Create README.md

README.md

@@ -1,3 +1,100 @@
----
-license: mit
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+# Datacard
+This dataset is the evaluation VLM dataset used in VLABench. It is designed to evaluate the planning capabilities of Vision-Language Models (VLMs) in embodied scenarios. 
+
+## Source
+- Project Page: [https://vlabench.github.io/](https://vlabench.github.io/)
+- Arxiv Paper: [https://arxiv.org/abs/2412.18194](https://arxiv.org/abs/2412.18194)
+- Code: [https://github.com/OpenMOSS/VLABench](https://github.com/OpenMOSS/VLABench)
+
+## Uses
+
+The dataset structure is as follows:
+```
+vlm_evaluation_v1.0/
+├── CommenSence/
+    ├── add_condiment_common_sense/
+    ├── insert_flower_common_sense/
+    ├── select_billiards_common_sense/
+    ├── select_chemistry_tube_common_sense/
+    ├── select_drink_common_sense/
+    ├── select_fruit_common_sense/
+    ├── select_nth_largest_poker/
+    └── select_toy_common_sense/
+├── Complex/
+    ├── book_rearrange/
+    ├── cook_dishes/
+    ├── hammer_nail_and_hang_picture/
+    ├── take_chemistry_experiment/
+    └── texas_holdem/
+├── M&T/
+    ├── add_condiment/
+    ├── insert_flower/
+    ├── select_billiards/
+    ├── select_book/
+    ├── select_chemistry_tube/
+    ├── select_drink/
+    ├── select_fruit/
+    ├── select_poker/
+    └── select_toy/
+├── PhysicsLaw/
+    ├── density_qa/
+    ├── friction_qa/
+    ├── magnetism_qa/
+    ├── reflection_qa/
+    ├── speed_of_sound_qa/
+    └── thermal_expansion_qa/
+├── Semantic/
+    ├── add_condiment_semantic/
+    ├── insert_flower_semantic/
+    ├── select_billiards_semantic/
+    ├── select_book_semantic/
+    ├── select_chemistry_tube_semantic/
+    ├── select_drink_semantic/
+    ├── select_fruit_semantic/
+    ├── select_poker_semantic/
+    └── select_toy_semantic/
+├── Spatial/
+    ├── add_condiment_spatial/
+    ├── insert_bloom_flower/
+    ├── select_billiards_spatial/
+    ├── select_book_spatial/
+    ├── select_chemistry_tube_spatial/
+    ├── select_fruit_spatial/
+    ├── select_poker_spatial/
+    └── select_toy_spatial/
+```
+In each subtask, there are 100 episodes of data, such as:
+```
+vlm_evaluation_v1.0/
+├── CommenSence/
+    └── add_condiment_common_sense/
+        ├── example0
+            ├── env_config
+            ├── input
+            └── output     
+     
+        ├── ...
+        └── example99
+```
+
+The `env_config` folder includes the episode_config for conveniently reproducing the evaluation environment.
+The `input` folder includes the stacked four-view images and their segmentated visual prompted images as the visual input to VLMs, as well as the instruction to descripe the task.
+The `output` folder includes the ground truth action sequence JSON file.
+
+## Evaluate
+
+To evaluate the dataset, please refer to our evaluation guidance in [repo](https://github.com/OpenMOSS/VLABench).
+
+## Citation
+If you find our work helps,please cite us:
+```
+@misc{zhang2024vlabench,
+      title={VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks}, 
+      author={Shiduo Zhang and Zhe Xu and Peiju Liu and Xiaopeng Yu and Yuan Li and Qinghui Gao and Zhaoye Fei and Zhangyue Yin and Zuxuan Wu and Yu-Gang Jiang and Xipeng Qiu},
+      year={2024},
+      eprint={2412.18194},
+      archivePrefix={arXiv},
+      primaryClass={cs.RO},
+      url={https://arxiv.org/abs/2412.18194}, 
+}
+```