaze(self, addr: int) -> faceGazeResult: ...

    def faceHeadPose(self, addr: int) -> faceHeadPoseResult: ...

    def faceIllumination(self, addr: int) -> List[int]: ...

    def faceBlur(self, addr: int) -> List[float]: ...

    def faceMouthClose(self, addr: int) -> List[float]: ...

    def faceMouthMask(self, addr: int) -> List[float]: ...

    def faceOcclusion(self, addr: int) -> faceOcclusionResult: ...

    def darkEnhance(self, in_addr: int, out_addr: int) -> int: ...

    def faceCrop(self, in_addr: int, out_addr: int) -> int: ...

    def faceBest(self, addr: int) -> List[float]: ...

    def faceLandmark(self, addr: int) -> faceLandmarkResult: ...

    def faceActionLive(self, addr: int, actionType: int, actionResult: List[int]) -> faceActionLiveResult: ...

    def clearActionLiveHistory(self) -> int: ...

    def faceFeature(self, addr: int, _type: int) -> faceFeatureResult: ...

    def livenessFeature(self, addr: int, _type: int) -> livenessFeatureResult: ...

    def match(self, addr1: int, addr2: int, _type: int) -> int: ...

    def compareFeature(self, f1: Feature, f2: Feature, _type: int) -> float: ...

    def rgbLiveness(self, addr: int) -> rgbLivenessResult: ...

    def userAddByMat(self, addr: int, userId: str, groupId: str, userInfo: str) -> str: ...

    def userAdd(self, fea: Feature, userId: str, groupId: str, userInfo: str) -> str: ...

    def userUpdate(self, addr: int, userId: str, groupId: str, userInfo: str) -> str: ...

    def userDelete(self, userId: str, groupId: str) -> str: ...

    def groupAdd(self, groupId: str) -> str: ...

    def groupDelete(self, groupId: str) -> str: ...

    def getUserInfo(self, userId: str, groupId: str) -> str: ...

    def getUserImage(self, out_addr: int, userId: str, groupId: str) -> int: ...

    def getUserList(self, groupId: str, start: int, length: int) -> str: ...

    def getGroupList(self, start: int, length: int) -> str: ...

    def dbFaceCount(self, groupId: str) -> int: ...

    def identifyByMat(self, addr: int, groupIdList: str, userId: str, _type: int)-> str: ...

    def identify(self, fea: Feature, groupIdList: str, userId: str, _type: int) -> str: ...

    def identifyWithAllByMat(self, addr: int, _type: int) -> str: ...

    def identifyWithAll(self, fea: Feature, _type: int) -> str: ...

    def loadDbFace(self) -> bool: ...

# baiduFaceSDK.result.py
# 定义接口的返回值，并做类型标注，即使是列表遍历之后Pycharm也会提示关键字，舒服！！！
from structs import *


class Mat:
    def release(self): ...

    def getNativeObjAddr(self) -> float: ...


class detectResult(list):
    def __getitem__(self, i) -> FaceBox: ...
    def __iter__(self) -> List[FaceBox]: ...


class trackResult(list):
    def __getitem__(self, i) -> TrackFaceInfo: ...
    def __iter__(self) -> List[TrackFaceInfo]: ...


class faceAttrResult(list):
    def __getitem__(self, i) -> Attribute: ...
    def __iter__(self) -> List[Attribute]: ...


class faceEyeCloseResult(list):
    def __getitem__(self, i) -> EyeClose: ...
    def __iter__(self) -> List[EyeClose]: ...


class faceGazeResult(list):
    def __getitem__(self, item) -> GazeInfo: ...
    def __iter__(self) -> List[GazeInfo]: ...


class faceHeadPoseResult(list):
    def __getitem__(self, item) -> HeadPose: ...
    def __iter__(self) -> List[HeadPose]: ...


class faceOcclusionResult(list):
    def __getitem__(self, item) -> Occlusion: ...
    def __iter__(self) -> List[Occlusion]: ...


class faceLandmarkResult(list):
    def __getitem__(self, item) -> Landmarks: ...
    def __iter__(self) -> List[Landmarks]: ...


class faceActionLiveResult(list):
    def __getitem__(self, item) -> FaceBox: ...
    def __iter__(self) -> List[FaceBox]: ...


class faceFeatureResult(list):
    def __getitem__(self, item) -> FeatureInfo: ...
    def __iter__(self) -> List[FeatureInfo]: ...


class livenessFeatureResult(list):
    def __getitem__(self, item) -> LiveFeatureInfo: ...
    def __iter__(self) -> List[LiveFeatureInfo]: ...


class rgbLivenessResult(list):
    def __getitem__(self, item) -> LivenessInfo: ...
    def __iter__(self) -> List[LivenessInfo]: ...

# baiduFaceSDK.structs.py
# 定义的结构体

from typing import List


class Attribute:
    age: int
    race: int  # 0：黄种人 1：白种人 2：黑种人 3：印第安人
    emotion: int  # 0：皱眉 1：笑 2：平静
    glasses: int  # 0：无眼镜 1：有眼镜 2：墨镜
    gender: int  # 0：女性 1：男性


class CropFaceConf:
    isFlat: int  # 是否镜像
    cropSize: int  # 抠图大小
    enlargeRatio: int  # 抠图倍数


class EyeClose:  # 双眼闭合置信度
    leftEyeCloseConf: float
    rightEyeCloseConf: float


class FaceBox:
    index: int
    centerx: float
    centery: float
    width: float
    height: float
    angle: float
    score: float


class Feature:
    size: int
    data: bytes


class FeatureInfo:
    feature: Feature
    face: FaceBox


class GazeInfo:  # 注意力信息
    leftEyeDirection: int  # 左眼凝视方向 0:向上看 1：向下看 2：向右看 3：向左看 4：向前看 5：闭眼
    leftEyeConf: float  # 置信度
    rightEyeDirection: int  # 右眼凝视方向 0:向上看 1：向下看 2：向右看 3：向左看 4：向前看 5：闭眼
    rightEyeConf: float  # 置信度


class HeadPose:
    yaw: float  # 水平转动
    roll: float  # 左右倾斜
    pitch: float  # 抬头低头


class Landmarks:
    index: int  # 关键点索引
    size: int
    data: List[float]  # 关键点数据，144个点，72个x，y坐标
    score: float  # 关键点分值


class LiveFeatureInfo:
    feature: Feature  # 特征值
    box: FaceBox  # 人脸框
    score: float  # 活体分值


class TrackFaceInfo:
    faceId: int
    box: FaceBox
    land: Landmarks


class LivenessInfo:
    trackinfo: TrackFaceInfo
    livescore: float


class Occlusion:
    leftEye: float
    rightEye: float
    nose: float
    mouth: float
    leftCheek: float
    rightCheek: float
    chin: float


class RgbDepthInfo:
    trackinfo: TrackFaceInfo
    rgbscore: float
    depthscore: float