表情识别

表情识别支持7种表情类型，生气、厌恶、恐惧、开心、难过、惊喜、平静等。

实现思路

使用OpenCV识别图片中的脸，在使用keras进行表情识别。

效果预览

实现代码

与《性别识别》相似，本文表情识别也是使用keras实现的，和性别识别相同，型数据使用的是oarriaga/face_classification的，代码如下：

#coding=utf-8

#表情识别

import cv2

from keras.models import load_model

import numpy as np

import chineseText

import datetime

startTime = datetime.datetime.now()

emotion_classifier = load_model(

"classifier/emotion_models/simple_CNN.530-0.65.hdf5")

endTime = datetime.datetime.now()

print(endTime - startTime)

emotion_labels = {

0: "生气",

1: "厌恶",

2: "恐惧",

3: "开心",

4: "难过",

5: "惊喜",

6: "平静"

}

img = cv2.imread("img/emotion/emotion.png")

face_classifier = cv2.CascadeClassifier(

"C:Python36Libsite-packagesopencv-masterdatahaarcascadeshaarcascade_frontalface_default.xml"

)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

faces = face_classifier.detectMultiScale(

gray, scaleFactor=1.2, minNeighbors=3, minSize=(40, 40))

color = (255, 0, 0)

for (x, y, w, h) in faces:

gray_face = gray[(y):(y + h), (x):(x + w)]

gray_face = cv2.resize(gray_face, (48, 48))

gray_face = gray_face / 255.0

gray_face = np.expand_dims(gray_face, 0)

gray_face = np.expand_dims(gray_face, -1)

emotion_label_arg = np.argmax(emotion_classifier.predict(gray_face))

emotion = emotion_labels[emotion_label_arg]

cv2.rectangle(img, (x + 10, y + 10), (x + h - 10, y + w - 10),

(255, 255, 255), 2)

img = chineseText.cv2ImgAddText(img, emotion, x + h * 0.3, y, color, 20)

cv2.imshow("Image", img)

cv2.waitKey(0)

cv2.destroyAllWindows()

以上就是python 实现表情识别的详细内容，更多关于python 表情识别的资料请关注云海天教程其它相关文章！

原文链接：https://github.com/vipstone/faceai/blob/master/doc/emotion.md