utils.py

### Utils
import h5py
import os

import matplotlib.pyplot as plt
import numpy as np


def load_it_data(path_to_data):
    """ Load IT data

    Args:
        path_to_data (str): Path to the data

    Returns:
        np.array (x6): Stimulus train/val/test; objects list train/val/test; spikes train/val
    """

    datafile = h5py.File(os.path.join(path_to_data,'IT_data.h5'), 'r')

    stimulus_train = datafile['stimulus_train'][()]
    spikes_train = datafile['spikes_train'][()]
    objects_train = datafile['object_train'][()]
    
    stimulus_val = datafile['stimulus_val'][()]
    spikes_val = datafile['spikes_val'][()]
    objects_val = datafile['object_val'][()]
    
    stimulus_test = datafile['stimulus_test'][()]
    objects_test = datafile['object_test'][()]

    ### Decode back object type to latin
    objects_train = [obj_tmp.decode("latin-1") for obj_tmp in objects_train]
    objects_val = [obj_tmp.decode("latin-1") for obj_tmp in objects_val]
    objects_test = [obj_tmp.decode("latin-1") for obj_tmp in objects_test]

    return stimulus_train, stimulus_val, stimulus_test, objects_train, objects_val, objects_test, spikes_train, spikes_val


def visualize_img(stimulus,objects,stim_idx):
    """Visualize image given the stimulus and corresponding index and the object name.

    Args:
        stimulus (array of float): Stimulus containing all the images
        objects (list of str): Object list containing all the names
        stim_idx (int): Index of the stimulus to plot
    """    
    normalize_mean=[0.485, 0.456, 0.406]
    normalize_std=[0.229, 0.224, 0.225]

    img_tmp = np.transpose(stimulus[stim_idx],[1,2,0])

    ### Go back from normalization
    img_tmp = (img_tmp*normalize_std + normalize_mean) * 255

    plt.figure()
    plt.imshow(img_tmp.astype(np.uint8),cmap='gray')
    plt.title(str(objects[stim_idx]))
    plt.show()
    return