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"""Script to download 3D objects from the Smithsonian Institution."""
import multiprocessing
import os
from multiprocessing import Pool
from typing import Dict, Optional, Tuple, Callable
import tempfile
import fsspec
import pandas as pd
import requests
from loguru import logger
from tqdm import tqdm
from objaverse_xl.utils import get_uid_from_str, get_file_hash
from objaverse_xl.abstract import ObjaverseSource
class SmithsonianDownloader(ObjaverseSource):
"""Script to download objects from the Smithsonian Institute."""
def get_annotations(self, download_dir: str = "~/.objaverse") -> 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".
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.
"""
filename = os.path.join(download_dir, "smithsonian", "object-metadata.parquet")
fs, path = fsspec.core.url_to_fs(filename)
fs.makedirs(os.path.dirname(path), exist_ok=True)
# download the parquet file if it doesn't exist
if not fs.exists(path):
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(path, "wb") as file:
file.write(response.content)
# load the parquet file with fsspec
with fs.open(path) as f:
df = pd.read_parquet(f)
return df
def _download_smithsonian_object(
self,
file_identifier: str,
download_dir: Optional[str],
expected_sha256: str,
handle_found_object: Optional[Callable],
handle_modified_object: Optional[Callable],
handle_missing_object: Optional[Callable],
) -> Tuple[str, Optional[str]]:
"""Downloads a Smithsonian Object from a URL.
Overwrites the file if it already exists and assumes this was previous checked.
Args:
file_identifier (str): URL to download the Smithsonian Object from.
download_dir (Optional[str]): Directory to download the Smithsonian Object
to. Supports all file systems supported by fsspec. If None, the
Smithsonian Object will be deleted after it is downloaded and processed
with the handler functions.
expected_sha256 (str): The expected SHA256 of the contents of the downloaded
object.
handle_found_object (Optional[Callable]): Called when an object is
successfully found and downloaded. Here, the object has the same sha256
as the one that was downloaded with Objaverse-XL. If None, the object
will be downloaded, but nothing will be done with it. Args for the
function include:
- local_path (str): Local path to the downloaded 3D object.
- file_identifier (str): File identifier of the 3D object.
- sha256 (str): SHA256 of the contents of the 3D object.
- metadata (Dict[str, Any]): Metadata about the 3D object, including the
GitHub organization and repo names.
Return is not used.
handle_modified_object (Optional[Callable]): Called when a modified object
is found and downloaded. Here, the object is successfully downloaded,
but it has a different sha256 than the one that was downloaded with
Objaverse-XL. This is not expected to happen very often, because the
same commit hash is used for each repo. If None, the object will be
downloaded, but nothing will be done with it. Args for the function
include:
- local_path (str): Local path to the downloaded 3D object.
- file_identifier (str): File identifier of the 3D object.
- new_sha256 (str): SHA256 of the contents of the newly downloaded 3D
object.
- old_sha256 (str): Expected SHA256 of the contents of the 3D object as
it was when it was downloaded with Objaverse-XL.
- metadata (Dict[str, Any]): Metadata about the 3D object, including the
GitHub organization and repo names.
Return is not used.
handle_missing_object (Optional[Callable]): Called when an object that is in
Objaverse-XL is not found. Here, it is likely that the repository was
deleted or renamed. If None, nothing will be done with the missing
object. Args for the function include:
- file_identifier (str): File identifier of the 3D object.
- sha256 (str): SHA256 of the contents of the original 3D object.
- metadata (Dict[str, Any]): Metadata about the 3D object, including the
GitHub organization and repo names.
Return is not used.
Returns:
Tuple[str, Optional[str]]: Tuple of the URL and the path to the downloaded
Smithsonian Object. If the Smithsonian Object was not downloaded, the path
will be None.
"""
uid = get_uid_from_str(file_identifier)
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = os.path.join(temp_dir, f"{uid}.glb")
temp_path_tmp = f"{temp_path}.tmp"
response = requests.get(file_identifier)
# check if the path is valid
if response.status_code == 404:
logger.warning(f"404 for {file_identifier}")
if handle_missing_object is not None:
handle_missing_object(
file_identifier=file_identifier,
sha256=expected_sha256,
metadata={},
)
return file_identifier, None
with open(temp_path_tmp, "wb") as file:
for chunk in response.iter_content(chunk_size=8192):
file.write(chunk)
# rename to temp_path
os.rename(temp_path_tmp, temp_path)
# check the sha256
sha256 = get_file_hash(temp_path)
if sha256 == expected_sha256:
if handle_found_object is not None:
handle_found_object(
local_path=temp_path,
file_identifier=file_identifier,
sha256=sha256,
metadata={},
)
else:
if handle_modified_object is not None:
handle_modified_object(
local_path=temp_path,
file_identifier=file_identifier,
new_sha256=sha256,
old_sha256=expected_sha256,
metadata={},
)
if download_dir is not None:
filename = os.path.join(
download_dir, "smithsonian", "objects", f"{uid}.glb"
)
fs, path = fsspec.core.url_to_fs(filename)
fs.makedirs(os.path.dirname(path), exist_ok=True)
fs.put(temp_path, path)
else:
path = None
return file_identifier, path
def _parallel_download_object(self, args):
# workaround since starmap doesn't work well with tqdm
return self._download_smithsonian_object(*args)
def download_objects(
self,
objects: pd.DataFrame,
download_dir: Optional[str] = "~/.objaverse",
processes: Optional[int] = None,
handle_found_object: Optional[Callable] = None,
handle_modified_object: Optional[Callable] = None,
handle_missing_object: Optional[Callable] = None,
**kwargs,
) -> Dict[str, str]:
"""Downloads all Smithsonian Objects.
