"""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