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import os |
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import re |
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import argparse |
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import zipfile |
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from concurrent.futures import ThreadPoolExecutor |
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from tqdm import tqdm |
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import pandas as pd |
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from utils import get_file_hash |
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def add_args(parser: argparse.ArgumentParser): |
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pass |
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def get_metadata(**kwargs): |
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metadata = pd.read_csv("hf://datasets/JeffreyXiang/TRELLIS-500K/Toys4k.csv") |
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return metadata |
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def download(metadata, output_dir, **kwargs): |
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os.makedirs(output_dir, exist_ok=True) |
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if not os.path.exists(os.path.join(output_dir, 'raw', 'toys4k_blend_files.zip')): |
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print("\033[93m") |
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print("Toys4k have to be downloaded manually") |
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print(f"Please download the toys4k_blend_files.zip file and place it in the {output_dir}/raw directory") |
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print("Visit https://github.com/rehg-lab/lowshot-shapebias/tree/main/toys4k for more information") |
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print("\033[0m") |
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raise FileNotFoundError("toys4k_blend_files.zip not found") |
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downloaded = {} |
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metadata = metadata.set_index("file_identifier") |
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with zipfile.ZipFile(os.path.join(output_dir, 'raw', 'toys4k_blend_files.zip')) as zip_ref: |
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with ThreadPoolExecutor(max_workers=os.cpu_count()) as executor, \ |
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tqdm(total=len(metadata), desc="Extracting") as pbar: |
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def worker(instance: str) -> str: |
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try: |
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zip_ref.extract(os.path.join('toys4k_blend_files', instance), os.path.join(output_dir, 'raw')) |
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sha256 = get_file_hash(os.path.join(output_dir, 'raw/toys4k_blend_files', instance)) |
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pbar.update() |
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return sha256 |
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except Exception as e: |
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pbar.update() |
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print(f"Error extracting for {instance}: {e}") |
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return None |
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sha256s = executor.map(worker, metadata.index) |
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executor.shutdown(wait=True) |
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for k, sha256 in zip(metadata.index, sha256s): |
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if sha256 is not None: |
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if sha256 == metadata.loc[k, "sha256"]: |
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downloaded[sha256] = os.path.join("raw/toys4k_blend_files", k) |
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else: |
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print(f"Error downloading {k}: sha256s do not match") |
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return pd.DataFrame(downloaded.items(), columns=['sha256', 'local_path']) |
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def foreach_instance(metadata, output_dir, func, max_workers=None, desc='Processing objects') -> pd.DataFrame: |
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import os |
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from concurrent.futures import ThreadPoolExecutor |
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from tqdm import tqdm |
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metadata = metadata.to_dict('records') |
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records = [] |
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max_workers = max_workers or os.cpu_count() |
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try: |
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with ThreadPoolExecutor(max_workers=max_workers) as executor, \ |
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tqdm(total=len(metadata), desc=desc) as pbar: |
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def worker(metadatum): |
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try: |
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local_path = metadatum['local_path'] |
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sha256 = metadatum['sha256'] |
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file = os.path.join(output_dir, local_path) |
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record = func(file, sha256) |
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if record is not None: |
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records.append(record) |
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pbar.update() |
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except Exception as e: |
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print(f"Error processing object {sha256}: {e}") |
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pbar.update() |
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executor.map(worker, metadata) |
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executor.shutdown(wait=True) |
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except: |
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print("Error happened during processing.") |
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return pd.DataFrame.from_records(records) |
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