Update README.md

README.md

@@ -65,24 +65,39 @@ Dataset split:
 
 ## Model Architecture
 
-The project uses **EfficientNet-B0** as the backbone network.
-
-Pipeline:
+The project uses a two-stage pipeline:
 
 ```text
 Image
  ↓
-Image Processor
+DETR Object Detector
+ ↓
+Cat Detection
  ↓
 EfficientNet-B0
  ↓
 Classification Head
  ↓
-Syrnyk / Other Cat
+Naughty Cat / Other Cat
 ```
 
-The model was trained using transfer learning.
+### Stage 1: Object Detection
+
+The system first uses **DETR (DEtection TRansformer)** (`facebook/detr-resnet-50`) to determine whether a cat is present in the image.
+
+Possible outcomes:
 
+- Cat detected → continue to classification
+- No cat detected → return a warning message
+
+### Stage 2: Cat Classification
+
+If a cat is detected, the image is passed to an **EfficientNet-B0** classifier trained using transfer learning.
+
+The classifier predicts one of two classes:
+
+- Naughty Cat
+- Other Cat
 ---
 
 ## Results