8215a34d3203f45254b06a63271fe8010d351e6f,UnetTraining.py,,get_training_weights,#,102

Before Change

def get_training_weights(y_train, n_classes):
    weights = []
    for label in range(n_classes):
        weights.append(get_class_weights(y_train[:, label], n_classes=2))
    print("Training weights: {0}".format(weights))
    return np.array(weights)


def get_class_weights(labels_array, n_classes):

After Change

def get_training_weights(training_generator, nb_training_samples, n_classes=2):
    counts = np.zeros((n_labels, n_classes))
    i = 0
    while i < nb_training_samples:
        _, y_train = training_generator.next()
        for label in range(n_labels):
            counts[label, :] += np.bincount(np.array(y_train[:, label].ravel(), dtype=np.uint8), minlength=n_classes)
        i += 1
    return counts_to_weights(counts)


def counts_to_weights(array):

Instances