convert classes to one-hot

one-hot.py

def toClasses(labels, num_classes):
    sorted = np.sort(np.array(labels, copy=True))
    bsize = math.floor( len(sorted) / num_classes )
    buckets = []
    for i in range(num_classes):        
        buckets.append(sorted[i*bsize])
    print("buckets: " + str(buckets))
    targets = np.digitize(labels, buckets) - 1
    one_hot_targets = np.eye(num_classes)[targets]
    print(one_hot_targets)
    return one_hot_targets