Update DataReadme.md

DataReadme.md

@@ -71,10 +71,20 @@ For each galaxy, multi-band (u, g, r, i, z) cutouts of size 300×300 pixels (0.3
 Regression (predicting continuous redshift value from multi-band images).
 
 ### Total Samples
-41,650 galaxies.
+50,896 galaxies.
 
 ### Split
 - Training set: 10,100 samples  
-- Test set: 31,600 samples  
+- Test set: 40,796 samples  
 
-The split is performed using **redshift-stratified sampling** to ensure consistent redshift distributions between training and test sets.
+The split is performed using **redshift-stratified sampling** to ensure consistent redshift distributions between training and test sets.
+
+## 4. `lens-detection`: Gravitational Lens Detection (Object Detection)
+
+### Description
+This dataset is designed for **strong gravitational lens detection** in wide-field survey images. It likely consists of image cutouts from surveys such as DESI, LSST, or the Kilo-Degree Survey (KiDS), annotated with bounding boxes around candidate lens systems (e.g., Einstein rings, arcs).
+
+The dataset supports the **object detection** downstream task evaluated in the FAMA paper, where the model demonstrated significant gains over supervised baselines.
+
+### Task Type
+Object detection (localization + binary classification: lens vs. non-lens).