"""Script to download objects from Objaverse 1.0.""" import gzip import json import os import urllib.request import multiprocessing from multiprocessing import Pool from typing import Any, Dict, List, Optional, Tuple, Callable import requests import pandas as pd import tempfile from objaverse_xl.utils import get_file_hash from objaverse_xl.abstract import ObjaverseSource import fsspec from loguru import logger from tqdm import tqdm class SketchfabDownloader(ObjaverseSource): """A class for downloading and processing Objaverse 1.0.""" def load_annotations(self, download_dir: str = "~/.objaverse") -> pd.DataFrame: """Load the annotations from the given directory. Args: download_dir (str, optional): The directory to load the annotations from. Supports all file systems supported by fsspec. Defaults to "~/.objaverse". Returns: pd.DataFrame: The annotations, which includes the columns "thingId", "fileId", "filename", and "license". """ remote_url = "https://huggingface.co/datasets/allenai/objaverse-xl/resolve/main/objaverse_v1/object-metadata.parquet" download_path = os.path.join( download_dir, "hf-objaverse-v1", "thingiverse-objects.parquet" ) fs, path = fsspec.core.url_to_fs(download_path) if not fs.exists(path): fs.makedirs(os.path.dirname(path), exist_ok=True) logger.info(f"Downloading {remote_url} to {download_path}") response = requests.get(remote_url) response.raise_for_status() with fs.open(path, "wb") as file: file.write(response.content) # read the file with pandas and fsspec with fs.open(download_path, "rb") as f: annotations_df = pd.read_parquet(f) annotations_df["metadata"] = "{}" return annotations_df def load_full_annotations( self, uids: Optional[List[str]] = None, download_dir: str = "~/.objaverse", ) -> Dict[str, Any]: """Load the full metadata of all objects in the dataset. Args: uids: A list of uids with which to load metadata. If None, it loads the metadata for all uids. download_dir: The base directory to download the annotations to. Supports all file systems supported by fsspec. Defaults to "~/.objaverse". Returns: A dictionary of the metadata for each object. The keys are the uids and the values are the metadata for that object. """ # make the metadata dir if it doesn't exist metadata_path = os.path.join(download_dir, "hf-objaverse-v1", "metadata") fs, _ = fsspec.core.url_to_fs(metadata_path) fs.makedirs(metadata_path, exist_ok=True) # get the dir ids that need to be loaded if only downloading a subset of uids object_paths = self._load_object_paths(download_dir=download_dir) dir_ids = ( {object_paths[uid].split("/")[1] for uid in uids} if uids is not None else {f"{i // 1000:03d}-{i % 1000:03d}" for i in range(160)} ) # get the existing metadata files existing_metadata_files = fs.glob( os.path.join(metadata_path, "*.json.gz"), refresh=True ) existing_dir_ids = { file.split("/")[-1].split(".")[0] for file in existing_metadata_files if file.endswith(".json.gz") # note partial files end with .json.gz.tmp } downloaded_dir_ids = existing_dir_ids.intersection(dir_ids) logger.info( f"Found {len(downloaded_dir_ids)} metadata files already downloaded" ) # download the metadata from the missing dir_ids dir_ids_to_download = dir_ids - existing_dir_ids logger.info(f"Downloading {len(dir_ids_to_download)} metadata files") # download the metadata file if it doesn't exist if len(dir_ids_to_download) > 0: for i_id in tqdm(dir_ids_to_download, desc="Downloading metadata files"): # get the path to the json file path = os.path.join(metadata_path, f"{i_id}.json.gz") # get the url to the remote json file hf_url = f"https://huggingface.co/datasets/allenai/objaverse/resolve/main/metadata/{i_id}.json.gz" # download the file to a tmp path to avoid partial downloads on interruption tmp_path = f"{path}.tmp" with fs.open(tmp_path, "wb") as f: with urllib.request.urlopen(hf_url) as response: f.write(response.read()) fs.rename(tmp_path, path) out = {} for i_id in tqdm(dir_ids, desc="Reading metadata files"): # get the path to the json file path = os.path.join(metadata_path, f"{i_id}.json.gz") # read the json file of the metadata chunk with fs.open(path, "rb") as f: with gzip.GzipFile(fileobj=f) as gfile: content = gfile.read() data = json.loads(content) # filter the data to only include the uids we want if uids is not None: data = {uid: data[uid] for uid in uids if uid in data} # add the data to the out dict out.update(data) return out def _load_object_paths(self, download_dir: str) -> Dict[str, str]: """Load the object paths from the