Visual Spatial Planning (VSP) Dataset
## Dataset Description
This dataset contains visual maze navigation and path verification tasks from the Visual Spatial Planning benchmark.
### Dataset Summary
- **Total samples**: 1100
- **Tasks**: Path Navigation (task-main) and Path Verification (task4)
- **Splits**:
- `navigation_test`: 600 samples
verify_test: 500 samples
### Task Types
1. **Path Verification (task4)**: Given a maze image and an action sequence, determine if the path is safe (avoids holes and reaches the goal).
2. **Path Navigation (task-main)**: Given a maze image, generate an optimal action sequence from start to goal while avoiding holes.
### Data Fields
Common fields:
- `idx`: Unique identifier
- `original_id`: Original data ID
- `image`: RGB image of the maze
- `text`: Task instruction and prompt
- `answer`: Ground truth answer
- `task_type`: Type of task (verify/navigation)
- `split`: Data split (test)
- `size`: Maze size (grid dimension)
- `level`: Difficulty level
- `gym_map`: Gym environment map representation (JSON string)
Path Verification specific fields:
- `path_length`: Length of the action sequence
- `path`: Action sequence string
Path Navigation specific fields:
- `start_coords`: Starting coordinates (JSON string)
- `goal_coords`: Goal coordinates (JSON string)
- `obstacle_coords`: Obstacle coordinates (JSON string)
- `astar_path`: A* algorithm path (if available)
### Actions
- `L`: Move left
- `R`: Move right
- `U`: Move up
- `D`: Move down
### Maze Elements
- `S`: Start position
- `G`: Goal position
- `F`: Frozen (safe) tile
- `H`: Hole (unsafe)
## Usage
```python
from datasets import load_dataset
# Load specific split
dataset = load_dataset("hitsmy/AdaEval-VSPO", split="navigation_test")
# Access an example
example = dataset[0]
image = example['image']
prompt = example['text']
answer = example['answer']
## Citation
If you use this dataset, please cite:
@dataset{vsp_dataset,
title={Visual Spatial Planning Dataset},
author={VSP Team},
year={2024}
}
##License
Apache 2.0
