utils.py

import numpy as np
import cv2
import matplotlib.pyplot as plt
from config import emotions

def afficher(image):
    if len(image.shape) == 3:
        if image.shape[2] == 3:  # (h,l,3)
            plt.imshow(image)
        elif image.shape[2] == 1:  # (h,l,1)->(h,l)
            image2 = image
            plt.imshow(tf.squeeze(image))
    elif len(image.shape) == 2:  # (h,l)
        plt.imshow(image)


def predir(modele, image):
    # Return output of image from modele
    return modele.predict(np.array([image]))[0, :]


def normAndResize(image, input_shape):
    # For an array image of shape (a,b,c) or (a,b), transform it into (h,l,p). Also normalize it.

    h, l, p = input_shape
    # resize for h and l                                       #
    image = cv2.resize(image, dsize=(h, l), interpolation=cv2.INTER_CUBIC)
    # if we want (h,l,3) -> (h,l,1) , we first transform it in to (h,l) (grey the image)
    if len(image.shape) == 3 and p == 1 and image.shape[2] != 1:
        image = image.mean(2)
    image = np.reshape(image, (h, l, p))  # restore third dimension
    image = image.astype("float32")
    image = (image/127.5)-1  # normalisation

    return image

def emotionToNumber(emotion):
    emotions = ["Angry", "Disgust", "Fear", "Happy", "Sad", "Suprise", "Neutral"]
    return emotions.index(emotion)