| import pandas as pd | |
| import cv2 | |
| import numpy as np | |
| dataset_path = 'fer2013/fer2013/fer2013.csv' | |
| image_size=(48,48) | |
| def load_fer2013(): | |
| data = pd.read_csv(dataset_path) | |
| pixels = data['pixels'].tolist() | |
| width, height = 48, 48 | |
| faces = [] | |
| for pixel_sequence in pixels: | |
| face = [int(pixel) for pixel in pixel_sequence.split(' ')] | |
| face = np.asarray(face).reshape(width, height) | |
| face = cv2.resize(face.astype('uint8'),image_size) | |
| faces.append(face.astype('float32')) | |
| faces = np.asarray(faces) | |
| faces = np.expand_dims(faces, -1) | |
| emotions = pd.get_dummies(data['emotion']).as_matrix() | |
| return faces, emotions | |
| def preprocess_input(x, v2=True): | |
| x = x.astype('float32') | |
| x = x / 255.0 | |
| if v2: | |
| x = x - 0.5 | |
| x = x * 2.0 | |
| return x |