YOLOv8-Segmentation: Optimized for Qualcomm Devices
Ultralytics YOLOv8 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 YOLOv8-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 YOLOv8-Segmentation on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.semantic_segmentation
Model Stats:
- Model checkpoint: YOLOv8N-Seg
- Input resolution: 640x640
- Number of output classes: 80
- Number of parameters: 3.43M
- Model size (float): 13.2 MB
- Model size (w8a16): 3.91 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| YOLOv8-Segmentation | ONNX | float | Snapdragon® X2 Elite | 3.422 ms | 16 - 16 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Snapdragon® X Elite | 6.888 ms | 17 - 17 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.045 ms | 14 - 288 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Qualcomm® QCS8550 (Proxy) | 6.355 ms | 12 - 19 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Qualcomm® QCS9075 | 7.778 ms | 15 - 18 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.317 ms | 2 - 227 MB | NPU |
| YOLOv8-Segmentation | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.956 ms | 0 - 233 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Snapdragon® X2 Elite | 2.737 ms | 5 - 5 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Snapdragon® X Elite | 4.84 ms | 5 - 5 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 3.331 ms | 5 - 216 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 16.901 ms | 1 - 180 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 4.483 ms | 5 - 6 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® SA8775P | 6.307 ms | 1 - 183 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® QCS9075 | 6.057 ms | 5 - 15 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 9.893 ms | 5 - 196 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® SA7255P | 16.901 ms | 1 - 180 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Qualcomm® SA8295P | 9.217 ms | 0 - 166 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.65 ms | 5 - 190 MB | NPU |
| YOLOv8-Segmentation | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.912 ms | 4 - 190 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.939 ms | 0 - 114 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 16.141 ms | 4 - 84 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.946 ms | 4 - 9 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® SA8775P | 5.846 ms | 4 - 90 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® QCS9075 | 5.771 ms | 4 - 23 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 8.894 ms | 4 - 208 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® SA7255P | 16.141 ms | 4 - 84 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Qualcomm® SA8295P | 8.606 ms | 4 - 174 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.24 ms | 0 - 89 MB | NPU |
| YOLOv8-Segmentation | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.767 ms | 0 - 102 MB | NPU |
License
- The license for the original implementation of YOLOv8-Segmentation can be found here.
References
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.