| import datasets | |
| import os | |
| from pathlib import Path | |
| _DESCRIPTION = """ | |
| CameraBench Binary Evaluation Dataset with video frames and optical flow visualizations. | |
| """ | |
| class CameraBenchConfig(datasets.BuilderConfig): | |
| """BuilderConfig for CameraBench.""" | |
| def __init__(self, **kwargs): | |
| super(CameraBenchConfig, self).__init__(**kwargs) | |
| class CameraBench(datasets.GeneratorBasedBuilder): | |
| """CameraBench dataset with frames and optical flows.""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({ | |
| "video_name": datasets.Value("string"), | |
| "video_path": datasets.Value("string"), | |
| "frames_path": datasets.Value("string"), | |
| "optical_flows_path": datasets.Value("string"), | |
| "first_frame": datasets.Image(), | |
| "first_flow": datasets.Image(), | |
| "num_frames": datasets.Value("int32"), | |
| "num_flows": datasets.Value("int32"), | |
| "question": datasets.Value("string"), | |
| "label": datasets.Value("string"), | |
| "task": datasets.Value("string"), | |
| "label_name": datasets.Value("string"), | |
| }) | |
| ) | |
| def _split_generators(self, dl_manager): | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"metadata_path": "data.jsonl"}, | |
| ), | |
| ] | |
| def _generate_examples(self, metadata_path): | |
| import json | |
| idx = 0 | |
| with open(metadata_path, "r") as f: | |
| for line in f: | |
| record = json.loads(line) | |
| yield idx, record | |
| idx += 1 | |