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YOLOv11-Segmentation

Image Segmentation
PyTorch
real_time
android
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metadata 
library_name: pytorch
license: other
tags:
  - real_time
  - android
pipeline_tag: image-segmentation

YOLOv11-Segmentation: Optimized for Qualcomm Devices

Ultralytics YOLOv11 is a machine learning model that predicts bounding boxes, segmentation masks and classes of objects in an image.

This is based on the implementation of YOLOv11-Segmentation 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

Due to licensing restrictions, we cannot distribute pre-exported model assets for this model. 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

See our repository for YOLOv11-Segmentation on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.semantic_segmentation

Model Stats:

  • Model checkpoint: YOLO11N-Seg
  • Input resolution: 640x640
  • Number of output classes: 80
  • Number of parameters: 2.89M
  • Model size (float): 11.1 MB
  • Model size (w8a16): 11.4 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
YOLOv11-Segmentation ONNX float Snapdragon® X Elite 6.416 ms 17 - 17 MB NPU
YOLOv11-Segmentation ONNX float Snapdragon® 8 Gen 3 Mobile 4.233 ms 2 - 206 MB NPU
YOLOv11-Segmentation ONNX float Qualcomm® QCS8550 (Proxy) 6.171 ms 11 - 15 MB NPU
YOLOv11-Segmentation ONNX float Qualcomm® QCS9075 8.053 ms 11 - 14 MB NPU
YOLOv11-Segmentation ONNX float Snapdragon® 8 Elite For Galaxy Mobile 3.491 ms 1 - 160 MB NPU
YOLOv11-Segmentation ONNX float Snapdragon® 8 Elite Gen 5 Mobile 3.043 ms 0 - 155 MB NPU
YOLOv11-Segmentation TFLITE float Snapdragon® 8 Gen 3 Mobile 3.147 ms 0 - 171 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® QCS8275 (Proxy) 15.466 ms 4 - 111 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® QCS8550 (Proxy) 4.342 ms 4 - 9 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® SA8775P 6.082 ms 4 - 113 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® QCS9075 5.829 ms 4 - 22 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® QCS8450 (Proxy) 10.084 ms 4 - 210 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® SA7255P 15.466 ms 4 - 111 MB NPU
YOLOv11-Segmentation TFLITE float Qualcomm® SA8295P 9.237 ms 4 - 177 MB NPU
YOLOv11-Segmentation TFLITE float Snapdragon® 8 Elite For Galaxy Mobile 2.39 ms 0 - 116 MB NPU
YOLOv11-Segmentation TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 1.957 ms 0 - 121 MB NPU

License

  • The license for the original implementation of YOLOv11-Segmentation can be found here.

References

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