YOLOv8-Segmentation: Optimized for Mobile Deployment

Real-time object segmentation optimized for mobile and edge by Ultralytics

Ultralytics YOLOv8 is a machine learning model that predicts bounding boxes, segmentation masks and classes of objects in an image.

This model is an implementation of YOLOv8-Segmentation found here.

More details on model performance across various devices, can be found here.

Model Details

  • Model Type: Model_use_case.semantic_segmentation
  • Model Stats:
    • Model checkpoint: YOLOv8N-Seg
    • Input resolution: 640x640
    • Number of parameters: 3.43M
    • Number of output classes: 80
    • Model size (float): 13.2 MB
Model Precision Device Chipset Target Runtime Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit Target Model
YOLOv8-Segmentation float QCS8275 (Proxy) Qualcomm® QCS8275 (Proxy) TFLITE 21.457 ms 4 - 65 MB NPU --
YOLOv8-Segmentation float QCS8275 (Proxy) Qualcomm® QCS8275 (Proxy) QNN 17.55 ms 1 - 10 MB NPU --
YOLOv8-Segmentation float QCS8450 (Proxy) Qualcomm® QCS8450 (Proxy) TFLITE 11.511 ms 4 - 48 MB NPU --
YOLOv8-Segmentation float QCS8450 (Proxy) Qualcomm® QCS8450 (Proxy) QNN 10.852 ms 5 - 45 MB NPU --
YOLOv8-Segmentation float QCS8550 (Proxy) Qualcomm® QCS8550 (Proxy) TFLITE 8.271 ms 4 - 23 MB NPU --
YOLOv8-Segmentation float QCS8550 (Proxy) Qualcomm® QCS8550 (Proxy) QNN 5.053 ms 5 - 7 MB NPU --
YOLOv8-Segmentation float QCS9075 (Proxy) Qualcomm® QCS9075 (Proxy) TFLITE 10.3 ms 4 - 65 MB NPU --
YOLOv8-Segmentation float QCS9075 (Proxy) Qualcomm® QCS9075 (Proxy) QNN 6.738 ms 1 - 13 MB NPU --
YOLOv8-Segmentation float SA7255P ADP Qualcomm® SA7255P TFLITE 21.457 ms 4 - 65 MB NPU --
YOLOv8-Segmentation float SA7255P ADP Qualcomm® SA7255P QNN 17.55 ms 1 - 10 MB NPU --
YOLOv8-Segmentation float SA8255 (Proxy) Qualcomm® SA8255P (Proxy) TFLITE 8.171 ms 4 - 26 MB NPU --
YOLOv8-Segmentation float SA8255 (Proxy) Qualcomm® SA8255P (Proxy) QNN 5.118 ms 5 - 7 MB NPU --
YOLOv8-Segmentation float SA8295P ADP Qualcomm® SA8295P TFLITE 12.714 ms 4 - 36 MB NPU --
YOLOv8-Segmentation float SA8295P ADP Qualcomm® SA8295P QNN 9.205 ms 0 - 17 MB NPU --
YOLOv8-Segmentation float SA8650 (Proxy) Qualcomm® SA8650P (Proxy) TFLITE 8.261 ms 4 - 28 MB NPU --
YOLOv8-Segmentation float SA8650 (Proxy) Qualcomm® SA8650P (Proxy) QNN 5.073 ms 5 - 7 MB NPU --
YOLOv8-Segmentation float SA8775P ADP Qualcomm® SA8775P TFLITE 10.3 ms 4 - 65 MB NPU --
YOLOv8-Segmentation float SA8775P ADP Qualcomm® SA8775P QNN 6.738 ms 1 - 13 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S23 Snapdragon® 8 Gen 2 Mobile TFLITE 8.134 ms 4 - 29 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S23 Snapdragon® 8 Gen 2 Mobile QNN 4.953 ms 0 - 26 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S23 Snapdragon® 8 Gen 2 Mobile ONNX 6.511 ms 0 - 82 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S24 Snapdragon® 8 Gen 3 Mobile TFLITE 5.93 ms 3 - 71 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S24 Snapdragon® 8 Gen 3 Mobile QNN 3.509 ms 5 - 191 MB NPU --
YOLOv8-Segmentation float Samsung Galaxy S24 Snapdragon® 8 Gen 3 Mobile ONNX 4.64 ms 6 - 198 MB NPU --
YOLOv8-Segmentation float Snapdragon 8 Elite QRD Snapdragon® 8 Elite Mobile TFLITE 5.537 ms 3 - 66 MB NPU --
YOLOv8-Segmentation float Snapdragon 8 Elite QRD Snapdragon® 8 Elite Mobile QNN 3.185 ms 5 - 132 MB NPU --
