Generates synthetic datasets for training and evaluating vision models on shortest path finding tasks. Each sample contains a simple grid with start and end points where an agent must find and traverse the shortest path.
Each sample pairs a task (first frame + prompt describing what needs to happen) with its ground truth solution (final frame showing the result + video demonstrating how to achieve it). This structure enables both model evaluation and training.
| Property | Value |
|---|---|
| Task ID | G-18 |
| Task | Grid Shortest Path |
| Category | Spatiality |
| Resolution | 1024×1024 px |
| FPS | 16 fps |
| Duration | ~3 seconds |
| Output | PNG images + MP4 video |
# 1. Clone the repository
git clone https://github.com/VBVR-DataFactory/G-18_grid_shortest_path_data-generator.git
cd G-18_grid_shortest_path_data-generator
# 2. Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# 3. Install dependencies
pip install --upgrade pip
pip install -r requirements.txt
pip install -e .# Generate 50 samples
python examples/generate.py --num-samples 50
# Custom output directory
python examples/generate.py --num-samples 100 --output data/my_dataset
# Reproducible generation with seed
python examples/generate.py --num-samples 50 --seed 42
# Without videos (faster)
python examples/generate.py --num-samples 50 --no-videos| Argument | Description |
|---|---|
--num-samples |
Number of tasks to generate (required) |
--output |
Output directory (default: data/questions) |
--seed |
Random seed for reproducibility |
--no-videos |
Skip video generation (images only) |
The scene shows a 10x10 grid with a red start square (containing a pink circular agent) and a blue end square. Starting from the red start square, the agent can move to adjacent cells (up, down, left, right). The goal is to move the agent to the blue end square along the shortest path.
 |
 |
 |
| Initial Frame Agent at green start, purple end visible |
Animation Agent moves along shortest path |
Final Frame Agent reached purple end point |
Navigate a 10×10 grid from start point to end point by following the shortest possible path.
- Grid: 10×10 grid of cells with black borders
- Start point: Colored filled cell with circular agent (e.g., green)
- End point: Different colored filled cell (e.g., purple)
- Agent: Circular character (color varies per sample)
- Movement: Can move up, down, left, right to adjacent cells
- Background: White grid with visible cell borders
- Goal: Reach end point using minimum number of moves
- Pure shortest path finding without obstacles
- Random start/end positions ensuring variety
- Distinct color coding for start and end points (8 color options)
- BFS algorithm guarantees optimal path
- Grid-based movement (no diagonal)
- Smooth animation with interpolated frames
data/questions/grid_shortest_path_task/grid_shortest_path_00000000/
├── first_frame.png # Initial grid with start and end points
├── final_frame.png # Agent at end point
├── prompt.txt # Shortest path instruction
├── ground_truth.mp4 # Animation of optimal path
└── question_metadata.json # Task metadata
File specifications:
- Images: 1024×1024 PNG format
- Video: MP4 format, 16 fps
- Duration: ~3 seconds
spatiality path-planning shortest-path grid-navigation spatial-reasoning graph-algorithms