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README.md

@@ -34,10 +34,10 @@ More details on model performance across various devices, can be found
 
 | 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 | 0.807 ms | 0 - 2 MB | FP16 | NPU |  [MediaPipePoseDetector.tflite](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseDetector.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.023 ms | 0 - 3 MB | FP16 | NPU |  [MediaPipePoseLandmarkDetector.tflite](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseLandmarkDetector.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.865 ms | 0 - 63 MB | FP16 | NPU |  [MediaPipePoseDetector.so](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseDetector.so) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.101 ms | 0 - 142 MB | FP16 | NPU |  [MediaPipePoseLandmarkDetector.so](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseLandmarkDetector.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 0.806 ms | 0 - 2 MB | FP16 | NPU |  [MediaPipePoseDetector.tflite](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseDetector.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.052 ms | 0 - 3 MB | FP16 | NPU |  [MediaPipePoseLandmarkDetector.tflite](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseLandmarkDetector.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.808 ms | 0 - 5 MB | FP16 | NPU |  [MediaPipePoseDetector.so](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseDetector.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.063 ms | 0 - 3 MB | FP16 | NPU |  [MediaPipePoseLandmarkDetector.so](https://huggingface.co/qualcomm/MediaPipe-Pose-Estimation/blob/main/MediaPipePoseLandmarkDetector.so) 
 
 
 ## Installation
@@ -45,11 +45,10 @@ More details on model performance across various devices, can be found
 This model can be installed as a Python package via pip.
 
 ```bash
-pip install "qai-hub-models[mediapipe_pose]"
+pip install qai-hub-models
 ```
 
 
-
 ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
 
 Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
@@ -98,31 +97,31 @@ python -m qai_hub_models.models.mediapipe_pose.export
 ```
 Profile Job summary of MediaPipePoseDetector
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 0.81 ms
-Estimated Peak Memory Range: 0.03-1.57 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 0.58 ms
+Estimated Peak Memory Range: 0.06-37.81 MB
 Compute Units: NPU (106) | Total (106)
 
 Profile Job summary of MediaPipePoseLandmarkDetector
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 1.02 ms
-Estimated Peak Memory Range: 0.01-3.10 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 0.76 ms
+Estimated Peak Memory Range: 0.01-80.71 MB
 Compute Units: NPU (229) | Total (229)
 
 Profile Job summary of MediaPipePoseDetector
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 0.86 ms
-Estimated Peak Memory Range: 0.20-63.21 MB
-Compute Units: NPU (139) | Total (139)
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 0.58 ms
+Estimated Peak Memory Range: 0.06-38.15 MB
+Compute Units: NPU (106) | Total (106)
 
 Profile Job summary of MediaPipePoseLandmarkDetector
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 1.10 ms
-Estimated Peak Memory Range: 0.02-142.47 MB
-Compute Units: NPU (305) | Total (305)
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 0.77 ms
+Estimated Peak Memory Range: 0.01-80.47 MB
+Compute Units: NPU (229) | Total (229)
 
 
 ```
@@ -227,7 +226,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of MediaPipe-Pose-Estimation can be found
   [here](https://github.com/zmurez/MediaPipePyTorch/blob/master/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 compiled assets for on-device deployment can be found [here]({deploy_license_url})
 
 ## References
 * [BlazePose: On-device Real-time Body Pose tracking](https://arxiv.org/abs/2006.10204)