Args:
objects (pd.DataFrmae): Objects to download. Must have columns for
the object "fileIdentifier" and "sha256". Use the `get_annotations`
function to get the metadata.
download_dir (Optional[str], optional): Directory to download the
Smithsonian Objects to. Supports all file systems supported by fsspec.
If None, the Smithsonian Objects will be deleted after they are
downloaded and processed with the handler functions. Defaults to
"~/.objaverse".
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.
handle_found_object (Optional[Callable], optional): Called when an object is
successfully found and downloaded. Here, the object has the same sha256
as the one that was downloaded with Objaverse-XL. If None, the object
will be downloaded, but nothing will be done with it. Args for the
function include:
- local_path (str): Local path to the downloaded 3D object.
- file_identifier (str): File identifier of the 3D object.
- sha256 (str): SHA256 of the contents of the 3D object.
- metadata (Dict[Hashable, Any]): Metadata about the 3D object,
including the GitHub organization and repo names.
Return is not used. Defaults to None.
handle_modified_object (Optional[Callable], optional): Called when a
modified object is found and downloaded. Here, the object is
successfully downloaded, but it has a different sha256 than the one that
was downloaded with Objaverse-XL. This is not expected to happen very
often, because the same commit hash is used for each repo. If None, the
object will be downloaded, but nothing will be done with it. Args for
the function include:
- local_path (str): Local path to the downloaded 3D object.
- file_identifier (str): File identifier of the 3D object.
- new_sha256 (str): SHA256 of the contents of the newly downloaded 3D
object.
- old_sha256 (str): Expected SHA256 of the contents of the 3D object as
it was when it was downloaded with Objaverse-XL.
- metadata (Dict[Hashable, Any]): Metadata about the 3D object, which is
particular to the souce.
Return is not used. Defaults to None.
handle_missing_object (Optional[Callable], optional): Called when an object
that is in Objaverse-XL is not found. Here, it is likely that the
repository was deleted or renamed. If None, nothing will be done with
the missing object.
Args for the function include:
- file_identifier (str): File identifier of the 3D object.
- sha256 (str): SHA256 of the contents of the original 3D object.
- metadata (Dict[Hashable, Any]): Metadata about the 3D object, which is
particular to the source.
Return is not used. Defaults to None.
Returns:
Dict[str, str]: A dictionary mapping from the fileIdentifier to the
download_path.
"""
if processes is None:
processes = multiprocessing.cpu_count()
out = {}
objects_to_download = []
if download_dir is not None:
objects_dir = os.path.join(download_dir, "smithsonian", "objects")
fs, path = fsspec.core.url_to_fs(objects_dir)
fs.makedirs(path, exist_ok=True)
# get the existing glb files
existing_glb_files = fs.glob(
os.path.join(objects_dir, "*.glb"), refresh=True
)
existing_uids = set(
os.path.basename(file).split(".")[0] for file in existing_glb_files
)
# find the urls that need to be downloaded
already_downloaded_objects = set()
for _, item in objects.iterrows():
file_identifier = item["fileIdentifier"]
uid = get_uid_from_str(file_identifier)
if uid not in existing_uids:
objects_to_download.append(item)
else:
already_downloaded_objects.add(file_identifier)
out[file_identifier] = os.path.join(
os.path.expanduser(objects_dir), f"{uid}.glb"
)
else:
existing_uids = set()
objects_to_download = [item for _, item in objects.iterrows()]
already_downloaded_objects = set()
out = {}
logger.info(
f"Found {len(already_downloaded_objects)} Smithsonian Objects already downloaded"
)
logger.info(
f"Downloading {len(objects_to_download)} Smithsonian Objects with {processes} processes"
)
if len(objects_to_download) == 0:
return out
args = [
[
item["fileIdentifier"],
download_dir,
item["sha256"],
handle_found_object,
handle_modified_object,
handle_missing_object,
]
for item in objects_to_download
]
with Pool(processes=processes) as pool:
results = list(
tqdm(
pool.imap_unordered(self._parallel_download_object, args),
total=len(objects_to_download),
desc="Downloading Smithsonian Objects",
)
)
for file_identifier, download_path in results:
if download_path is not None:
out[file_identifier] = download_path
return out
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