release code

Dassl.ProGrad.pytorch/dassl/data/datasets/dg/office_home_dg.py

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+import os.path as osp
+
+from ..build import DATASET_REGISTRY
+from .digits_dg import DigitsDG
+from ..base_dataset import DatasetBase
+
+
+@DATASET_REGISTRY.register()
+class OfficeHomeDG(DatasetBase):
+    """Office-Home.
+
+    Statistics:
+        - Around 15,500 images.
+        - 65 classes related to office and home objects.
+        - 4 domains: Art, Clipart, Product, Real World.
+        - URL: http://hemanthdv.org/OfficeHome-Dataset/.
+
+    Reference:
+        - Venkateswara et al. Deep Hashing Network for Unsupervised
+        Domain Adaptation. CVPR 2017.
+    """
+
+    dataset_dir = "office_home_dg"
+    domains = ["art", "clipart", "product", "real_world"]
+    data_url = "https://drive.google.com/uc?id=1gkbf_KaxoBws-GWT3XIPZ7BnkqbAxIFa"
+
+    def __init__(self, cfg):
+        root = osp.abspath(osp.expanduser(cfg.DATASET.ROOT))
+        self.dataset_dir = osp.join(root, self.dataset_dir)
+
+        if not osp.exists(self.dataset_dir):
+            dst = osp.join(root, "office_home_dg.zip")
+            self.download_data(self.data_url, dst, from_gdrive=True)
+
+        self.check_input_domains(
+            cfg.DATASET.SOURCE_DOMAINS, cfg.DATASET.TARGET_DOMAINS
+        )
+
+        train = DigitsDG.read_data(
+            self.dataset_dir, cfg.DATASET.SOURCE_DOMAINS, "train"
+        )
+        val = DigitsDG.read_data(
+            self.dataset_dir, cfg.DATASET.SOURCE_DOMAINS, "val"
+        )
+        test = DigitsDG.read_data(
+            self.dataset_dir, cfg.DATASET.TARGET_DOMAINS, "all"
+        )
+
+        super().__init__(train_x=train, val=val, test=test)