Update README.md

README.md

@@ -140,6 +140,10 @@ Each material in the dataset comes with rich metadata, including information on
 and, when available, descriptions and physical size. 
 This comprehensive metadata facilitates precise material selection and usage, catering to the specific needs of users.
 
+<center>
+  <img src="https://gvecchio.com/matsynth/static/images/data.png" style="border-radius:10px">
+</center>
+
 ## 📂 Dataset Structure
  
 The MatSynth dataset is divided into two splits: the test split, containing 89 materials, and the train split, consisting of 3,980 materials. 
@@ -182,14 +186,32 @@ presented as the length of the edge in centimeters (358).
 ## 🧑‍💻 Usage
 
 MatSynth is accessible through the datasets python library.
+Following a usage example:
 
 ```python
 from datasets import load_dataset
+from torch.utils.data import DataLoader
 
+# load the dataset in streaming mode
 ds = load_dataset(
     "gvecchio/MatSynth", 
     streaming = True,
 )
+
+# remove unnecessary columns to reduce downloaded data
+ds = ds.remove_columns(["diffuse", "specular", "displacement", "opacity", "blend_mask"])
+# keep only specified columns
+ds = ds.select_columns(["basecolor", "normal", "roughness", " metallic"])
+
+# filter data matching a specific criteria, e.g.: only CC0 materials
+ds = ds.filter(lambda x: x["metadata"]["license"] == "CC0")
+
+# shuffle data
+ds = ds.shuffle(buffer_size=100)
+
+# set format for usage in torch
+ds = ds.with_format("torch")
+dl = DataLoader(ds, batch_size=8)
 ```
 
 ## 📜 Citation