fix: Separate to hdf5 script.

tests/data/io/to_hdf5_test.py

@@ -4,7 +4,7 @@
 import unittest
 
 from tests.util import get_test_data
-from vis4d.data.io.hdf5 import convert_dataset
+from vis4d.data.io.to_hdf5 import convert_dataset
 
 
 class TestHDF5(unittest.TestCase):

vis4d/data/io/hdf5.py

@@ -6,12 +6,10 @@
 
 from __future__ import annotations
 
-import argparse
 import os
 from typing import Literal
 
 import numpy as np
-from tqdm import tqdm
 
 from vis4d.common.imports import H5PY_AVAILABLE
 
@@ -242,63 +240,3 @@ def close(self) -> None:
         for client, _ in self.db_cache.values():
             client.close()
         self.db_cache.clear()
-
-
-def convert_dataset(source_dir: str) -> None:
-    """Convert a dataset to HDF5 format.
-
-    This function converts an arbitary dictionary to an HDF5 file. The keys
-    inside the HDF5 file preserve the directory structure of the original.
-
-    As an example, if you convert "/path/to/dataset" to HDF5, the resulting
-    file will be: "/path/to/dataset.hdf5". The file "relative/path/to/file"
-    will be stored at "relative/path/to/file" inside /path/to/dataset.hdf5.
-
-    Args:
-        source_dir (str): The path to the dataset to convert.
-    """
-    if not os.path.exists(source_dir):
-        raise FileNotFoundError(f"No such file or directory: {source_dir}")
-
-    source_dir = os.path.join(source_dir, "")  # must end with trailing slash
-    hdf5_path = source_dir.rstrip("/") + ".hdf5"
-    if os.path.exists(hdf5_path):
-        print(f"File {hdf5_path} already exists! Skipping {source_dir}")
-        return
-
-    print(f"Converting dataset at: {source_dir}")
-    hdf5_file = h5py.File(hdf5_path, mode="w")
-    sub_dirs = list(os.walk(source_dir))
-    file_count = sum(len(files) for (_, _, files) in sub_dirs)
-
-    with tqdm(total=file_count) as pbar:
-        for root, _, files in sub_dirs:
-            g_name = root.replace(source_dir, "")
-            g = hdf5_file.create_group(g_name) if g_name else hdf5_file
-            for f in files:
-                filepath = os.path.join(root, f)
-                if os.path.isfile(filepath):
-                    with open(filepath, "rb") as fp:
-                        file_content = fp.read()
-                    g.create_dataset(
-                        f, data=np.frombuffer(file_content, dtype="uint8")
-                    )
-                pbar.update()
-
-    hdf5_file.close()
-    print("done.")
-
-
-if __name__ == "__main__":  # pragma: no cover
-    parser = argparse.ArgumentParser(
-        description="Converts a dataset at the specified path to hdf5. The "
-        "local directory structure is preserved in the hdf5 file."
-    )
-    parser.add_argument(
-        "-p",
-        "--path",
-        required=True,
-        help="path to the root folder of a specific dataset to convert",
-    )
-    args = parser.parse_args()
-    convert_dataset(args.path)

vis4d/data/io/to_hdf5.py

@@ -0,0 +1,76 @@
+"""Script to convert a dataset to hdf5 format."""
+
+from __future__ import annotations
+
+import argparse
+import os
+
+import numpy as np
+from tqdm import tqdm
+
+from vis4d.common.imports import H5PY_AVAILABLE
+
+if H5PY_AVAILABLE:
+    import h5py
+else:
+    raise ImportError("Please install h5py to enable HDF5Backend.")
+
+
+def convert_dataset(source_dir: str) -> None:
+    """Convert a dataset to HDF5 format.
+
+    This function converts an arbitary dictionary to an HDF5 file. The keys
+    inside the HDF5 file preserve the directory structure of the original.
+
+    As an example, if you convert "/path/to/dataset" to HDF5, the resulting
+    file will be: "/path/to/dataset.hdf5". The file "relative/path/to/file"
+    will be stored at "relative/path/to/file" inside /path/to/dataset.hdf5.
+
+    Args:
+        source_dir (str): The path to the dataset to convert.
+    """
+    if not os.path.exists(source_dir):
+        raise FileNotFoundError(f"No such file or directory: {source_dir}")
+
+    source_dir = os.path.join(source_dir, "")  # must end with trailing slash
+    hdf5_path = source_dir.rstrip("/") + ".hdf5"
+    if os.path.exists(hdf5_path):
+        print(f"File {hdf5_path} already exists! Skipping {source_dir}")
+        return
+
+    print(f"Converting dataset at: {source_dir}")
+    hdf5_file = h5py.File(hdf5_path, mode="w")
+    sub_dirs = list(os.walk(source_dir))
+    file_count = sum(len(files) for (_, _, files) in sub_dirs)
+
+    with tqdm(total=file_count) as pbar:
+        for root, _, files in sub_dirs:
+            g_name = root.replace(source_dir, "")
+            g = hdf5_file.create_group(g_name) if g_name else hdf5_file
+            for f in files:
+                filepath = os.path.join(root, f)
+                if os.path.isfile(filepath):
+                    with open(filepath, "rb") as fp:
+                        file_content = fp.read()
+                    g.create_dataset(
+                        f, data=np.frombuffer(file_content, dtype="uint8")
+                    )
+                pbar.update()
+
+    hdf5_file.close()
+    print("done.")
+
+
+if __name__ == "__main__":  # pragma: no cover
+    parser = argparse.ArgumentParser(
+        description="Converts a dataset at the specified path to hdf5. The "
+        "local directory structure is preserved in the hdf5 file."
+    )
+    parser.add_argument(
+        "-p",
+        "--path",
+        required=True,
+        help="path to the root folder of a specific dataset to convert",
+    )
+    args = parser.parse_args()
+    convert_dataset(args.path)