v0.62.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.62.0 for changelog.
- README.md +57 -59
- release_assets.json +3 -3
README.md
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@@ -14,7 +14,7 @@ pipeline_tag: image-segmentation
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Mask R-CNN is a machine learning model that extends Faster R-CNN to perform instance segmentation by detecting objects in an image while simultaneously generating a high-quality segmentation mask for each instance. It adds a branch for predicting segmentation masks in parallel with the existing branch for bounding box recognition.
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This is based on the implementation of MaskRCNN found [here](https://github.com/pytorch/vision).
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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.
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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.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.
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For more device-specific assets and performance metrics, visit **[MaskRCNN on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/maskrcnn)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [MaskRCNN on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| proposal_generator | ONNX | float | Snapdragon® 8 Gen 3 Mobile |
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| proposal_generator | ONNX | float | Snapdragon® 8 Gen 1 Mobile |
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 |
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 92.
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| proposal_generator | ONNX | float | Qualcomm® QCS8450 |
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 |
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ Q-8750 |
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| proposal_generator | ONNX | float | Snapdragon® 8 Elite Mobile |
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| proposal_generator | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 41.
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| proposal_generator | QNN_DLC | float | Snapdragon® X2 Elite |
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| proposal_generator | QNN_DLC | float | Snapdragon® X Elite |
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 69.
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile |
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 127.
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float | Qualcomm®
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| proposal_generator | QNN_DLC | float |
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Elite Mobile |
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| roi_head | ONNX | float | Snapdragon® 8 Gen
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| roi_head | ONNX | float |
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| roi_head | ONNX | float | Qualcomm® Dragonwing™
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| roi_head | ONNX | float | Qualcomm®
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| roi_head | ONNX | float | Qualcomm®
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| roi_head | ONNX | float | Qualcomm® Dragonwing™
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| roi_head | ONNX | float |
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| roi_head | ONNX | float | Snapdragon® 8 Elite Mobile |
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| roi_head |
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| roi_head | QNN_DLC | float | Snapdragon®
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| roi_head | QNN_DLC | float | Snapdragon®
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| roi_head | QNN_DLC | float | Snapdragon® 8 Gen
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| roi_head | QNN_DLC | float |
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float | Qualcomm®
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| roi_head | QNN_DLC | float |
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| roi_head | QNN_DLC | float |
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| roi_head | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 112.298 ms | 21 - 511 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 82.119 ms | 15 - 515 MB | NPU
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## License
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* The license for the original implementation of MaskRCNN can be found
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Mask R-CNN is a machine learning model that extends Faster R-CNN to perform instance segmentation by detecting objects in an image while simultaneously generating a high-quality segmentation mask for each instance. It adds a branch for predicting segmentation masks in parallel with the existing branch for bounding box recognition.
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This is based on the implementation of MaskRCNN found [here](https://github.com/pytorch/vision).
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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/v0.62.0/src/qai_hub_models/models/maskrcnn) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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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.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.62.0/maskrcnn-onnx-float.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.62.0/maskrcnn-qnn_dlc-float.zip)
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For more device-specific assets and performance metrics, visit **[MaskRCNN on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/maskrcnn)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.0/src/qai_hub_models/models/maskrcnn) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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+
See our repository for [MaskRCNN on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.62.0/src/qai_hub_models/models/maskrcnn) for usage instructions.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| proposal_generator | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 70.231 ms | 0 - 2812 MB | NPU
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| proposal_generator | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 142.534 ms | 130 - 2863 MB | NPU
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 124.965 ms | 24 - 35 MB | NPU
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 92.531 ms | 123 - 199 MB | NPU
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| proposal_generator | ONNX | float | Qualcomm® QCS8450 | 142.534 ms | 130 - 2863 MB | NPU
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 119.396 ms | 7 - 17 MB | NPU
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| proposal_generator | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 52.601 ms | 127 - 1623 MB | NPU
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| proposal_generator | ONNX | float | Snapdragon® 8 Elite Mobile | 52.601 ms | 127 - 1623 MB | NPU
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| proposal_generator | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 41.473 ms | 126 - 1479 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® X2 Elite | 42.762 ms | 7 - 7 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® X Elite | 92.038 ms | 7 - 7 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 69.972 ms | 7 - 2330 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 147.799 ms | 8 - 2739 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 127.626 ms | 7 - 72 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 94.57 ms | 7 - 10 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® SA8775P | 122.238 ms | 1 - 1758 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® SA8650P | 122.238 ms | 1 - 1758 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® SA8255P | 122.238 ms | 1 - 1758 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® QCS8450 | 147.799 ms | 8 - 2739 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 122.505 ms | 7 - 71 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 92.038 ms | 7 - 7 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 53.247 ms | 0 - 1510 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® SA7255P | 353.632 ms | 2 - 1759 MB | NPU
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| proposal_generator | QNN_DLC | float | Qualcomm® SA8295P | 125.972 ms | 0 - 1430 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 53.247 ms | 0 - 1510 MB | NPU
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| proposal_generator | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 42.128 ms | 7 - 1789 MB | NPU
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| roi_head | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 72.432 ms | 244 - 718 MB | NPU
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| roi_head | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 138.03 ms | 234 - 680 MB | NPU
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| roi_head | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 154.653 ms | 108 - 208 MB | NPU
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| roi_head | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 87.331 ms | 271 - 273 MB | NPU
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| roi_head | ONNX | float | Qualcomm® QCS8450 | 138.03 ms | 234 - 680 MB | NPU
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| roi_head | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 109.801 ms | 112 - 211 MB | NPU
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| roi_head | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 62.278 ms | 226 - 623 MB | NPU
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| roi_head | ONNX | float | Snapdragon® 8 Elite Mobile | 62.278 ms | 226 - 623 MB | NPU
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| roi_head | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 50.521 ms | 190 - 588 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® X2 Elite | 89.841 ms | 52 - 52 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® X Elite | 231.039 ms | 52 - 52 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 159.1 ms | 10 - 795 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 295.243 ms | 39 - 787 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 243.435 ms | 52 - 107 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 224.388 ms | 51 - 52 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® SA8775P | 261.792 ms | 49 - 777 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® SA8650P | 261.792 ms | 49 - 777 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® SA8255P | 261.792 ms | 49 - 777 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® QCS8450 | 295.243 ms | 39 - 787 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 256.185 ms | 52 - 106 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 231.039 ms | 52 - 52 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 116.843 ms | 1 - 490 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® SA7255P | 560.942 ms | 31 - 534 MB | NPU
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| roi_head | QNN_DLC | float | Qualcomm® SA8295P | 287.976 ms | 49 - 769 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 116.843 ms | 1 - 490 MB | NPU
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| roi_head | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 82.518 ms | 13 - 513 MB | NPU
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## License
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* The license for the original implementation of MaskRCNN can be found
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release_assets.json
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{
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"version": "0.
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"precisions": {
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"float": {
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"universal_assets": {
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"qairt": "2.45.0.260326154327",
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"onnx_runtime": "1.27.1"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.
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},
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"qnn_dlc": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.
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}
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}
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}
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{
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"version": "0.62.0",
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"precisions": {
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"float": {
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"universal_assets": {
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"qairt": "2.45.0.260326154327",
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"onnx_runtime": "1.27.1"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.62.0/maskrcnn-onnx-float.zip"
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},
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"qnn_dlc": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/maskrcnn/releases/v0.62.0/maskrcnn-qnn_dlc-float.zip"
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}
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}
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}
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