v0.65.0

See https://github.com/qualcomm/ai-hub-models/releases/v0.65.0 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/blob/v0.64.0/src/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/v0.65.0/src/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 2.50, ONNX Runtime 1.30.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fomm/releases/v0.64.0/fomm-onnx-float.zip)
+| ONNX | float | Universal | QAIRT 2.50, ONNX Runtime 1.30.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fomm/releases/v0.65.0/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/blob/v0.64.0/src/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/v0.65.0/src/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/blob/v0.64.0/src/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/v0.65.0/src/qai_hub_models/models/fomm) for usage instructions.
 
 ## Model Details
 
@@ -68,8 +68,6 @@ See our repository for [First-Order-Motion-Model on GitHub](https://github.com/q
 | detector | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 5.774 ms | 1 - 4 MB | NPU
 | detector | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 4.642 ms | 28 - 28 MB | NPU
 | detector | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 2.936 ms | 0 - 25 MB | NPU
-| detector | TFLITE | float | Qualcomm® SA8650P | 5.807 ms | 0 - 29 MB | NPU
-| detector | TFLITE | float | Qualcomm® SA8255P | 5.807 ms | 0 - 29 MB | NPU
 | generator | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 10.409 ms | 14 - 181 MB | NPU
 | generator | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 13.319 ms | 13 - 169 MB | NPU
 | generator | ONNX | float | Snapdragon® X2 Elite | 12.454 ms | 23 - 23 MB | NPU
@@ -82,8 +80,6 @@ See our repository for [First-Order-Motion-Model on GitHub](https://github.com/q
 | generator | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 32.995 ms | 17 - 21 MB | NPU
 | generator | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 22.412 ms | 89 - 89 MB | NPU
 | generator | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 13.319 ms | 13 - 169 MB | NPU
-| generator | TFLITE | float | Qualcomm® SA8650P | 545.416 ms | 19 - 37 MB | CPU
-| generator | TFLITE | float | Qualcomm® SA8255P | 545.416 ms | 19 - 37 MB | CPU
 
 ## License
 * The license for the original implementation of First-Order-Motion-Model can be found

release_assets.json

@@ -1,5 +1,5 @@
 {
-    "version": "0.64.0",
+    "version": "0.65.0",
     "precisions": {
         "float": {
             "universal_assets": {
@@ -8,7 +8,7 @@
                         "qairt": "2.50.0.260828221209",
                         "onnx_runtime": "1.30.0"
                     },
-                    "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fomm/releases/v0.64.0/fomm-onnx-float.zip"
+                    "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fomm/releases/v0.65.0/fomm-onnx-float.zip"
                 }
             }
         }