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README.md

@@ -30,14 +30,15 @@ More details on model performance across various devices, can be found
   - Input resolution: 224x224
   - Number of parameters: 32.9M
   - Model size: 126 MB
+  - Number of output classes: 21
 
 
 
 
 | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
 | ---|---|---|---|---|---|---|---|
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 42.095 ms | 21 - 24 MB | FP16 | NPU |  [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 42.393 ms | 3 - 20 MB | FP16 | NPU |  [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 42.457 ms | 21 - 24 MB | FP16 | NPU |  [FCN-ResNet50.tflite](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 42.386 ms | 3 - 21 MB | FP16 | NPU |  [FCN-ResNet50.so](https://huggingface.co/qualcomm/FCN-ResNet50/blob/main/FCN-ResNet50.so) 
 
 
 
@@ -99,8 +100,8 @@ python -m qai_hub_models.models.fcn_resnet50.export
 Profile Job summary of FCN-ResNet50
 --------------------------------------------------
 Device: SA8255 (Proxy) (13)
-Estimated Inference Time: 42.54 ms
-Estimated Peak Memory Range: 3.04-19.53 MB
+Estimated Inference Time: 42.56 ms
+Estimated Peak Memory Range: 3.06-19.48 MB
 Compute Units: NPU (127) | Total (127)