add updated smithsonian support

objaverse_xl/__init__.py

@@ -1,22 +1,42 @@
+import multiprocessing
 import os
+import uuid
+from functools import partial
+from multiprocessing import Pool
+from typing import Dict, List, Optional
 
 import pandas as pd
 import requests
+from loguru import logger
+from tqdm import tqdm
 
 
-def load_smithsonian_df(
-    download_dir: str = "~/.objaverse_xl",
+def get_uid_from_str(string: str) -> str:
+    """Generates a UUID from a string.
+
+    Args:
+        string (str): String to generate a UUID from.
+
+    Returns:
+        str: UUID generated from the string.
+    """
+    namespace = uuid.NAMESPACE_DNS
+    return str(uuid.uuid5(namespace, string))
+
+
+def load_smithsonian_metadata(
+    download_dir: str = "~/.objaverse-xl",
 ) -> pd.DataFrame:
     """Loads the Smithsonian Object Metadata dataset as a Pandas DataFrame.
 
     Args:
         download_dir (str, optional): Directory to download the parquet metadata file.
-            Defaults to "~/.objaverse_xl".
+            Defaults to "~/.objaverse-xl".
 
     Returns:
         pd.DataFrame: Smithsonian Object Metadata dataset as a Pandas DataFrame with
-            columns for the object "title", "url", "quality", and "file_type".
-            The quality is always Medium and the file_type is always glb.
+            columns for the object "title", "url", "quality", "file_type", "uid", and
+            "license". The quality is always Medium and the file_type is always glb.
     """
     dirname = os.path.expanduser(os.path.join(download_dir, "smithsonian"))
     os.makedirs(dirname, exist_ok=True)
@@ -28,4 +48,86 @@ def load_smithsonian_df(
     with open(filename, "wb") as file:
         file.write(response.content)
 
-    return pd.read_parquet(filename)
+    df = pd.read_parquet(filename)
+    df["uid"] = df["url"].apply(get_uid_from_str)
+    df["license"] = "CC0"
+    return df
+
+
+def download_smithsonian_object(url: str, download_dir: str = "~/.objaverse-xl") -> str:
+    """Downloads a Smithsonian Object from a URL.
+
+    Args:
+        url (str): URL to download the Smithsonian Object from.
+        download_dir (str, optional): Directory to download the Smithsonian Object to.
+            Defaults to "~/.objaverse-xl".
+
+    Returns:
+        str: Path to the downloaded Smithsonian Object.
+    """
+    uid = get_uid_from_str(url)
+
+    dirname = os.path.expanduser(os.path.join(download_dir, "smithsonian", "objects"))
+    os.makedirs(dirname, exist_ok=True)
+    filename = os.path.join(dirname, f"{uid}.glb")
+
+    if os.path.exists(filename):
+        return filename
+
+    tmp_path = os.path.join(dirname, f"{uid}.glb.tmp")
+    response = requests.get(url)
+    if response.status_code == 404:
+        logger.warning(f"404 for {url}")
+        return None
+    with open(tmp_path, "wb") as file:
+        for chunk in response.iter_content(chunk_size=8192):
+            file.write(chunk)
+    os.rename(tmp_path, filename)
+
+    return filename
+
+
+def download_smithsonian_objects(
+    urls: Optional[str] = None,
+    processes: Optional[int] = None,
+    download_dir: str = "~/.objaverse-xl",
+) -> List[Dict[str, str]]:
+    """Downloads all Smithsonian Objects.
+
+    Args:
+        urls (Optional[str], optional): List of URLs to download the Smithsonian Objects
+            from. If None, all Smithsonian Objects will be downloaded. Defaults to None.
+        processes (Optional[int], optional): Number of processes to use for downloading
+            the Smithsonian Objects. If None, the number of processes will be set to the
+            number of CPUs on the machine (multiprocessing.cpu_count()). Defaults to None.
+        download_dir (str, optional): Directory to download the Smithsonian Objects to.
+            Defaults to "~/.objaverse-xl".
+
+    Returns:
+        List[Dict[str, str]]: List of dictionaries with keys "download_path" and "url"
+            for each downloaded object.
+    """
+    if processes is None:
+        processes = multiprocessing.cpu_count()
+    if urls is None:
+        df = load_smithsonian_metadata(download_dir=download_dir)
+        urls = df["url"].tolist()
+
+    logger.info(f"Downloading {len(urls)} Smithsonian Objects with {processes=}")
+    with Pool(processes=processes) as pool:
+        results = list(
+            tqdm(
+                pool.imap_unordered(
+                    partial(download_smithsonian_object, download_dir=download_dir),
+                    urls,
+                ),
+                total=len(urls),
+                desc="Downloading Smithsonian Objects",
+            )
+        )
+    out = [
+        {"download_path": download_path, "url": url}
+        for download_path, url in zip(results, urls)
+        if download_path is not None
+    ]
+    return out

requirements.txt

@@ -1,2 +1,5 @@
+requests
 pandas
-pyarrow
+pyarrow
+tqdm
+loguru