Add 'real_scenes_seesaw_scene_128P' config data files
Browse files- README.md +7 -3
- dataset_infos.json +10 -10
- real_scenes_seesaw_scene_128P/train-00000-of-00001.parquet +3 -0
    	
        README.md
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                dtype: string
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              splits:
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              - name: train
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                num_bytes:  | 
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                num_examples: 10000
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              download_size:  | 
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              dataset_size:  | 
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            - config_name: real_scenes_spring_scene_128P
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              features:
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              - name: image
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              data_files:
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              - split: train
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                path: real_scenes_rendered_reflection_128P/train-*
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            ---
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            # 🧠 Causal3D: A Benchmark for Visual Causal Reasoning
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                dtype: string
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              splits:
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              - name: train
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                num_bytes: 2234514.0
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                num_examples: 10000
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              download_size: 1257167
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              dataset_size: 2234514.0
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            - config_name: real_scenes_spring_scene_128P
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              features:
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              - name: image
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              data_files:
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              - split: train
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                path: real_scenes_rendered_reflection_128P/train-*
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            - config_name: real_scenes_seesaw_scene_128P
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              data_files:
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              - split: train
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                path: real_scenes_seesaw_scene_128P/train-*
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            ---
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            # 🧠 Causal3D: A Benchmark for Visual Causal Reasoning
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        dataset_infos.json
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    | @@ -820,7 +820,7 @@ | |
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                },
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                "real_scenes_seesaw_scene_128P": {
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                    "description": "Causal3D is a benchmark for evaluating causal reasoning in physical and hypothetical visual scenes. \nIt includes both real-world recordings and rendered synthetic scenes demonstrating causal interactions.\n",
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                    "citation": "@article{liu2025causal3d,\n  title={CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data},\n  author={Liu, Disheng and Qiao, Yiran and Liu, Wuche and Lu, Yiren and Zhou, Yunlai and Liang, Tuo and Yin, Yu and Ma, Jing},\n  journal={arXiv preprint arXiv:2503.04852},\n  year={2025}\n}",
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                    "homepage": "https://huggingface.co/datasets/LLDDSS/Causal3D",
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                    "license": "CC-BY-4.0",
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                    "features": {
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                            "_type": "Value"
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                        }
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                    },
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                    "builder_name": " | 
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                    "version": {
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                        "version_str": "1.0.0",
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                        "major": 1,
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                    "splits": {
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                        "train": {
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                            "name": "train",
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                            "num_bytes": 0,
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                            "num_examples":  | 
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                            "dataset_name":  | 
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                        }
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                    },
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                    " | 
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                    " | 
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                    "size_in_bytes": 0,
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                    "config_name": "real_scenes_seesaw_scene_128P"
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                },
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                "real_scenes_spring_scene_128P": {
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                    "description": "Causal3D is a benchmark for evaluating causal reasoning in physical and hypothetical visual scenes. \nIt includes both real-world recordings and rendered synthetic scenes demonstrating causal interactions.\n",
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                },
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                "real_scenes_seesaw_scene_128P": {
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                    "description": "Causal3D is a benchmark for evaluating causal reasoning in physical and hypothetical visual scenes. \nIt includes both real-world recordings and rendered synthetic scenes demonstrating causal interactions.\n",
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                    "citation": "@article{liu2025causal3d,\n  title={CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data},\n  author={Liu, Disheng and Qiao, Yiran and Liu, Wuche and Lu, Yiren and Zhou, Yunlai and Liang, Tuo and Yin, Yu and Ma, Jing},\n  journal={arXiv preprint arXiv:2503.04852},\n  year={2025}\n}\n",
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                    "homepage": "https://huggingface.co/datasets/LLDDSS/Causal3D",
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                    "license": "CC-BY-4.0",
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                    "features": {
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                            "_type": "Value"
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                        }
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                    },
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                    "builder_name": "causal3_d",
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                    "dataset_name": "causal3_d",
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                    "config_name": "real_scenes_seesaw_scene_128P",
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                    "version": {
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                        "version_str": "1.0.0",
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                        "major": 1,
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                    "splits": {
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                        "train": {
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                            "name": "train",
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                            "num_bytes": 2234514.0,
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                            "num_examples": 10000,
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                            "dataset_name": null
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                        }
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                    },
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                    "download_size": 1257167,
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                    "dataset_size": 2234514.0,
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                    "size_in_bytes": 3491681.0
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                },
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                "real_scenes_spring_scene_128P": {
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                    "description": "Causal3D is a benchmark for evaluating causal reasoning in physical and hypothetical visual scenes. \nIt includes both real-world recordings and rendered synthetic scenes demonstrating causal interactions.\n",
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        real_scenes_seesaw_scene_128P/train-00000-of-00001.parquet
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            version https://git-lfs.github.com/spec/v1
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            oid sha256:1565d4feebe96715e87a1db5517997f4874601834845931c2ccd43e04651ab30
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            size 1257167
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