AAAI Version

AAAI Supplementary Material/Model Training Code/data/counter_animal.py

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+import os
+from loguru import logger
+
+from PIL import Image
+from torch.utils.data import Dataset
+
+
+class CounterAnimal(Dataset):
+    """Dataset to load the CounterAnimal dataset with ImageNet labels."""
+
+    def __init__(self, base_path, mode, transform=None, target_transform=None, train=False):
+        """Create the dataset.
+
+        Args:
+            base_path (str): path to the base folder (the one where the class folders are in)
+            mode (str): mode/variant of the dataset (common/counter)
+            transform: Image augmentation
+            target_transform: label augmentation
+            train: train or test set. Train set is not supported
+        """
+        super().__init__()
+        self.base = base_path
+        assert mode in ["counter", "common"], f"Supported modes are counter and common, but got '{mode}'"
+        assert not train, "CounterAnimal only consists of test data, not training data."
+        self.transform = transform
+        self.target_transform = target_transform
+
+        self.index = []
+        for class_folder in os.listdir(self.base):
+            if not os.path.isdir(os.path.join(self.base, class_folder)):
+                continue
+            # print(f"looking in folder {class_folder}")
+            class_idx = int(class_folder.split(" ")[0])
+            for variant_folder in os.listdir(os.path.join(self.base, class_folder)):
+                # print(f"\tlooking in variant {variant_folder}")
+                if not variant_folder.startswith(mode):
+                    # print("\t\tskip")
+                    continue
+
+                _folder = os.path.join(self.base, class_folder, variant_folder)
+                # print(f"\t\tadding {len(os.listdir(_folder))} files to index")
+                for file in os.listdir(_folder):
+                    if file.lower().split(".")[-1] in ["jpg", "jpeg", "png"]:
+                        self.index.append((os.path.join(_folder, file), class_idx))
+
+        # print(f"loaded {len(self.index)} images into the index: {self.index[:5]}...")
+        assert len(self.index) > 0, "did not find any images :("
+
+    def __len__(self):
+        return len(self.index)
+
+    def __getitem__(self, idx):
+        path, label = self.index[idx]
+
+        img = Image.open(path).convert("RGB")
+
+        if self.transform:
+            img = self.transform(img)
+
+        if self.target_transform:
+            label = self.target_transform(label)
+
+        return img, label