YOLOv8-Segmentation float Snapdragon 8 Elite QRD Snapdragon® 8 Elite Mobile ONNX 4.327 ms 5 - 135 MB NPU --
YOLOv8-Segmentation float Snapdragon X Elite CRD Snapdragon® X Elite QNN 5.416 ms 5 - 5 MB NPU --
YOLOv8-Segmentation float Snapdragon X Elite CRD Snapdragon® X Elite ONNX 7.119 ms 17 - 17 MB NPU --
YOLOv8-Segmentation w8a16 QCS8275 (Proxy) Qualcomm® QCS8275 (Proxy) QNN 9.0 ms 1 - 11 MB NPU --
YOLOv8-Segmentation w8a16 QCS8450 (Proxy) Qualcomm® QCS8450 (Proxy) QNN 6.154 ms 2 - 51 MB NPU --
YOLOv8-Segmentation w8a16 QCS8550 (Proxy) Qualcomm® QCS8550 (Proxy) QNN 4.576 ms 2 - 5 MB NPU --
YOLOv8-Segmentation w8a16 QCS9075 (Proxy) Qualcomm® QCS9075 (Proxy) QNN 5.168 ms 1 - 13 MB NPU --
YOLOv8-Segmentation w8a16 RB3 Gen 2 (Proxy) Qualcomm® QCS6490 (Proxy) QNN 20.693 ms 2 - 16 MB NPU --
YOLOv8-Segmentation w8a16 SA7255P ADP Qualcomm® SA7255P QNN 9.0 ms 1 - 11 MB NPU --
YOLOv8-Segmentation w8a16 SA8255 (Proxy) Qualcomm® SA8255P (Proxy) QNN 4.558 ms 2 - 12 MB NPU --
YOLOv8-Segmentation w8a16 SA8295P ADP Qualcomm® SA8295P QNN 5.955 ms 0 - 17 MB NPU --
YOLOv8-Segmentation w8a16 SA8650 (Proxy) Qualcomm® SA8650P (Proxy) QNN 4.559 ms 2 - 5 MB NPU --
YOLOv8-Segmentation w8a16 SA8775P ADP Qualcomm® SA8775P QNN 5.168 ms 1 - 13 MB NPU --
YOLOv8-Segmentation w8a16 Samsung Galaxy S23 Snapdragon® 8 Gen 2 Mobile QNN 4.513 ms 2 - 15 MB NPU --
YOLOv8-Segmentation w8a16 Samsung Galaxy S23 Snapdragon® 8 Gen 2 Mobile ONNX 7.892 ms 6 - 29 MB NPU --
YOLOv8-Segmentation w8a16 Samsung Galaxy S24 Snapdragon® 8 Gen 3 Mobile QNN 3.048 ms 2 - 55 MB NPU --
YOLOv8-Segmentation w8a16 Samsung Galaxy S24 Snapdragon® 8 Gen 3 Mobile ONNX 4.882 ms 8 - 80 MB NPU --
YOLOv8-Segmentation w8a16 Snapdragon 8 Elite QRD Snapdragon® 8 Elite Mobile QNN 2.562 ms 2 - 52 MB NPU --
YOLOv8-Segmentation w8a16 Snapdragon 8 Elite QRD Snapdragon® 8 Elite Mobile ONNX 4.852 ms 5 - 102 MB NPU --
YOLOv8-Segmentation w8a16 Snapdragon X Elite CRD Snapdragon® X Elite QNN 5.002 ms 2 - 2 MB NPU --
YOLOv8-Segmentation w8a16 Snapdragon X Elite CRD Snapdragon® X Elite ONNX 8.738 ms 15 - 15 MB NPU --

License

  • The license for the original implementation of YOLOv8-Segmentation can be found here.
  • The license for the compiled assets for on-device deployment can be found here

References

Community

Usage and Limitations

Model may not be used for or in connection with any of the following applications:

  • Accessing essential private and public services and benefits;
  • Administration of justice and democratic processes;
  • Assessing or recognizing the emotional state of a person;
  • Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics;
  • Education and vocational training;
  • Employment and workers management;
  • Exploitation of the vulnerabilities of persons resulting in harmful behavior;
  • General purpose social scoring;
  • Law enforcement;
  • Management and operation of critical infrastructure;
  • Migration, asylum and border control management;
  • Predictive policing;
  • Real-time remote biometric identification in public spaces;
  • Recommender systems of social media platforms;
  • Scraping of facial images (from the internet or otherwise); and/or
  • Subliminal manipulation
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