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README.md

@@ -19,7 +19,7 @@ tags:
 
 MobileNet-v3-Large is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
 
-This model is an implementation of MobileNet-v3-Large found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py).
+This model is an implementation of MobileNet-v3-Large found [here]({source_repo}).
 This repository provides scripts to run MobileNet-v3-Large on Qualcomm® devices.
 More details on model performance across various devices, can be found
 [here](https://aihub.qualcomm.com/models/mobilenet_v3_large).
@@ -34,15 +34,32 @@ More details on model performance across various devices, can be found
   - Number of parameters: 5.47M
   - Model size: 20.9 MB
 
+| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
+|---|---|---|---|---|---|---|---|---|
+| MobileNet-v3-Large | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 0.987 ms | 0 - 37 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 1.051 ms | 1 - 5 MB | FP16 | NPU | [MobileNet-v3-Large.so](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.so) |
+| MobileNet-v3-Large | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 0.993 ms | 1 - 2 MB | FP16 | NPU | [MobileNet-v3-Large.onnx](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.onnx) |
+| MobileNet-v3-Large | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 0.698 ms | 0 - 65 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 0.732 ms | 1 - 19 MB | FP16 | NPU | [MobileNet-v3-Large.so](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.so) |
+| MobileNet-v3-Large | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 0.722 ms | 0 - 66 MB | FP16 | NPU | [MobileNet-v3-Large.onnx](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.onnx) |
+| MobileNet-v3-Large | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 0.987 ms | 0 - 1 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 1.001 ms | 1 - 2 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 0.986 ms | 0 - 242 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | SA8255 (Proxy) | SA8255P Proxy | QNN | 1.003 ms | 1 - 2 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | SA8775 (Proxy) | SA8775P Proxy | TFLITE | 0.991 ms | 0 - 2 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | SA8775 (Proxy) | SA8775P Proxy | QNN | 0.994 ms | 1 - 2 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 0.989 ms | 0 - 246 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | SA8650 (Proxy) | SA8650P Proxy | QNN | 1.0 ms | 1 - 2 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 1.385 ms | 0 - 67 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 1.473 ms | 1 - 23 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 0.679 ms | 0 - 25 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) |
+| MobileNet-v3-Large | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 0.71 ms | 1 - 15 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 0.734 ms | 0 - 27 MB | FP16 | NPU | [MobileNet-v3-Large.onnx](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.onnx) |
+| MobileNet-v3-Large | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 1.166 ms | 1 - 1 MB | FP16 | NPU | Use Export Script |
+| MobileNet-v3-Large | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 1.072 ms | 13 - 13 MB | FP16 | NPU | [MobileNet-v3-Large.onnx](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.onnx) |
 
 
 
-| 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 | 0.996 ms | 0 - 2 MB | FP16 | NPU |  [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.044 ms | 1 - 274 MB | FP16 | NPU |  [MobileNet-v3-Large.so](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.so) 
-
-
 
 ## Installation
 
@@ -97,16 +114,16 @@ device. This script does the following:
 ```bash
 python -m qai_hub_models.models.mobilenet_v3_large.export
 ```
-
 ```
-Profile Job summary of MobileNet-v3-Large
---------------------------------------------------
-Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 1.17 ms
-Estimated Peak Memory Range: 0.57-0.57 MB
-Compute Units: NPU (144) | Total (144)
-
-
+Profiling Results
+------------------------------------------------------------
+MobileNet-v3-Large
+Device                          : Samsung Galaxy S23 (13)
+Runtime                         : TFLITE                 
+Estimated inference time (ms)   : 1.0                    
+Estimated peak memory usage (MB): [0, 37]                
+Total # Ops                     : 128                    
+Compute Unit(s)                 : NPU (128 ops)          
 ```
 
 
@@ -205,15 +222,19 @@ provides instructions on how to use the `.so` shared library  in an Android appl
 Get more details on MobileNet-v3-Large's performance across various devices [here](https://aihub.qualcomm.com/models/mobilenet_v3_large).
 Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 
+
 ## License
-- The license for the original implementation of MobileNet-v3-Large can be found
-  [here](https://github.com/pytorch/vision/blob/main/LICENSE).
-- The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
+* The license for the original implementation of MobileNet-v3-Large can be found [here](https://github.com/pytorch/vision/blob/main/LICENSE).
+* The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
+
+
 
 ## References
 * [Searching for MobileNetV3](https://arxiv.org/abs/1905.02244)
 * [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py)
 
+
+
 ## Community
 * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
 * For questions or feedback please [reach out to us](mailto:[email protected]).