bd1fa163ba2e3a02da40151c9ab5e498878800e9,riot_neuralnet/data.py,,get_raw_training_labels,#,68

Before Change

        row = prelabels[key]
        numImages = row[0]

        increment = list()
        for j in range(4):
            increment.append((row[2][j] - row[1][j]) / numImages)

        rowLabels = list()

After Change

        time_series = raw_training_labels[time_series_key]
        num_images = time_series[0]
        increment = [(time_series[2][emotion_dimension_idx] - time_series[1][emotion_dimension_idx]) / num_images for emotion_dimension_idx in range(4)]
        labels[time_series_key] = [[increment[label_idx]*image_idx + (time_series[1][label_idx]) for label_idx in range(4)] for image_idx in range(num_images)]

    return labels

Instances