import os import sys import cv2 import numpy as np import torch import yaml from torch.utils import data from PIL import Image from torchvision import transforms import util.visda_helper as visda from util.setup import load_args args = load_args(os.getcwd()) paths = args.paths root_dir = paths["data_train_path"] class GTA5Dataset(data.Dataset): def __init__(self, im_size=visda.shape, mode="train"): if mode == "train": self.image_fnlist = glob.glob( os.path.join(root_dir, "images", "*.png")) self.label_fnlist = [ fn.replace("images", "annotations") for fn in self.image_fnlist ] else: self.image_fnlist = glob.glob( os.path.join(root_dir, "eval", "images", "*.png"))
def main(args): config = setup.load_args(os.getcwd()) experiment = get_experiment(args.experiment, config) experiment.train()