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README.md
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 6.
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 6.
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 4.
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 5.
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 4.
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 4.
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.
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| YOLOv8-Segmentation | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 6.
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| YOLOv8-Segmentation | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 6.
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| YOLOv8-Segmentation | SA7255P ADP | SA7255P | TFLITE | 93.
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| YOLOv8-Segmentation | SA7255P ADP | SA7255P | QNN | 92.
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| YOLOv8-Segmentation | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 6.
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| YOLOv8-Segmentation | SA8255 (Proxy) | SA8255P Proxy | QNN | 6.
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| YOLOv8-Segmentation | SA8295P ADP | SA8295P | TFLITE | 11.
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| YOLOv8-Segmentation | SA8295P ADP | SA8295P | QNN |
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| YOLOv8-Segmentation | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 6.
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| YOLOv8-Segmentation | SA8650 (Proxy) | SA8650P Proxy | QNN | 6.
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| YOLOv8-Segmentation | SA8775P ADP | SA8775P | TFLITE | 10.
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| YOLOv8-Segmentation | SA8775P ADP | SA8775P | QNN | 10.
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| YOLOv8-Segmentation | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 10.
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| YOLOv8-Segmentation | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 9.
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| YOLOv8-Segmentation | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 6.
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| YOLOv8-Segmentation | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 7.
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## Installation
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This model can be installed as a Python package via pip.
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```bash
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pip install "qai-hub-models[
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```
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## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 6.5
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Estimated peak memory usage (MB): [4,
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Total # Ops : 338
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Compute Unit(s) : NPU (338 ops)
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```
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy
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# Trace model
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input_shape = torch_model.get_input_spec()
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## License
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* The license for the original implementation of YOLOv8-Segmentation can be found
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* The license for the compiled assets for on-device deployment can be found [here](https://github.com/ultralytics/ultralytics/blob/main/LICENSE)
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 6.507 ms | 4 - 27 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 6.403 ms | 5 - 15 MB | FP16 | NPU | [YOLOv8-Segmentation.so](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.so) |
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| YOLOv8-Segmentation | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 7.767 ms | 14 - 50 MB | FP16 | NPU | [YOLOv8-Segmentation.onnx](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.onnx) |
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 4.788 ms | 0 - 54 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 4.569 ms | 0 - 55 MB | FP16 | NPU | [YOLOv8-Segmentation.so](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.so) |
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| YOLOv8-Segmentation | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 5.183 ms | 16 - 78 MB | FP16 | NPU | [YOLOv8-Segmentation.onnx](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.onnx) |
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 4.602 ms | 0 - 52 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 4.439 ms | 5 - 60 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 4.787 ms | 5 - 58 MB | FP16 | NPU | [YOLOv8-Segmentation.onnx](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.onnx) |
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| YOLOv8-Segmentation | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 6.485 ms | 4 - 25 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 6.316 ms | 5 - 8 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | SA7255P ADP | SA7255P | TFLITE | 93.297 ms | 4 - 51 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | SA7255P ADP | SA7255P | QNN | 92.263 ms | 0 - 9 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 6.532 ms | 4 - 26 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | SA8255 (Proxy) | SA8255P Proxy | QNN | 6.294 ms | 5 - 8 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | SA8295P ADP | SA8295P | TFLITE | 11.454 ms | 4 - 42 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | SA8295P ADP | SA8295P | QNN | 11.015 ms | 0 - 14 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 6.539 ms | 4 - 27 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | SA8650 (Proxy) | SA8650P Proxy | QNN | 6.394 ms | 5 - 8 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | SA8775P ADP | SA8775P | TFLITE | 10.159 ms | 4 - 50 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | SA8775P ADP | SA8775P | QNN | 10.125 ms | 0 - 10 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 10.14 ms | 4 - 45 MB | FP16 | NPU | [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) |
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| YOLOv8-Segmentation | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 9.542 ms | 5 - 51 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 6.895 ms | 5 - 5 MB | FP16 | NPU | Use Export Script |
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| YOLOv8-Segmentation | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 7.655 ms | 17 - 17 MB | FP16 | NPU | [YOLOv8-Segmentation.onnx](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.onnx) |
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## Installation
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Install the package via pip:
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```bash
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pip install "qai-hub-models[yolov8-seg]"
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```
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## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
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Device : Samsung Galaxy S23 (13)
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Runtime : TFLITE
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Estimated inference time (ms) : 6.5
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Estimated peak memory usage (MB): [4, 27]
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Total # Ops : 338
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Compute Unit(s) : NPU (338 ops)
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```
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy S24")
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# Trace model
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input_shape = torch_model.get_input_spec()
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## License
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* The license for the original implementation of YOLOv8-Segmentation can be found
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[here](https://github.com/ultralytics/ultralytics/blob/main/LICENSE).
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* The license for the compiled assets for on-device deployment can be found [here](https://github.com/ultralytics/ultralytics/blob/main/LICENSE)
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