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| import os | |
| from torch.utils.data import Dataset | |
| from src.utils.dataset import read_img_gray | |
| class AachenDataset(Dataset): | |
| def __init__(self, img_path, match_list_path, img_resize=None, down_factor=16): | |
| self.img_path = img_path | |
| self.img_resize = img_resize | |
| self.down_factor = down_factor | |
| with open(match_list_path, "r") as f: | |
| self.raw_pairs = f.readlines() | |
| print("number of matching pairs: ", len(self.raw_pairs)) | |
| def __len__(self): | |
| return len(self.raw_pairs) | |
| def __getitem__(self, idx): | |
| raw_pair = self.raw_pairs[idx] | |
| image_name0, image_name1 = raw_pair.strip("\n").split(" ") | |
| path_img0 = os.path.join(self.img_path, image_name0) | |
| path_img1 = os.path.join(self.img_path, image_name1) | |
| img0, scale0 = read_img_gray( | |
| path_img0, resize=self.img_resize, down_factor=self.down_factor | |
| ) | |
| img1, scale1 = read_img_gray( | |
| path_img1, resize=self.img_resize, down_factor=self.down_factor | |
| ) | |
| return { | |
| "image0": img0, | |
| "image1": img1, | |
| "scale0": scale0, | |
| "scale1": scale1, | |
| "pair_names": (image_name0, image_name1), | |
| "dataset_name": "AachenDayNight", | |
| } | |