zachguo

from sklearn.metrics import confusion_matrix

def print_cm(cm, labels, hide_zeroes=False, hide_diagonal=False, hide_threshold=None):
    """pretty print for confusion matrixes"""
    columnwidth = max([len(x) for x in labels]+[5]) # 5 is value length
    empty_cell = " " * columnwidth
    # Print header
    print "    " + empty_cell,
    for label in labels: 
        print "%{0}s".format(columnwidth) % label,

chpatrick

import numpy as np
import re
import sys

'''
Load a PFM file into a Numpy array. Note that it will have
a shape of H x W, not W x H. Returns a tuple containing the
loaded image and the scale factor from the file.
'''
def load_pfm(file):