ranftlr

import torch
import cv2
import h5py
import numpy as np

from scipy.io import loadmat

import torch.utils.data as data
import torch.nn.functional as F
from torchvision.transforms import Compose

ranftlr

def trimmed_mae_loss(prediction, target, mask, trim=0.2):
    M = torch.sum(mask, (1, 2))
    res = prediction - target

    res = res[mask.bool()].abs()

    trimmed, _ = torch.sort(res.view(-1), descending=False)[
        : int(len(res) * (1.0 - trim))
    ]

ranftlr

import torch
import glob
import numpy as np
import imageio
import cv2

import torch.utils.data as data
import torch.nn.functional as F
from torchvision.transforms import Compose