| import json |
| import os |
| import datasets |
|
|
| _CITATION = """\ |
| @InProceedings{...}, |
| title = {Your Dataset Title}, |
| author={Your Name}, |
| year={2025} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| Dataset containing multi-view images with camera poses, depth maps, and masks for NeRF training. |
| """ |
|
|
| _LICENSE = "MIT" |
|
|
| class RefRefConfig(datasets.BuilderConfig): |
| """BuilderConfig for RefRef dataset.""" |
|
|
| def __init__(self, scene=None, **kwargs): |
| """BuilderConfig for RefRef dataset. |
| |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super().__init__(**kwargs) |
| self.scene = scene |
|
|
| class RefRef(datasets.GeneratorBasedBuilder): |
| """A dataset loader for NeRF-style data with camera poses, depth maps, and masks.""" |
|
|
| VERSION = datasets.Version("1.0.0") |
| BUILDER_CONFIG_CLASS = RefRefConfig |
| BUILDER_CONFIGS = [ |
| RefRefConfig( |
| name="single-non-convex", |
| description="Single non-convex scene configuration for RefRef dataset.", |
| ), |
| RefRefConfig( |
| name="multiple-non-convex", |
| description="Multiple non-convex scene configuration for RefRef dataset.", |
| ), |
| RefRefConfig( |
| name="single-convex", |
| description="Single convex scene configuration for RefRef dataset.", |
| ) |
| ] |
|
|
| def _info(self): |
| features = datasets.Features({ |
| "image": datasets.Image(), |
| "depth": datasets.Image(), |
| "mask": datasets.Image(), |
| "transform_matrix": datasets.Sequence( |
| datasets.Sequence(datasets.Value("float64"), length=4), |
| length=4 |
| ), |
| "rotation": datasets.Value("float32") |
| }) |
| |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=features, |
| homepage="", |
| license=_LICENSE, |
| citation=_CITATION |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| |
| return [ |
| datasets.SplitGenerator( |
| name=f"{'cubeBg' if cat == 'textured_cube_scene' else 'sphereBg' if cat == 'textured_sphere_scene' else 'envMapBg'}_{'singleMatConvex' if self.config.name == 'single-convex' else 'singleMatNonConvex' if self.config.name == 'single-non-convex' else 'multiMatNonConvex'}_{self.config.scene}", |
| gen_kwargs={ |
| "filepaths": os.path.join(f"https://huggingface.co/datasets/yinyue27/RefRef_dataset/resolve/main/image_data/{cat}/{self.config.name}/", |
| f"{self.config.scene}_sphere" if cat == "textured_sphere_scene" else f"{self.config.scene}_hdr" if cat == "environment_map_scene" else self.config.scene), |
| "split": f"{'cubeBg' if cat == 'textured_cube_scene' else 'sphereBg' if cat == 'textured_sphere_scene' else 'envMapBg'}_{'singleMatConvex' if self.config.name == 'single-convex' else 'singleMatNonConvex' if self.config.name == 'single-non-convex' else 'multiMatNonConvex'}_{self.config.scene}", |
| }, |
| ) for cat in ["textured_sphere_scene", "textured_cube_scene", "environment_map_scene"] |
| ] |
|
|
| def _generate_examples(self, filepaths, split): |
| for split in ["train", "val", "test"]: |
| split_filepaths = os.path.join(filepaths, f"transforms_{split}.json") |
| with open(split_filepaths, "r", encoding="utf-8") as f: |
| try: |
| data = json.load(f) |
| except json.JSONDecodeError: |
| print("Error opening " + split_filepaths) |
| continue |
| |
| scene_name = os.path.basename(os.path.dirname(split_filepaths)) |
| |
| for frame_idx, frame in enumerate(data.get("frames", [])): |
| base_dir = os.path.dirname(split_filepaths) |
| |
| yield f"{scene_name}_{frame_idx}", { |
| "image": os.path.join(base_dir, frame["file_path"]+".png"), |
| "depth": os.path.join(base_dir, frame["depth_file_path"]), |
| "mask": os.path.join(base_dir, frame["mask_file_path"]), |
| "transform_matrix": frame["transform_matrix"], |
| "rotation": frame.get("rotation", 0.0) |
| } |
