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！！！
一、环境配置
python3.7依赖库:pyjniusjdk18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)
import os
import jnius_config
env = []
jar2classPaths = []
def run():
os.environ['path'] = ';'.join(env)
jnius_config.add_classpath(*jar2classPaths)
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")
import jvm
jvm.env.extend([
r"C:\Program Files\Java\jdk-18\bin\server",
r"E:\projects\Python\tempitem\mada_emotion\lib"])
jvm.jar2classPaths.extend([
r"E:\projects\kotlin\BaiduFaceSDK\bin",
r"E:\projects\Python\tempitem\mada_emotion\lib\opencv-320"])
jvm.run()
api = autoclass("com.jni.face.Face")()
print(api.sdkInit("xxxxx"))
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。
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: ...
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]: ...
from typing import List
class Attribute:
age: int
race: int
emotion: int
glasses: int
gender: int
class CropFaceConf:
isFlat: int
cropSize: int
enlargeRatio: int
class EyeClose:
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:
leftEyeDirection: int
leftEyeConf: float
rightEyeDirection: int
rightEyeConf: float
class HeadPose:
yaw: float
roll: float
pitch: float
class Landmarks:
index: int
size: int
data: List[float]
score: float
class LiveFeatureInfo:
feature: Feature
box: FaceBox
score: float
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
Original: https://blog.csdn.net/LionLone/article/details/123701276
Author: LionLone
Title: Python 人脸离线识别SDK(Baidu)
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