File size: 870 Bytes
872b0a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import numpy as np
import os, sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
import cv2, skimage
import skimage.io
#import scipy.misc as sm
import imageio as sm
# Adopted from https://github.com/mrharicot/monodepth
def compute_errors(gt, pred, nyu=False):
thresh = np.maximum((gt / pred), (pred / gt))
a1 = (thresh < 1.25).mean()
a2 = (thresh < 1.25**2).mean()
a3 = (thresh < 1.25**3).mean()
rmse = (gt - pred)**2
rmse = np.sqrt(rmse.mean())
rmse_log = (np.log(gt) - np.log(pred))**2
rmse_log = np.sqrt(rmse_log.mean())
log10 = np.mean(np.abs((np.log10(gt) - np.log10(pred))))
abs_rel = np.mean(np.abs(gt - pred) / (gt))
sq_rel = np.mean(((gt - pred)**2) / (gt))
if nyu:
return abs_rel, sq_rel, rmse, log10, a1, a2, a3
else:
return abs_rel, sq_rel, rmse, rmse_log, a1, a2, a3
|