Update README.md

README.md

@@ -5,31 +5,131 @@ language:
 pretty_name: FiftyOne_Gaussian_Splatting
 ---
 
-## Description
+## **Gaussian Splats Dataset**  
+**3D Gaussian Splatting for Real-Time Radiance Field Rendering**  
+
+**Dataset Author**: Paula Ramos  
+**Created Using**: [3D Gaussian Splatting Paper](https://arxiv.org/abs/2308.04079)  
+**Code Repository**: [GitHub - graphdeco-inria/gaussian-splatting](https://github.com/graphdeco-inria/gaussian-splatting) 
+
+
+## **Description**
 
 This dataset consists of Gaussian Splats representations of different real-world scenes, created using the official 3D Gaussian Splatting method. Each scene folder contains:
 
     A reference image representing the scene.
     A PLY file stored in a point_cloud_folder, containing the Gaussian Splats reconstruction.
 
-### The dataset is structured as follows:
 
-```
+### **Overview**  
+This dataset consists of **Gaussian Splats representations** of different real-world scenes, created using the official **3D Gaussian Splatting method**. Each scene folder contains:  
+- A **reference image** representing the scene.  
+- Two **PLY files** stored in a `point_cloud_folder`, containing the **Gaussian Splats reconstructions at iterations 7000 and 30000**.  
+
+The dataset is structured as follows:
+```plaintext
 FO_dataset/
 │── drjohnson/          # Scene Folder
-│   ├── reference_image.jpg 
+│   ├── reference_image.png
 │   ├── point_cloud_folder/
-│       ├── reconstruction.ply
+│       ├── reconstruction_7000.ply
+│       └── reconstruction_30000.ply
 │── playroom/
-│   ├── reference_image.jpg
+│   ├── reference_image.png
 │   ├── point_cloud_folder/
-│       ├── reconstruction.ply
+│       ├── reconstruction_7000.ply
+│       └── reconstruction_30000.ply
 │── train/
-│   ├── reference_image.jpg
+│   ├── reference_image.png
 │   ├── point_cloud_folder/
-│       ├── reconstruction.ply
+│       ├── reconstruction_7000.ply
+│       └── reconstruction_30000.ply
 │── truck/
-│   ├── reference_image.jpg
+│   ├── reference_image.png
 │   ├── point_cloud_folder/
-│       ├── reconstruction.ply
+│       ├── reconstruction_7000.ply
+│       └── reconstruction_30000.ply
+```
+
+---
+
+## **How to Use the Dataset**  
+### **1. Install the Required FiftyOne Plugin**  
+To visualize all `.ply` files using FiftyOne, download the **Gaussian Splats plugin**:
+```bash
+!fiftyone plugins download https://github.com/danielgural/ksplats_panel
+```
+
+### **2. Load & Visualize the Dataset with FiftyOne**  
+Use the following Python script to **load and explore the dataset** in FiftyOne:
+
+```python
+import fiftyone as fo
+from fiftyone.utils.splats import SplatFile
+
+# Create a FiftyOne dataset
+dataset = fo.Dataset(name="splat-test", overwrite=True)
+
+# Add samples (update paths as needed)
+sample1 = fo.Sample(filepath="FO_dataset/drjohnson/reference_image.png")
+sample1["splat"] = SplatFile(filepath="FO_dataset/drjohnson/point_cloud_folder/reconstruction_30000.ply")
+
+sample2 = fo.Sample(filepath="FO_dataset/drjohnson/reference_image.png")
+sample2["splat"] = SplatFile(filepath="FO_dataset/drjohnson/point_cloud_folder/reconstruction_7000.ply")
+
+sample3 = fo.Sample(filepath="FO_dataset/playroom/reference_image.png")
+sample3["splat"] = SplatFile(filepath="FO_dataset/playroom/point_cloud_folder/reconstruction_7000.ply")
+
+sample4 = fo.Sample(filepath="FO_dataset/playroom/reference_image.png")
+sample4["splat"] = SplatFile(filepath="FO_dataset/playroom/point_cloud_folder/reconstruction_30000.ply")
+
+sample5 = fo.Sample(filepath="FO_dataset/train/reference_image.png")
+sample5["splat"] = SplatFile(filepath="FO_dataset/train/point_cloud_folder/reconstruction_7000.ply")
+
+sample6 = fo.Sample(filepath="FO_dataset/train/reference_image.png")
+sample6["splat"] = SplatFile(filepath="FO_dataset/train/point_cloud_folder/reconstruction_30000.ply")
+
+sample7 = fo.Sample(filepath="FO_dataset/truck/reference_image.png")
+sample7["splat"] = SplatFile(filepath="FO_dataset/truck/point_cloud_folder/reconstruction_7000.ply")
+
+sample8 = fo.Sample(filepath="FO_dataset/truck/reference_image.png")
+sample8["splat"] = SplatFile(filepath="FO_dataset/truck/point_cloud_folder/reconstruction_30000.ply")
+
+# Add samples to the dataset
+dataset.add_sample(sample1)
+dataset.add_sample(sample2)
+dataset.add_sample(sample3)
+dataset.add_sample(sample4)
+dataset.add_sample(sample5)
+dataset.add_sample(sample6)
+dataset.add_sample(sample7)
+dataset.add_sample(sample8)
+
+# Launch FiftyOne App
+session = fo.launch_app(dataset, auto=False, port=5152)
+```
+
+---
+
+## **Research & Applications**  
+This dataset is useful for a variety of **3D vision and AI applications**, including:  
+- **NeRF & Gaussian Splatting Benchmarking**  
+- **3D Scene Understanding & Reconstruction**  
+- **Multi-Modal AI (Images + 3D Point Clouds)**  
+- **Real-Time 3D Rendering Research**  
+
+---
+
+## **Citation**  
+If you use this dataset, please cite the original **3D Gaussian Splatting** paper:
+```bibtex
+@article{kerbl2023gsplatting,
+  title={3D Gaussian Splatting for Real-Time Radiance Field Rendering},
+  author={Kerbl, Bernhard and Kopanas, Georgios and Leimkühler, Thomas and Drettakis, George},
+  journal={arXiv preprint arXiv:2308.04079},
+  year={2023}
+}
 ```
+And also the link of this dataset in hugging Face
+---
+