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README.md

@@ -30,14 +30,15 @@ More details on model performance across various devices, can be found
   - Input resolution: 1024x512
   - Number of parameters: 32.1M
   - Model size: 123 MB
+  - Number of output classes: 19
 
 
 
 
 | 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 | 6.446 ms | 1 - 3 MB | FP16 | NPU |  [FFNet-122NS-LowRes.tflite](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 6.982 ms | 6 - 31 MB | FP16 | NPU |  [FFNet-122NS-LowRes.so](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 6.447 ms | 1 - 3 MB | FP16 | NPU |  [FFNet-122NS-LowRes.tflite](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 6.994 ms | 6 - 31 MB | FP16 | NPU |  [FFNet-122NS-LowRes.so](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.so) 
 
 
 
@@ -100,8 +101,8 @@ python -m qai_hub_models.models.ffnet_122ns_lowres.export
 Profile Job summary of FFNet-122NS-LowRes
 --------------------------------------------------
 Device: SA8255 (Proxy) (13)
-Estimated Inference Time: 7.01 ms
-Estimated Peak Memory Range: 6.04-29.38 MB
+Estimated Inference Time: 6.99 ms
+Estimated Peak Memory Range: 6.03-31.56 MB
 Compute Units: NPU (348) | Total (348)