Update README.md

README.md

@@ -16,7 +16,7 @@ tags:
 
 [GitHub](https://github.com/OpsiClear/noise_guided_splatting) | [Project Page](https://opsiclear.github.io/ngs/)
 
-This repository contains the datasets used in the paper **"Fix False Transparency by Noise Guided Splatting"**[cite: 1]. It is designed to facilitate research and benchmarking for the "false transparency" artifact in 3D Gaussian Splatting (3DGS) reconstructions of opaque objects.
+This repository contains the datasets used in the paper **"Fix False Transparency by Noise Guided Splatting"**. It is designed to facilitate research and benchmarking for the "false transparency" artifact in 3D Gaussian Splatting (3DGS) reconstructions of opaque objects.
 
 The repository is composed of four distinct subsets, each augmented with noise Gaussian infills (`inside_gaussians.ply`) crucial for evaluating surface opacity.
 
@@ -49,10 +49,10 @@ The dataset is organized into four main directories, one for each subset. Each s
 ├── objects/
 │   ├── scan\_*/
 │   │   └── ...
-├── dtu/
+├── DTU/
 │   ├── scan\_*/
 │   │   └── ...
-└── omniobject3d/
+└── OmniObject3D/
 ├── scan\_*/ (e.g., antique\_004, dinosaur\_004)
 │   └── ...
 
@@ -62,21 +62,10 @@ The dataset is organized into four main directories, one for each subset. Each s
 
 This dataset is designed to be used with the Hugging Face `datasets` library, which can load each subset using a specific configuration name.
 
-```python
-from datasets import load_dataset
 
-# Load the 'stones' subset
-stone_dataset = load_dataset("OpsiClear/stones", name="stones", split="train")
-print(f"Loaded {len(stone_dataset)} samples from the 'stones' subset.")
-print("First sample:", stone_dataset[0])
 
-# Load the 'dtu' subset
-dtu_dataset = load_dataset("OpsiClear/stones", name="dtu", split="train")
-print(f"Loaded {len(dtu_dataset)} samples from the 'dtu' subset.")
+To evaluate transparency using our method, see the official [NGS repository](https://github.com/OpsiClear/noise_guided_splatting)
 
-# To evaluate transparency using our method, see the official NGS repository:
-# (https://github.com/OpsiClear/noise_guided_splatting)
-````
 
 ## Licensing