v0.50.1

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

README.md

@@ -14,7 +14,7 @@ pipeline_tag: image-segmentation
 The Fast Segment Anything Model (FastSAM) is a novel, real-time CNN-based solution for the Segment Anything task. This task is designed to segment any object within an image based on various possible user interaction prompts. The model performs competitively despite significantly reduced computation, making it a practical choice for a variety of vision tasks.
 
 This is based on the implementation of FastSam-S found [here](https://github.com/CASIA-IVA-Lab/FastSAM).
-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/fastsam_s) 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/fastsam_s) 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.
 
@@ -27,23 +27,23 @@ 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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-tflite-float.zip)
 
 For more device-specific assets and performance metrics, visit **[FastSam-S on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/fastsam_s)**.
 
 
 ### 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/fastsam_s) 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/fastsam_s) 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 [FastSam-S on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/fastsam_s) for usage instructions.
+See our repository for [FastSam-S on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/fastsam_s) 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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.0/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-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/fastsam_s/releases/v0.50.1/fastsam_s-onnx-float.zip"}}}}}