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data/lmdbify.py

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+import torch
+import lmdb
+import os
+import pickle
+from io import BytesIO
+from data.dataset import CARS, ImprovedImageFolder
+import torchvision
+from tqdm import tqdm
+
+
+def dataset_to_lmdb(dataset, lmdb_path):
+    env = lmdb.open(lmdb_path, map_size=1099511627776 * 2, subdir=os.path.isdir(lmdb_path))
+    with env.begin(write=True) as txn:
+        for i in tqdm(range(len(dataset))):
+            buffer = BytesIO()
+            torch.save(dataset[i], buffer)
+            txn.put("{}".format(i).encode(), buffer.getvalue())
+        txn.put(b"classes_list", pickle.dumps(dataset.classes_list))
+        txn.put(b"__len__", pickle.dumps(len(dataset)))
+
+
+def main():
+    data_transform = torchvision.transforms.Compose([
+        torchvision.transforms.Resize([int(224 * 1.15), int(224 * 1.15)]),
+        torchvision.transforms.CenterCrop(224),
+        torchvision.transforms.ToTensor(),
+        torchvision.transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+    ])
+    origin_dataset = ImprovedImageFolder("/data/few-shot/CUB_200_2011/CUB_200_2011/images", transform=data_transform)
+    dataset_to_lmdb(origin_dataset, "/data/few-shot/lmdb/CUB_200_2011/data.lmdb")
+
+
+if __name__ == '__main__':
+    main()
+