Added 'test' split support for Places365 dataset

torchvision/datasets/places365.py

@@ -1,7 +1,7 @@
 import os
 from os import path
 from pathlib import Path
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Union
 from urllib.parse import urljoin
 
 from .folder import default_loader
@@ -15,7 +15,7 @@ class Places365(VisionDataset):
     Args:
         root (str or ``pathlib.Path``): Root directory of the Places365 dataset.
         split (string, optional): The dataset split. Can be one of ``train-standard`` (default), ``train-challenge``,
-            ``val``.
+            ``val``, ``test``.
         small (bool, optional): If ``True``, uses the small images, i.e. resized to 256 x 256 pixels, instead of the
             high resolution ones.
         download (bool, optional): If ``True``, downloads the dataset components and places them in ``root``. Already
@@ -36,7 +36,8 @@ class Places365(VisionDataset):
         RuntimeError: If ``download is False`` and the meta files, i.e. the devkit, are not present or corrupted.
         RuntimeError: If ``download is True`` and the image archive is already extracted.
     """
-    _SPLITS = ("train-standard", "train-challenge", "val")
+
+    _SPLITS = ("train-standard", "train-challenge", "val", "test")
     _BASE_URL = "http://data.csail.mit.edu/places/places365/"
     # {variant: (archive, md5)}
     _DEVKIT_META = {
@@ -50,15 +51,18 @@ class Places365(VisionDataset):
         "train-standard": ("places365_train_standard.txt", "30f37515461640559006b8329efbed1a"),
         "train-challenge": ("places365_train_challenge.txt", "b2931dc997b8c33c27e7329c073a6b57"),
         "val": ("places365_val.txt", "e9f2fd57bfd9d07630173f4e8708e4b1"),
+        "test": ("places365_test.txt", "2fce8233fe493576d724142e45d93653"),
     }
     # {(split, small): (file, md5)}
     _IMAGES_META = {
         ("train-standard", False): ("train_large_places365standard.tar", "67e186b496a84c929568076ed01a8aa1"),
         ("train-challenge", False): ("train_large_places365challenge.tar", "605f18e68e510c82b958664ea134545f"),
         ("val", False): ("val_large.tar", "9b71c4993ad89d2d8bcbdc4aef38042f"),
+        ("test", False): ("test_large.tar", "41a4b6b724b1d2cd862fb3871ed59913"),
         ("train-standard", True): ("train_256_places365standard.tar", "53ca1c756c3d1e7809517cc47c5561c5"),
         ("train-challenge", True): ("train_256_places365challenge.tar", "741915038a5e3471ec7332404dfb64ef"),
         ("val", True): ("val_256.tar", "e27b17d8d44f4af9a78502beb927f808"),
+        ("test", True): ("test_256.tar", "f532f6ad7b582262a2ec8009075e186b"),
     }
 
     def __init__(
@@ -123,10 +127,14 @@ def process(line: str) -> Tuple[str, int]:
 
         return sorted(class_to_idx.keys()), class_to_idx
 
-    def load_file_list(self, download: bool = True) -> Tuple[List[Tuple[str, int]], List[int]]:
-        def process(line: str, sep="/") -> Tuple[str, int]:
-            image, idx = line.split()
-            return path.join(self.images_dir, image.lstrip(sep).replace(sep, os.sep)), int(idx)
+    def load_file_list(
+        self, download: bool = True
+    ) -> Tuple[List[Tuple[str, Union[int, None]]], List[Union[int, None]]]:
+        def process(line: str, sep="/") -> Tuple[str, Union[int, None]]:
+            image, idx = (line.split() + [None])[:2]
+            image = cast(str, image)
+            idx = int(idx) if idx is not None else None
+            return path.join(self.images_dir, image.lstrip(sep).replace(sep, os.sep)), idx
 
         file, md5 = self._FILE_LIST_META[self.split]
         file = path.join(self.root, file)