Update README.md

README.md

@@ -42,4 +42,37 @@ The dataset is split using a **class-wise stratified approach** to ensure balanc
 | Val   | 23,952        | 15,738             |21,042        | `val/`  |
 | Test  | 18,492        | 10,278             |12,819        | `test/` |
 
-Each split contains separate folders for annotations and images: `train/`, `val/`, `test/`
+Each split contains separate folders for annotations and images: `train/`, `val/`, `test/`
+
+## Extracting Images from Parquet Files
+
+The dataset stores all images in Parquet format as raw bytes. To convert these bytes back into .png images, you can use the following Python code:
+
+```python
+import pandas as pd
+from PIL import Image
+import io
+import os
+
+# Load Parquet
+train_df = pd.read_parquet("train/train.parquet")
+
+# Directory to save images
+output_dir = "train/images"
+os.makedirs(output_dir, exist_ok=True)
+
+# Loop over all rows
+for idx, row in train_df.iterrows():
+    imagename = row['image_name']
+    image_bytes = row['image']
+
+    # Convert bytes to PIL Image
+    img = Image.open(io.BytesIO(image_bytes))
+
+    # Save image as PNG
+    save_path = os.path.join(output_dir, f"{imagename}")
+    img.save(save_path)
+```
+### Note:
+*  This will create a folder ```train/images/``` and save all images as ```.png```.
+* You can modify the path if your Parquet file is in a different location or if you want to save images elsewhere.