| import numpy as np |
| import os, sys |
| sys.path.append(os.path.dirname(os.path.abspath(__file__))) |
| import cv2, skimage |
| import skimage.io |
| |
| import imageio as sm |
|
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| |
| 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 |
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|