dataset. The object paths specify the location of where the object is located in the Hugging Face repo. Returns: A dictionary mapping the uid to the object path. """ object_paths_file = "object-paths.json.gz" local_path = os.path.join(download_dir, "hf-objaverse-v1", object_paths_file) # download the object_paths file if it doesn't exist fs, path = fsspec.core.url_to_fs(local_path) if not fs.exists(path): hf_url = f"https://huggingface.co/datasets/allenai/objaverse/resolve/main/{object_paths_file}" fs.makedirs(os.path.dirname(path), exist_ok=True) # download the file to a tmp path to avoid partial downloads on interruption tmp_path = f"{path}.tmp" with fs.open(tmp_path, "wb") as f: with urllib.request.urlopen(hf_url) as response: f.write(response.read()) fs.rename(tmp_path, path) # read the object_paths with fs.open(path, "rb") as f: with gzip.GzipFile(fileobj=f) as gfile: content = gfile.read() object_paths = json.loads(content) return object_paths def load_uids(self, download_dir: str = "~/.objaverse") -> List[str]: """Load the uids from the dataset. Returns: A list of all the UIDs from the dataset. """ return list(self._load_object_paths(download_dir=download_dir).keys()) def _download_object( self, file_identifier: str, hf_object_path: str, download_dir: Optional[str], expected_sha256: str, handle_found_object: Optional[Callable] = None, handle_modified_object: Optional[Callable] = None, handle_missing_object: Optional[Callable] = None, ) -> Tuple[str, Optional[str]]: """Download the object for the given uid. Args: file_identifier: The file identifier of the object. hf_object_path: The path to the object in the Hugging Face repo. Here, hf_object_path is the part that comes after "main" in the Hugging Face repo url: https://huggingface.co/datasets/allenai/objaverse/resolve/main/{hf_object_path} download_dir: The base directory to download the object to. Supports all file systems supported by fsspec. Defaults to "~/.objaverse". expected_objects (str): The expected SHA256 of the contents of the downloaded object. 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): GitHub URL 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. 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): GitHub URL 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. 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): GitHub URL 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. Defaults to None. Returns: A tuple of the uid and the path to where the downloaded object. If download_dir is None, the path will be None. """ hf_url = f"https://huggingface.co/datasets/allenai/objaverse/resolve/main/{hf_object_path}" with tempfile.TemporaryDirectory() as temp_dir: # download the file locally temp_path = os.path.join(temp_dir, hf_object_path) os.makedirs(os.path.dirname(temp_path), exist_ok=True) temp_path_tmp = f"{temp_path}.tmp" with open(temp_path_tmp, "wb") as file: with urllib.request.urlopen(hf_url) as response: file.write(response.read()) os.rename(temp_path_tmp, temp_path) # get the sha256 of the downloaded file 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=dict(), ) 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=dict(), ) if download_dir is not None: filename = os.path.join(download_dir, "hf-objaverse-v1", hf_object_path) 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_object(*args) def _get_uid(self, item: pd.Series) -> str: file_identifier = item["fileIdentifier"] return file_identifier.split("/")[-1] def uid_to_file_identifier(self, uid: str) -> str: """Convert the uid to the file identifier. Args: uid (str): The uid of the object. Returns: The file identifier of the object. """ return f"https://sketchfab.com/3d-models/{uid}" def file_identifier_to_uid(self, file_identifier: str) -> str: """Convert the file identifier to the uid. Args: file_identifier (str): The file identifier of the object. Returns: The uid of the object. """ return file_identifier.split("/")[-1] 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]: """Return the path to the object files for the given uids. If the object is not already downloaded, it will be downloaded. Args: objects (pd.DataFrame): Objects to download. Must have columns for the object "fileIdentifier" and "sha256". Use the `load_annotations` function to get the metadata. download_dir (Optional[str], optional): The base directory to download the object to. Supports all file systems supported by fsspec. If None, the objects will be removed after downloading. Defaults to "~/.objaverse". processes (Optional[int], optional): The number of processes to use to download the 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: A dictionary mapping the object fileIdentifier to the local path of where the object downloaded. """ hf_object_paths = self._load_object_paths( download_dir=download_dir if download_dir is not None else "~/.objaverse" ) if processes is None: processes = multiprocessing.cpu_count() # make a copy of the objects so we don't modify the original objects = objects.copy() objects["uid"] = objects.apply(self._get_uid, axis=1) uids_to_sha256 = dict(zip(objects["uid"], objects["sha256"])) uids_set = set(uids_to_sha256.keys()) # create a new df where the uids are the index objects_uid_index = objects.set_index("uid") out = {} objects_to_download = [] if download_dir is None: for _, item in objects.iterrows(): uid = item["uid"] if uid not in hf_object_paths: logger.error(f"Could not find object with uid {uid}!") if handle_missing_object is not None: handle_missing_object( file_identifier=item["fileIdentifier"], sha256=item["sha256"], metadata=dict(), ) continue objects_to_download.append( (item["fileIdentifier"], hf_object_paths[uid], item["sha256"]) ) else: versioned_dirname = os.path.join(download_dir, "hf-objaverse-v1") fs, path = fsspec.core.url_to_fs(versioned_dirname) # Get the existing file paths. This is much faster than calling fs.exists() for each # file. `glob()` is like walk, but returns a list of files instead of the nested # directory structure. glob() is also faster than find() / walk() since it doesn't # need to traverse the entire directory structure. existing_file_paths = fs.glob( os.path.join(path, "glbs", "*", "*.glb"), refresh=True ) existing_uids = { file.split("/")[-1].split(".")[0] for file in existing_file_paths if file.endswith(".glb") # note partial files end with .glb.tmp } # add the existing downloaded uids to the return dict already_downloaded_uids = uids_set.intersection(existing_uids) for uid in already_downloaded_uids: hf_object_path = hf_object_paths[uid] fs_abs_object_path = os.path.join(versioned_dirname, hf_object_path) out[self.uid_to_file_identifier(uid)] = fs_abs_object_path logger.info( f"Found {len(already_downloaded_uids)} objects already downloaded" ) # get the uids that need to be downloaded remaining_uids = uids_set - existing_uids for uid in remaining_uids: item = objects_uid_index.loc[uid] if uid not in hf_object_paths: logger.error(f"Could not find object with uid {uid}. Skipping it.") if handle_missing_object is not None: handle_missing_object( file_identifier=item["fileIdentifier"], sha256=item["sha256"], metadata=dict(), ) continue objects_to_download.append( (item["fileIdentifier"], hf_object_paths[uid], item["sha256"]) ) logger.info( f"Downloading {len(objects_to_download)} new objects across {processes} processes" ) # check if all objects are already downloaded if len(objects_to_download) == 0: return out args = [ ( file_identifier, hf_object_path, download_dir, sha256, handle_found_object, handle_modified_object, handle_missing_object, ) for file_identifier, hf_object_path, sha256 in objects_to_download ] # download the objects in parallel with Pool(processes) as pool: new_object_downloads = list( tqdm( pool.imap_unordered(self._parallel_download_object, args), total=len(args), ) ) for file_identifier, local_path in new_object_downloads: out[file_identifier] = local_path return out def load_lvis_annotations( self, download_dir: str = "~/.objaverse", ) -> Dict[str, List[str]]: """Load the LVIS annotations. If the annotations are not already downloaded, they will be downloaded. Args: download_dir: The base directory to download the annotations to. Supports all file systems supported by fsspec. Defaults to "~/.objaverse". Returns: A dictionary mapping the LVIS category to the list of uids in that category. """ hf_url = "https://huggingface.co/datasets/allenai/objaverse/resolve/main/lvis-annotations.json.gz" download_path = os.path.join( download_dir, "hf-objaverse-v1", "lvis-annotations.json.gz" ) # use fsspec fs, path = fsspec.core.url_to_fs(download_path) if not fs.exists(path): # make dir if it doesn't exist fs.makedirs(os.path.dirname(path), exist_ok=True) # download the file with fs.open(path, "wb") as f: with urllib.request.urlopen(hf_url) as response: f.write(response.read()) # load the gzip file with fs.open(path, "rb") as f: with gzip.GzipFile(fileobj=f) as gfile: content = gfile.read() data = json.loads(content) return data