refactor

objaverse_xl/__init__.py

@@ -1,150 +1 @@
-import multiprocessing
-import os
-import uuid
-from functools import partial
-from multiprocessing import Pool
-from typing import Dict, List, Optional
-
-import fsspec
-import pandas as pd
-import requests
-from loguru import logger
-from tqdm import tqdm
-
-
-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.
-            Supports all file systems supported by fsspec. Defaults to
-            "~/.objaverse-xl".
-
-    Returns:
-        pd.DataFrame: Smithsonian Object Metadata dataset as a Pandas DataFrame with
-            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"))
-    filename = os.path.join(dirname, "object-metadata.parquet")
-    fs, path = fsspec.core.url_to_fs(filename)
-    if fs.protocol == "file":
-        os.makedirs(dirname, exist_ok=True)
-
-    if fs.exists(filename):
-        df = pd.read_parquet(filename)
-        return df
-    else:
-        url = "https://huggingface.co/datasets/allenai/objaverse-xl/resolve/main/smithsonian/object-metadata.parquet"
-        response = requests.get(url)
-        response.raise_for_status()
-        with fs.open(filename, "wb") as file:
-            file.write(response.content)
-        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.
-            Supports all file systems supported by fsspec. 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"))
-    filename = os.path.join(dirname, f"{uid}.glb")
-    fs, path = fsspec.core.url_to_fs(filename)
-    if fs.protocol == "file":
-        os.makedirs(dirname, exist_ok=True)
-
-    if not fs.exists(filename):
-        tmp_path = os.path.join(dirname, f"{uid}.glb.tmp")
-        response = requests.get(url)
-
-        # check if the path is valid
-        if response.status_code == 404:
-            logger.warning(f"404 for {url}")
-            return None
-
-        # write to tmp path
-        with fs.open(tmp_path, "wb") as file:
-            for chunk in response.iter_content(chunk_size=8192):
-                file.write(chunk)
-
-        # rename to final path
-        fs.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.
-            Supports all file systems supported by fsspec. 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
+from smithsonian import download_smithsonian_objects, load_smithsonian_metadata

objaverse_xl/smithsonian.py

@@ -0,0 +1,138 @@
+import multiprocessing
+import os
+import uuid
+from functools import partial
+from multiprocessing import Pool
+from typing import Dict, List, Optional
+
+import fsspec
+import pandas as pd
+import requests
+from loguru import logger
+from tqdm import tqdm
+from utils import get_uid_from_str
+
+
+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.
+            Supports all file systems supported by fsspec. Defaults to
+            "~/.objaverse-xl".
+
+    Returns:
+        pd.DataFrame: Smithsonian Object Metadata dataset as a Pandas DataFrame with
+            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"))
+    filename = os.path.join(dirname, "object-metadata.parquet")
+    fs, path = fsspec.core.url_to_fs(filename)
+    if fs.protocol == "file":
+        os.makedirs(dirname, exist_ok=True)
+
+    if fs.exists(filename):
+        df = pd.read_parquet(filename)
+        return df
+    else:
+        url = "https://huggingface.co/datasets/allenai/objaverse-xl/resolve/main/smithsonian/object-metadata.parquet"
+        response = requests.get(url)
+        response.raise_for_status()
+        with fs.open(filename, "wb") as file:
+            file.write(response.content)
+        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.
+            Supports all file systems supported by fsspec. 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"))
+    filename = os.path.join(dirname, f"{uid}.glb")
+    fs, path = fsspec.core.url_to_fs(filename)
+    if fs.protocol == "file":
+        os.makedirs(dirname, exist_ok=True)
+
+    if not fs.exists(filename):
+        tmp_path = os.path.join(dirname, f"{uid}.glb.tmp")
+        response = requests.get(url)
+
+        # check if the path is valid
+        if response.status_code == 404:
+            logger.warning(f"404 for {url}")
+            return None
+
+        # write to tmp path
+        with fs.open(tmp_path, "wb") as file:
+            for chunk in response.iter_content(chunk_size=8192):
+                file.write(chunk)
+
+        # rename to final path
+        fs.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.
+            Supports all file systems supported by fsspec. 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

objaverse_xl/utils.py

@@ -0,0 +1,14 @@
+import uuid
+
+
+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))

requirements.txt

@@ -3,4 +3,4 @@ pandas
 pyarrow
 tqdm
 loguru
-fsspec==2022.11.0
+fsspec>=2022.11.0