Hugging Peers

MaskRCNN

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by Qualcomm-AI-Hub image-segmentation bsd-3-clause
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Model card

MaskRCNN: Optimized for Qualcomm Devices

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.

This is based on the implementation of MaskRCNN found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime Precision Chipset SDK Versions Download
ONNX float Universal QAIRT 2.45, ONNX Runtime 1.27.1 Download
QNN_DLC float Universal QAIRT 2.45 Download

For more device-specific assets and performance metrics, visit MaskRCNN on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models 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 MaskRCNN on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.semantic_segmentation

Model Stats:

  • Input resolution: 800x800
  • Model checkpoint: Mask R-CNN ResNet-50 FPN V2
  • Model size (float): 177 MB
  • Number of output classes: 91
  • Number of parameters: 46.4M

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
proposal_generator ONNX float Snapdragon® 8 Gen 3 Mobile 70.231 ms 0 - 2812 MB NPU
proposal_generator ONNX float Snapdragon® 8 Gen 1 Mobile 142.534 ms 130 - 2863 MB NPU
proposal_generator ONNX float Qualcomm® Dragonwing™ IQ-8275 124.965 ms 24 - 35 MB NPU
proposal_generator ONNX float Qualcomm® Dragonwing™ QCS8550 (Proxy) 92.531 ms 123 - 199 MB NPU
proposal_generator ONNX float Qualcomm® QCS8450 142.534 ms 130 - 2863 MB NPU
proposal_generator ONNX float Qualcomm® Dragonwing™ IQ-9075 119.396 ms 7 - 17 MB NPU
proposal_generator ONNX float Qualcomm® Dragonwing™ Q-8750 52.601 ms 127 - 1623 MB NPU
proposal_generator ONNX float Snapdragon® 8 Elite Mobile 52.601 ms 127 - 1623 MB NPU
proposal_generator ONNX float Snapdragon® 8 Elite Gen 5 Mobile 41.473 ms 126 - 1479 MB NPU
proposal_generator QNN_DLC float Snapdragon® X2 Elite 42.762 ms 7 - 7 MB NPU
proposal_generator QNN_DLC float Snapdragon® X Elite 92.038 ms 7 - 7 MB NPU
proposal_generator QNN_DLC float Snapdragon® 8 Gen 3 Mobile 69.972 ms 7 - 2330 MB NPU
proposal_generator QNN_DLC float Snapdragon® 8 Gen 1 Mobile 147.799 ms 8 - 2739 MB NPU
proposal_generator QNN_DLC float Qualcomm® Dragonwing™ IQ-8275 127.626 ms 7 - 72 MB NPU
proposal_generator QNN_DLC float Qualcomm® Dragonwing™ QCS8550 (Proxy) 94.57 ms 7 - 10 MB NPU
proposal_generator QNN_DLC float Qualcomm® SA8775P 122.238 ms 1 - 1758 MB NPU
proposal_generator QNN_DLC float Qualcomm® SA8650P 122.238 ms 1 - 1758 MB NPU
proposal_generator QNN_DLC float Qualcomm® SA8255P 122.238 ms 1 - 1758 MB NPU
proposal_generator QNN_DLC float Qualcomm® QCS8450 147.799 ms 8 - 2739 MB NPU
proposal_generator QNN_DLC float Qualcomm® Dragonwing™ IQ-9075 122.505 ms 7 - 71 MB NPU
proposal_generator QNN_DLC float Qualcomm® Dragonwing™ IQ-X7181 92.038 ms 7 - 7 MB NPU
proposal_generator QNN_DLC float Qualcomm® Dragonwing™ Q-8750 53.247 ms 0 - 1510 MB NPU
proposal_generator QNN_DLC float Qualcomm® SA7255P 353.632 ms 2 - 1759 MB NPU
proposal_generator QNN_DLC float Qualcomm® SA8295P 125.972 ms 0 - 1430 MB NPU
proposal_generator QNN_DLC float Snapdragon® 8 Elite Mobile 53.247 ms 0 - 1510 MB NPU
proposal_generator QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 42.128 ms 7 - 1789 MB NPU
roi_head ONNX float Snapdragon® 8 Gen 3 Mobile 72.432 ms 244 - 718 MB NPU
roi_head ONNX float Snapdragon® 8 Gen 1 Mobile 138.03 ms 234 - 680 MB NPU
roi_head ONNX float Qualcomm® Dragonwing™ IQ-8275 154.653 ms 108 - 208 MB NPU
roi_head ONNX float Qualcomm® Dragonwing™ QCS8550 (Proxy) 87.331 ms 271 - 273 MB NPU
roi_head ONNX float Qualcomm® QCS8450 138.03 ms 234 - 680 MB NPU
roi_head ONNX float Qualcomm® Dragonwing™ IQ-9075 109.801 ms 112 - 211 MB NPU
roi_head ONNX float Qualcomm® Dragonwing™ Q-8750 62.278 ms 226 - 623 MB NPU
roi_head ONNX float Snapdragon® 8 Elite Mobile 62.278 ms 226 - 623 MB NPU
roi_head ONNX float Snapdragon® 8 Elite Gen 5 Mobile 50.521 ms 190 - 588 MB NPU
roi_head QNN_DLC float Snapdragon® X2 Elite 89.841 ms 52 - 52 MB NPU
roi_head QNN_DLC float Snapdragon® X Elite 231.039 ms 52 - 52 MB NPU
roi_head QNN_DLC float Snapdragon® 8 Gen 3 Mobile 159.1 ms 10 - 795 MB NPU
roi_head QNN_DLC float Snapdragon® 8 Gen 1 Mobile 295.243 ms 39 - 787 MB NPU
roi_head QNN_DLC float Qualcomm® Dragonwing™ IQ-8275 243.435 ms 52 - 107 MB NPU
roi_head QNN_DLC float Qualcomm® Dragonwing™ QCS8550 (Proxy) 224.388 ms 51 - 52 MB NPU
roi_head QNN_DLC float Qualcomm® SA8775P 261.792 ms 49 - 777 MB NPU
roi_head QNN_DLC float Qualcomm® SA8650P 261.792 ms 49 - 777 MB NPU
roi_head QNN_DLC float Qualcomm® SA8255P 261.792 ms 49 - 777 MB NPU
roi_head QNN_DLC float Qualcomm® QCS8450 295.243 ms 39 - 787 MB NPU
roi_head QNN_DLC float Qualcomm® Dragonwing™ IQ-9075 256.185 ms 52 - 106 MB NPU
roi_head QNN_DLC float Qualcomm® Dragonwing™ IQ-X7181 231.039 ms 52 - 52 MB NPU
roi_head QNN_DLC float Qualcomm® Dragonwing™ Q-8750 116.843 ms 1 - 490 MB NPU
roi_head QNN_DLC float Qualcomm® SA7255P 560.942 ms 31 - 534 MB NPU
roi_head QNN_DLC float Qualcomm® SA8295P 287.976 ms 49 - 769 MB NPU
roi_head QNN_DLC float Snapdragon® 8 Elite Mobile 116.843 ms 1 - 490 MB NPU
roi_head QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 82.518 ms 13 - 513 MB NPU

License

  • The license for the original implementation of MaskRCNN can be found here.

References

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