Datasets:
ArXiv:
License:
File size: 1,754 Bytes
94c6c5d e35f382 cd00be0 e35f382 a77e617 e35f382 cd00be0 e35f382 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
---
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.
|