updated readme

README.md

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 license: cc-by-4.0
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+# 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://arxiv.org/abs/2212.02842 
+
+Nature Scientific data paper will be available soon.
+
+