Python-卷积神经网络实现人脸检测以及情绪识别

# Face and Emotion Recognition This software recognizes person's faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV, Dlib, face_recognition and Deep Learning. ## Demo  ## Dependencies - Opencv - Cmake - Dlib - Keras Note : If you are facing issues installing dlib in your system then use google collab its comes as pre-installed. ## Usage <!-- - Download a `shape_predictor_68_face_landmarks.dat` file from [here](https://drive.google.com/open?id=1hyDn8eJ5yaTVkMgdKGmoFIn48zwdvIkg) and put in the folder. --> - `test` folder contain images or video that we will feed to the model. - `images` folder contain only images of person face to perform face recognition. - `models` contain the pre-trained model for emotion classifier. - `emotion.py` can to run to classify emotions of person's face. - `face-rec-emotion.py` can recognise faces and classify emotion at a time. - face_recognition library uses the FaceNet Implementation for face recognition.For more details please visit `python emotion.py` `python face-rec-emotion.py` ## To train new models for emotion classification - Download the fer2013.tar.gz file from [here](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data) - Move the downloaded file to the datasets directory inside this repository. - Untar the file: `tar -xzf fer2013.tar` - Download train_emotion_classifier.py from orriaga's repo [here] - Run the train_emotion_classification.py file: `python train_emotion_classifier.py` ## Deep Learning Model  ## Credit * Computer vision powered by OpenCV. * Neural network scaffolding powered by Keras with Tensorflow. * FaceNet [Research Paper](https://arxiv.org/pdf/1503.03832.pdf) * Convolutional Neural Network (CNN) deep learning architecture is from this [research paper]