| |
| 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"), |
| "frames": datasets.Sequence(datasets.Image()), |
| "optical_flows": datasets.Sequence(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) |
| |
| |
| video_base_name = record['video_name'].replace('.mp4', '') |
| frames_dir = f"frames/{video_base_name}" |
| flows_dir = f"optical_flows/{video_base_name}" |
| |
| |
| frame_paths = [] |
| if os.path.exists(frames_dir): |
| frame_files = sorted([f for f in os.listdir(frames_dir) if f.endswith('.png')]) |
| frame_paths = [os.path.join(frames_dir, f) for f in frame_files] |
| |
| |
| flow_paths = [] |
| if os.path.exists(flows_dir): |
| flow_files = sorted([f for f in os.listdir(flows_dir) if f.endswith('.png')]) |
| flow_paths = [os.path.join(flows_dir, f) for f in flow_files] |
| |
| record['frames'] = frame_paths |
| record['optical_flows'] = flow_paths |
| |
| yield idx, record |
| idx += 1 |
|
|