README.md

---
license: cc-by-4.0
---

# VISEM-Tracking-graphs - HuggingFace Repository

This HuggingFace repository contains the pre-generated graphs for the sperm video dataset called VISEM-Tracking (https://huggingface.co/papers/2212.02842) . The graphs represent spatial and temporal relationships between sperm in a video. Spatial edges connect sperms within the same frame, while temporal edges connect sperms across different frames.

The graphs have been generated with varying spatial threshold values: 0.1, 0.2, 0.3, 0.4, and 0.5. Each spatial threshold determines the maximum distance between two nodes for them to be connected in the graph. The repository contains separate directories for each spatial threshold.

## Repository Structure

The repository is structured as follows:

- `spatial_threshold_0.1`
- `spatial_threshold_0.2`
- `spatial_threshold_0.3`
- `spatial_threshold_0.4`
- `spatial_threshold_0.5`

Inside each `spatial_threshold_X` directory, you will find:

- `frame_graphs`: A directory containing individual frame graphs as GraphML files.
- `video_graph.graphml`: A GraphML file containing the complete video graph.

## Usage

To use the graphs in this repository, you need to:

1. Download the desired graph files (frame graphs or video graph) for the spatial threshold of your choice.
2. Load the graphs using a graph library such as NetworkX in Python:

```python
import networkx as nx

# Load a frame graph
frame_graph = nx.read_graphml('path/to/frame_graph_X.graphml')

# Load the video graph
video_graph = nx.read_graphml('path/to/video_graph.graphml')
```

TO USE THIS DATA, you need to cite the paper:
https://www.nature.com/articles/s41597-023-02173-4

The correspondign Nature Scientific data paper will be available soon.