"""Open Cortex FX v3 Dataset.""" import csv import io import zipfile from pathlib import Path from typing import Iterator import datasets _DESCRIPTION = """\ Open Cortex FX v3 is a video dataset focusing on human manual labor and physical work activities. Each video has been carefully annotated to identify work-related content and categorized into specific labor types. """ _HOMEPAGE = "https://huggingface.co/datasets/Standout/open-cortex-fx-v3" _LICENSE = "Apache 2.0" _CITATION = """\ @dataset{open_cortex_fx_v3, title={Open Cortex FX v3: A Classified Dataset of Human Manual Labor}, author={Standout}, year={2024}, url={https://huggingface.co/datasets/Standout/open-cortex-fx-v3} } """ class OpenCortexFXv3(datasets.GeneratorBasedBuilder): """Open Cortex FX v3 Dataset.""" VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="default", version=VERSION, description="Open Cortex FX v3 dataset", ), ] DEFAULT_CONFIG_NAME = "default" def _info(self) -> datasets.DatasetInfo: return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "name": datasets.Value("string"), "category": datasets.Value("string"), "split": datasets.Value("string"), "video": datasets.Value("binary"), } ), homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager): """Returns SplitGenerators.""" # Define splits based on available zip files # We'll create splits for final_0 through final_5 (can be extended) splits = [] for i in range(6): # We have 6 splits (final_0 through final_5) split_name = f"final_{i}" zip_url = f"https://huggingface.co/datasets/Standout/open-cortex-fx-v3/resolve/main/final_{i}.zip" try: zip_path = dl_manager.download(zip_url) if zip_path and Path(zip_path).exists(): splits.append( datasets.SplitGenerator( name=datasets.Split(split_name), gen_kwargs={"zip_path": Path(zip_path)}, ) ) except Exception: # Skip if file doesn't exist continue # If no splits found, return at least one to avoid errors if not splits: # Fallback: try to find any zip file data_dir = Path(dl_manager.download_and_extract("https://huggingface.co/datasets/Standout/open-cortex-fx-v3/tree/main")) zip_files = sorted(data_dir.glob("final_*.zip")) for zip_file in zip_files: split_name = zip_file.stem splits.append( datasets.SplitGenerator( name=datasets.Split(split_name), gen_kwargs={"zip_path": zip_file}, ) ) return splits def _generate_examples(self, zip_path: Path) -> Iterator[tuple[int, dict]]: """Yields examples.""" with zipfile.ZipFile(zip_path, "r") as z: # Read metadata try: with z.open("metadata.csv") as f: content = f.read().decode("utf-8") reader = csv.DictReader(io.StringIO(content)) metadata = list(reader) except KeyError: # If metadata.csv not found, skip this split return # Get split name from zip filename split_name = zip_path.stem for idx, row in enumerate(metadata): video_name = row["name"] category = row["category"] # Find video in zip - try different path formats video_paths = [ f"{category}/{video_name}", f"{category.replace(' ', '_')}/{video_name}", video_name, # Fallback to root ] video_data = None for video_path in video_paths: try: video_data = z.read(video_path) break except KeyError: continue if video_data: yield idx, { "name": video_name, "category": category, "split": split_name, "video": video_data, }