feat: add swc convert example

Author: seankmartin

README.md

@@ -40,4 +40,10 @@ cd tests
 jest MATCH --config=jest.config.js
 ```
 
-where `MATCH` is a substring of the test name.
+where `MATCH` is a substring of the test name.
+
+### Running local server
+
+```
+npx http-server FOLDER_WITH_DATA/ --cors=authorization
+```

examples/convert_swc.py

@@ -0,0 +1,96 @@
+# See https://github.com/seung-lab/cloud-volume/issues/412
+import json
+
+from cloudvolume import Skeleton
+from cloudvolume import CloudVolume
+from pathlib import Path
+from cryoet_data_portal_neuroglancer.models.json_generator import (
+    SegmentPropertyJSONGenerator,
+)
+
+
+def open_swc(swc_path):
+    with open(swc_path, "r") as f:
+        data = f.read()
+    skeleton = Skeleton.from_swc(data)
+
+    return skeleton
+
+
+def save_swc(skeleton, output_path, id):
+    info = {
+        "@type": "neuroglancer_skeletons",
+        "transform": [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0],
+        # "vertex_attributes": [
+        #     {"id": "radius", "data_type": "float32", "num_components": 1}
+        # ],
+        "scales": [
+            {
+                "chunk_sizes": [
+                    [256, 256, 256]
+                ],  # information required by neuroglancer but not used
+                "key": "data",
+                "resolution": [1, 1, 1],
+                "size": [1024, 1024, 1024],
+            },
+        ],
+        "segment_properties": "props",
+    }
+
+    skeleton.id = id
+    cv = CloudVolume(f"file://{str(output_path)}", info=info, compress=False)
+    cv.skeleton.meta.info = info
+    cv.skeleton.meta.commit_info()
+    cv.skeleton.upload(skeleton)
+
+
+def generate_properties(output_path, ids, labels):
+    output_path = Path(output_path)
+    output_path.mkdir(parents=True, exist_ok=True)
+    generator = SegmentPropertyJSONGenerator(
+        ids=ids,
+        labels=labels,
+    )
+    json_res = generator.generate_json()
+    print(f"Generated properties for {len(ids)} segments.")
+    output_file = output_path / "info"
+    output_file.write_text(json.dumps(json_res, indent=2))
+
+
+def main(output_path, input_folder):
+    output_path = Path(output_path)
+    output_path.mkdir(parents=True, exist_ok=True)
+    input_folder = Path(input_folder)
+    ids = []
+    labels = []
+    for swc_file in input_folder.glob("*.swc"):
+        print(f"Processing {swc_file}")
+        skeleton = open_swc(swc_file)
+        id_string = swc_file.stem.split("_")[-1]
+        id_ = int(id_string)
+        rest = swc_file.stem[: -len(id_string) - 1]
+        label = rest.replace("[", "")
+        label = label.replace("]", "")
+        label = label.strip()
+        ids.append(id_)
+        labels.append(label)
+        save_swc(skeleton, output_path, id_)
+        print(f"Saved skeleton with ID {id_} to {output_path}")
+    generate_properties(output_path / "skeletons" / "props", ids, labels)
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(
+        description="Convert SWC files to CloudVolume format."
+    )
+    parser.add_argument(
+        "output_path", type=str, help="Path to the output CloudVolume directory."
+    )
+    parser.add_argument(
+        "input_folder", type=str, help="Path to the folder containing SWC files."
+    )
+
+    args = parser.parse_args()
+    main(args.output_path, args.input_folder)