import os import re import argparse import tarfile from concurrent.futures import ThreadPoolExecutor from tqdm import tqdm import pandas as pd import huggingface_hub from utils import get_file_hash def add_args(parser: argparse.ArgumentParser): pass def get_metadata(**kwargs): metadata = pd.read_csv("hf://datasets/JeffreyXiang/TRELLIS-500K/HSSD.csv") return metadata def download(metadata, output_dir, **kwargs): os.makedirs(os.path.join(output_dir, 'raw'), exist_ok=True) # check login try: huggingface_hub.whoami() except: print("\033[93m") print("Haven't logged in to the Hugging Face Hub.") print("Visit https://huggingface.co/settings/tokens to get a token.") print("\033[0m") huggingface_hub.login() try: huggingface_hub.hf_hub_download(repo_id="hssd/hssd-models", filename="README.md", repo_type="dataset") except: print("\033[93m") print("Error downloading HSSD dataset.") print("Check if you have access to the HSSD dataset.") print("Visit https://huggingface.co/datasets/hssd/hssd-models for more information") print("\033[0m") downloaded = {} metadata = metadata.set_index("file_identifier") with ThreadPoolExecutor(max_workers=os.cpu_count()) as executor, \ tqdm(total=len(metadata), desc="Downloading") as pbar: def worker(instance: str) -> str: try: huggingface_hub.hf_hub_download(repo_id="hssd/hssd-models", filename=instance, repo_type="dataset", local_dir=os.path.join(output_dir, 'raw')) sha256 = get_file_hash(os.path.join(output_dir, 'raw', instance)) pbar.update() return sha256 except Exception as e: pbar.update() print(f"Error extracting for {instance}: {e}") return None sha256s = executor.map(worker, metadata.index) executor.shutdown(wait=True) for k, sha256 in zip(metadata.index, sha256s): if sha256 is not None: if sha256 == metadata.loc[k, "sha256"]: downloaded[sha256] = os.path.join('raw', k) else: print(f"Error downloading {k}: sha256s do not match") return pd.DataFrame(downloaded.items(), columns=['sha256', 'local_path']) def foreach_instance(metadata, output_dir, func, max_workers=None, desc='Processing objects') -> pd.DataFrame: import os from concurrent.futures import ThreadPoolExecutor from tqdm import tqdm # load metadata metadata = metadata.to_dict('records') # processing objects records = [] max_workers = max_workers or os.cpu_count() try: with ThreadPoolExecutor(max_workers=max_workers) as executor, \ tqdm(total=len(metadata), desc=desc) as pbar: def worker(metadatum): try: local_path = metadatum['local_path'] sha256 = metadatum['sha256'] file = os.path.join(output_dir, local_path) record = func(file, sha256) if record is not None: records.append(record) pbar.update() except Exception as e: print(f"Error processing object {sha256}: {e}") pbar.update() executor.map(worker, metadata) executor.shutdown(wait=True) except: print("Error happened during processing.") return pd.DataFrame.from_records(records)