v0.50.1

See https://github.com/qualcomm/ai-hub-models/releases/v0.50.1 for changelog.

README.md

@@ -15,7 +15,7 @@ pipeline_tag: image-segmentation
 Transformer based encoder-decoder where prompts specify what to segment in an image thereby allowing segmentation without the need for additional training. The image encoder generates embeddings and the lightweight decoder operates on the embeddings for point and mask based image segmentation.
 
 This is based on the implementation of MobileSam found [here](https://github.com/facebookresearch/segment-anything).
-This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/mobilesam) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
+This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/mobilesam) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
 
 Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
 
@@ -28,23 +28,23 @@ Below are pre-exported model assets ready for deployment.
 
 | Runtime | Precision | Chipset | SDK Versions | Download |
 |---|---|---|---|---|
-| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-onnx-float.zip)
-| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-qnn_dlc-float.zip)
-| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-tflite-float.zip)
+| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-onnx-float.zip)
+| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-qnn_dlc-float.zip)
+| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-tflite-float.zip)
 
 For more device-specific assets and performance metrics, visit **[MobileSam on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/mobilesam)**.
 
 
 ### Option 2: Export with Custom Configurations
 
-Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/mobilesam) Python library to compile and export the model with your own:
+Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/mobilesam) Python library to compile and export the model with your own:
 - Custom weights (e.g., fine-tuned checkpoints)
 - Custom input shapes
 - Target device and runtime configurations
 
 This option is ideal if you need to customize the model beyond the default configuration provided here.
 
-See our repository for [MobileSam on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/mobilesam) for usage instructions.
+See our repository for [MobileSam on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/mobilesam) for usage instructions.
 
 ## Model Details
 

release_assets.json

@@ -1 +1 @@
-{"version":"0.50.0","precisions":{"float":{"universal_assets":{"tflite":{"tool_versions":{"qairt":"2.43.0.260127150333_193827","tflite":"2.17.0"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-tflite-float.zip"},"qnn_dlc":{"tool_versions":{"qairt":"2.43.0.260127150333_193827"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-qnn_dlc-float.zip"},"onnx":{"tool_versions":{"qairt":"2.42.0.251225135753_193295","onnx_runtime":"1.24.1"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.0/mobilesam-onnx-float.zip"}}}}}
+{"version":"0.50.1","precisions":{"float":{"universal_assets":{"tflite":{"tool_versions":{"qairt":"2.43.0.260127150333_193827","tflite":"2.17.0"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-tflite-float.zip"},"qnn_dlc":{"tool_versions":{"qairt":"2.43.0.260127150333_193827"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-qnn_dlc-float.zip"},"onnx":{"tool_versions":{"qairt":"2.42.0.251225135753_193295","onnx_runtime":"1.24.1"},"download_url":"https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mobilesam/releases/v0.50.1/mobilesam-onnx-float.zip"}}}}}