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()
