v0.50.0

See https://github.com/qualcomm/ai-hub-models/releases/v0.50.0 for changelog.

README.md

@@ -14,7 +14,7 @@ pipeline_tag: image-to-video
 FOMM is a machine learning model that animates a still image to mirror the movements from a target video.
 
 This is based on the implementation of First-Order-Motion-Model found [here](https://github.com/AliaksandrSiarohin/first-order-model/tree/master).
-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/tree/v0.49.1/qai_hub_models/models/fomm) 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/qai_hub_models/models/fomm) 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.
 
@@ -27,21 +27,21 @@ 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/fomm/releases/v0.49.1/fomm-onnx-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/fomm/releases/v0.50.0/fomm-onnx-float.zip)
 
 For more device-specific assets and performance metrics, visit **[First-Order-Motion-Model on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/fomm)**.
 
 
 ### Option 2: Export with Custom Configurations
 
-Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/fomm) 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/qai_hub_models/models/fomm) 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 [First-Order-Motion-Model on GitHub](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/fomm) for usage instructions.
+See our repository for [First-Order-Motion-Model on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/fomm) for usage instructions.
 
 ## Model Details
 
@@ -50,24 +50,24 @@ See our repository for [First-Order-Motion-Model on GitHub](https://github.com/q
 **Model Stats:**
 - Model checkpoint: vox-256
 - Input resolution: 256x256
-- Model size (FOMMDetector) (float): 54.2 MB
-- Model size (FOMMGenerator) (float): 174 MB
+- Model size (detector) (float): 54.2 MB
+- Model size (generator) (float): 174 MB
 
 ## Performance Summary
 | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
 |---|---|---|---|---|---|---
-| FOMMDetector | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.75 ms | 0 - 24 MB | NPU
-| FOMMDetector | ONNX | float | Snapdragon® X2 Elite | 2.777 ms | 28 - 28 MB | NPU
-| FOMMDetector | ONNX | float | Snapdragon® X Elite | 4.579 ms | 27 - 27 MB | NPU
-| FOMMDetector | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.275 ms | 0 - 32 MB | NPU
-| FOMMDetector | ONNX | float | Qualcomm® QCS9075 | 5.8 ms | 1 - 4 MB | NPU
-| FOMMDetector | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.925 ms | 0 - 21 MB | NPU
-| FOMMGenerator | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 10.76 ms | 0 - 196 MB | NPU
-| FOMMGenerator | ONNX | float | Snapdragon® X2 Elite | 12.262 ms | 91 - 91 MB | NPU
-| FOMMGenerator | ONNX | float | Snapdragon® X Elite | 29.148 ms | 89 - 89 MB | NPU
-| FOMMGenerator | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 17.31 ms | 3 - 222 MB | NPU
-| FOMMGenerator | ONNX | float | Qualcomm® QCS9075 | 34.708 ms | 18 - 22 MB | NPU
-| FOMMGenerator | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 13.265 ms | 8 - 196 MB | NPU
+| detector | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.75 ms | 0 - 24 MB | NPU
+| detector | ONNX | float | Snapdragon® X2 Elite | 2.777 ms | 28 - 28 MB | NPU
+| detector | ONNX | float | Snapdragon® X Elite | 4.579 ms | 27 - 27 MB | NPU
+| detector | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.275 ms | 0 - 32 MB | NPU
+| detector | ONNX | float | Qualcomm® QCS9075 | 5.8 ms | 1 - 4 MB | NPU
+| detector | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.925 ms | 0 - 21 MB | NPU
+| generator | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 10.76 ms | 0 - 196 MB | NPU
+| generator | ONNX | float | Snapdragon® X2 Elite | 12.262 ms | 91 - 91 MB | NPU
+| generator | ONNX | float | Snapdragon® X Elite | 29.148 ms | 89 - 89 MB | NPU
+| generator | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 17.31 ms | 3 - 222 MB | NPU
+| generator | ONNX | float | Qualcomm® QCS9075 | 34.708 ms | 18 - 22 MB | NPU
+| generator | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 13.265 ms | 8 - 196 MB | NPU
 
 ## License
 * The license for the original implementation of First-Order-Motion-Model can be found

release_assets.json

@@ -0,0 +1 @@
+{"version":"0.50.0","precisions":{"float":{"universal_assets":{"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/fomm/releases/v0.50.0/fomm-onnx-float.zip"}}}}}