import multiprocessing import os from functools import partial from multiprocessing import Pool from typing import Dict, List, Optional, Tuple 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") -> 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) # add uid and license columns df["uid"] = df["url"].apply(get_uid_from_str) df["license"] = "CC0" return df def _download_smithsonian_object( url: str, download_dir: str = "~/.objaverse" ) -> 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: 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". 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(url) filename = os.path.join(download_dir, "smithsonian", "objects", f"{uid}.glb") fs, path = fsspec.core.url_to_fs(filename) response = requests.get(url) # check if the path is valid if response.status_code == 404: logger.warning(f"404 for {url}") return url, None # write to tmp path so that we don't have a partial file tmp_path = f"{path}.tmp" 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, path) return url, filename def download_smithsonian_objects( urls: Optional[str] = None, processes: Optional[int] = None, download_dir: str = "~/.objaverse", ) -> 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". 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() # filename = os.path.join(download_dir, "smithsonian", "objects", f"{uid}.glb") 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 = [ os.path.basename(file).split(".")[0] for file in existing_glb_files ] # find the urls that need to be downloaded out = [] urls_to_download = set([]) already_downloaded_urls = set([]) for url in urls: uid = get_uid_from_str(url) if uid not in existing_uids: urls_to_download.add(url) else: already_downloaded_urls.add(url) out.append( {"download_path": os.path.join(objects_dir, f"{uid}.glb"), "url": url} ) logger.info( f"Found {len(already_downloaded_urls)} Smithsonian Objects already downloaded" ) logger.info( f"Downloading {len(urls_to_download)} Smithsonian Objects with {processes=}" ) if len(urls_to_download) == 0: return out with Pool(processes=processes) as pool: results = list( tqdm( pool.imap_unordered( partial(_download_smithsonian_object, download_dir=download_dir), urls_to_download, ), total=len(urls_to_download), desc="Downloading Smithsonian Objects", ) ) out.extend( [ {"download_path": download_path, "url": url} for url, download_path in results if download_path is not None ] ) return out