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2025-10-07 22:42:55 +08:00
commit d3ddab7c5d
218 changed files with 125815 additions and 0 deletions
--- a/datasets/eurosat.py
+++ b/datasets/eurosat.py
@@ -0,0 +1,73 @@
+import os
+import pickle
+
+from dassl.data.datasets import DATASET_REGISTRY, Datum, DatasetBase
+from dassl.utils import mkdir_if_missing
+
+from .oxford_pets import OxfordPets
+from .dtd import DescribableTextures as DTD
+
+NEW_CNAMES = {
+    "AnnualCrop": "Annual Crop Land",
+    "Forest": "Forest",
+    "HerbaceousVegetation": "Herbaceous Vegetation Land",
+    "Highway": "Highway or Road",
+    "Industrial": "Industrial Buildings",
+    "Pasture": "Pasture Land",
+    "PermanentCrop": "Permanent Crop Land",
+    "Residential": "Residential Buildings",
+    "River": "River",
+    "SeaLake": "Sea or Lake",
+}
+
+
+@DATASET_REGISTRY.register()
+class EuroSAT(DatasetBase):
+
+    dataset_dir = "eurosat"
+
+    def __init__(self, cfg):
+        root = os.path.abspath(os.path.expanduser(cfg.DATASET.ROOT))
+        self.dataset_dir = os.path.join(root, self.dataset_dir)
+        self.image_dir = os.path.join(self.dataset_dir, "2750")
+        self.split_path = os.path.join(self.dataset_dir, "split_zhou_EuroSAT.json")
+        self.split_fewshot_dir = os.path.join(self.dataset_dir, "split_fewshot")
+        mkdir_if_missing(self.split_fewshot_dir)
+
+        if os.path.exists(self.split_path):
+            train, val, test = OxfordPets.read_split(self.split_path, self.image_dir)
+        else:
+            train, val, test = DTD.read_and_split_data(self.image_dir, new_cnames=NEW_CNAMES)
+            OxfordPets.save_split(train, val, test, self.split_path, self.image_dir)
+
+        num_shots = cfg.DATASET.NUM_SHOTS
+        if num_shots >= 1:
+            seed = cfg.SEED
+            preprocessed = os.path.join(self.split_fewshot_dir, f"shot_{num_shots}-seed_{seed}.pkl")
+            
+            if os.path.exists(preprocessed):
+                print(f"Loading preprocessed few-shot data from {preprocessed}")
+                with open(preprocessed, "rb") as file:
+                    data = pickle.load(file)
+                    train, val = data["train"], data["val"]
+            else:
+                train = self.generate_fewshot_dataset(train, num_shots=num_shots)
+                val = self.generate_fewshot_dataset(val, num_shots=min(num_shots, 4))
+                data = {"train": train, "val": val}
+                print(f"Saving preprocessed few-shot data to {preprocessed}")
+                with open(preprocessed, "wb") as file:
+                    pickle.dump(data, file, protocol=pickle.HIGHEST_PROTOCOL)
+
+        subsample = cfg.DATASET.SUBSAMPLE_CLASSES
+        train, val, test = OxfordPets.subsample_classes(train, val, test, subsample=subsample)
+
+        super().__init__(train_x=train, val=val, test=test)
+
+    def update_classname(self, dataset_old):
+        dataset_new = []
+        for item_old in dataset_old:
+            cname_old = item_old.classname
+            cname_new = NEW_CNAMES[cname_old]
+            item_new = Datum(impath=item_old.impath, label=item_old.label, classname=cname_new)
+            dataset_new.append(item_new)
+        return dataset_new