人脸描点检测

.settings/org.eclipse.core.resources.prefs

@@ -12,6 +12,7 @@ encoding//QGraphicsView\u7EC3\u4E60/\u6DFB\u52A0QWidget.py=utf-8
 encoding//tmp/\u622A\u56FE\u753B\u77E9\u5F62/DrawRectangle.py=utf-8
 encoding//tmp/\u7B80\u5355\u63D2\u4EF6/Widget.py=utf-8
 encoding//\u4E0B\u62C9\u9009\u62E9\u8054\u52A8/ComboBox.py=utf-8
+encoding//\u4EBA\u8138\u63CF\u70B9\u68C0\u6D4B/OpencvWidget.py=utf-8
 encoding//\u5168\u5C40\u70ED\u952E/HotKey.py=utf-8
 encoding//\u56FE\u7247\u52A0\u8F7D/LoadImage.py=utf-8
 encoding//\u56FE\u7247\u52A0\u8F7D/res_rc.py=utf-8

README.md

@@ -20,6 +20,7 @@
  - [1.15 气泡提示](气泡提示/)
  - [1.16 自定义import](自定义import/)
  - [1.17 下拉选择联动](下拉选择联动/)
+ - [1.18 人脸描点检测](人脸描点检测/)
 
 ### [2.QGraphicsView练习](QGraphicsView练习/)
  - [2.1 世界地图](QGraphicsView练习/世界地图)

人脸描点检测/OpencvWidget.py

@@ -0,0 +1,113 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+'''
+Created on 2018年1月29日
+@author: Irony."[讽刺]
+@site: http://alyl.vip, http://orzorz.vip, https://coding.net/u/892768447, https://github.com/892768447
+@email: 892768447@qq.com
+@file: OpencvWidget
+@description: 
+'''
+import sys
+
+from PyQt5.QtCore import QTimer
+from PyQt5.QtGui import QImage, QPixmap
+from PyQt5.QtWidgets import QLabel, QMessageBox, QApplication
+import cv2  # @UnresolvedImport
+import dlib
+import numpy
+
+
+__Author__ = "By: Irony.\"[讽刺]\nQQ: 892768447\nEmail: 892768447@qq.com"
+__Copyright__ = "Copyright (c) 2018 Irony.\"[讽刺]"
+__Version__ = "Version 1.0"
+
+DOWNSCALE = 4
+
+
+class OpencvWidget(QLabel):
+
+    def __init__(self, *args, **kwargs):
+        super(OpencvWidget, self).__init__(*args, **kwargs)
+        self.fps = 24
+        self.resize(800, 600)
+        self.setText("请稍候，正在初始化数据和摄像头。。。")
+
+    def start(self):
+        try:
+            # 检测相关
+            self.detector = dlib.get_frontal_face_detector()
+            self.predictor = dlib.shape_predictor(
+                "data/shape_predictor_68_face_landmarks.dat")
+            cascade_fn = "data/lbpcascades/lbpcascade_frontalface.xml"
+            self.cascade = cv2.CascadeClassifier(cascade_fn)
+            if not self.cascade:
+                return QMessageBox.critical(self, "错误", cascade_fn + " 无法找到")
+            self.cap = cv2.VideoCapture(0)
+            if not self.cap or not self.cap.isOpened():
+                return QMessageBox.critical(self, "错误", "打开摄像头失败")
+            # 开启定时器定时捕获
+            self.timer = QTimer(self, timeout=self.onCapture)
+            self.timer.start(1000 / self.fps)
+        except Exception as e:
+            QMessageBox.critical(self, "错误", str(e))
+
+    def closeEvent(self, event):
+        if hasattr(self, "timer"):
+            self.timer.stop()
+            self.timer.deleteLater()
+            self.cap.release()
+            del self.predictor, self.detector, self.cascade, self.cap
+        super(OpencvWidget, self).closeEvent(event)
+        self.deleteLater()
+
+    def onCapture(self):
+        _, frame = self.cap.read()
+
+        minisize = (
+            int(frame.shape[1] / DOWNSCALE), int(frame.shape[0] / DOWNSCALE))
+        tmpframe = cv2.resize(frame, minisize)
+        tmpframe = cv2.cvtColor(tmpframe, cv2.COLOR_BGR2GRAY)  # 做灰度处理
+        tmpframe = cv2.equalizeHist(tmpframe)
+
+        # minNeighbors表示每一个目标至少要被检测到5次
+        faces = self.cascade.detectMultiScale(tmpframe, minNeighbors=5)
+        del tmpframe
+        if len(faces) < 1:  # 没有检测到脸
+            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            img = QImage(
+                frame.data, frame.shape[1], frame.shape[0], frame.shape[1] * 3, QImage.Format_RGB888)
+            del frame
+            return self.setPixmap(QPixmap.fromImage(img))
+        # 特征点检测描绘
+        for x, y, w, h in faces:
+            x, y, w, h = x * DOWNSCALE, y * DOWNSCALE, w * DOWNSCALE, h * DOWNSCALE
+            # 画脸矩形
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0))
+            # 截取的人脸部分
+            tmpframe = frame[y:y + h, x:x + w]
+            # 进行特征点描绘
+            rects = self.detector(tmpframe, 1)
+            if len(rects) > 0:
+                landmarks = numpy.matrix(
+                    [[p.x, p.y] for p in self.predictor(tmpframe, rects[0]).parts()])
+                for _, point in enumerate(landmarks):
+                    pos = (point[0, 0] + x, point[0, 1] + y)
+                    # 在原来画面上画点
+                    cv2.circle(frame, pos, 3, color=(0, 255, 0))
+            # 转成Qt能显示的
+            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            img = QImage(
+                frame.data, frame.shape[1], frame.shape[0], frame.shape[1] * 3, QImage.Format_RGB888)
+            del frame
+            self.setPixmap(QPixmap.fromImage(img))
+
+
+if __name__ == "__main__":
+    app = QApplication(sys.argv)
+    w = OpencvWidget()
+    w.show()
+    # 5秒后启动
+    QTimer.singleShot(5000, w.start)
+    sys.exit(app.exec_())

人脸描点检测/README.md

@@ -0,0 +1,16 @@
+# Opencv 人脸描点检测
+
+简单联系PyQt 结合 Opencv 进行人脸检测
+
+### 依赖文件
+ - [opencv](https://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv)
+ - [numpy](https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy)
+ - [dlib](http://dlib.net/)
+  - [dlib-19.4.0.win32-py2.7.exe](dist/dlib-19.4.0.win32-py2.7.exe)
+  - [dlib-19.4.0.win32-py3.4.exe](dist/dlib-19.4.0.win32-py3.4.exe)
+  - [dlib-19.4.0.win32-py3.5.exe](dist/dlib-19.4.0.win32-py3.5.exe)
+ - [shape-predictor-68-face-landmarks.dat.bz2](http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2)
+
+截图
+
+![1](ScreenShot/1.png)

人脸描点检测/data/.gitignore

@@ -0,0 +1 @@
+/shape_predictor_68_face_landmarks.dat

人脸描点检测/data/readme.txt

@@ -0,0 +1,7 @@
+This folder contains various data that is used by cv libraries and/or demo applications.
+----------------------------------------------------------------------------------------
+
+haarcascades - the folder contains trained classifiers for detecting objects
+               of a particular type, e.g. faces (frontal, profile), pedestrians etc.
+               Some of the classifiers have a special license - please,
+               look into the files for details.