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
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:

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

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
proposal_generator	QNN_DLC	float	Snapdragon® X2 Elite	42.554 ms	7 - 7 MB	NPU
proposal_generator	QNN_DLC	float	Snapdragon® X Elite	91.369 ms	7 - 7 MB	NPU
proposal_generator	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	70.212 ms	7 - 2326 MB	NPU
proposal_generator	QNN_DLC	float	Snapdragon® 8 Gen 1 Mobile	151.831 ms	7 - 2736 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8275	354.445 ms	2 - 1759 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	94.473 ms	7 - 24 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® SA8775P	122.283 ms	2 - 1759 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® SA8650P	122.283 ms	2 - 1759 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® SA8255P	122.283 ms	2 - 1759 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® QCS8450	151.831 ms	7 - 2736 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-9075	122.578 ms	7 - 71 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-X7181	91.369 ms	7 - 7 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® Dragonwing™ Q-8750	53.816 ms	12 - 1523 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® SA7255P	354.445 ms	2 - 1759 MB	NPU
proposal_generator	QNN_DLC	float	Qualcomm® SA8295P	125.987 ms	0 - 1430 MB	NPU
proposal_generator	QNN_DLC	float	Snapdragon® 8 Elite Mobile	53.816 ms	12 - 1523 MB	NPU
proposal_generator	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	42.27 ms	7 - 1789 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® X2 Elite	98.312 ms	52 - 52 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® X Elite	257.611 ms	52 - 52 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	177.662 ms	49 - 897 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® 8 Gen 1 Mobile	300.661 ms	0 - 918 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8275	573.44 ms	30 - 725 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	243.427 ms	52 - 679 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® SA8775P	270.285 ms	49 - 925 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® SA8650P	270.285 ms	49 - 925 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® SA8255P	270.285 ms	49 - 925 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® QCS8450	300.661 ms	0 - 918 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-9075	279.963 ms	52 - 106 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-X7181	257.611 ms	52 - 52 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® Dragonwing™ Q-8750	125.217 ms	34 - 726 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® SA7255P	573.44 ms	30 - 725 MB	NPU
roi_head	QNN_DLC	float	Qualcomm® SA8295P	306.965 ms	49 - 847 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® 8 Elite Mobile	125.217 ms	34 - 726 MB	NPU
roi_head	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	92.646 ms	13 - 719 MB	NPU

License

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

References

• Mask R-CNN
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.