v0.34.0
Browse filesSee https://github.com/quic/ai-hub-models/releases/v0.34.0 for changelog.
README.md
CHANGED
@@ -19,7 +19,11 @@ Ultralytics YOLOv10 is a machine learning model that predicts bounding boxes and
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This model is an implementation of YOLOv10-Detection found [here](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models/yolo/detect).
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### Model Details
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@@ -34,87 +38,255 @@ This model is an implementation of YOLOv10-Detection found [here](https://github
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| Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model
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|---|---|---|---|---|---|---|---|---|
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| YOLOv10-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 16.
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| YOLOv10-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 12.906 ms | 1 - 99 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 9.
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| YOLOv10-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 9.1 ms | 5 - 45 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 6.
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| YOLOv10-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 3.942 ms | 0 - 72 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 7.
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| YOLOv10-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 5.461 ms | 2 - 104 MB | NPU | -- |
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| YOLOv10-Detection | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 16.
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| YOLOv10-Detection | float | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 12.906 ms | 1 - 99 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 6.
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| YOLOv10-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 3.978 ms | 0 - 59 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 10.
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| YOLOv10-Detection | float | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 8.267 ms | 3 - 37 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 6.
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| YOLOv10-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 3.966 ms | 0 - 61 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 7.
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| YOLOv10-Detection | float | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 5.461 ms | 2 - 104 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 6.
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 3.953 ms | 0 - 67 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 5.
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 4.
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 2.794 ms | 5 - 215 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 4.
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE |
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 2.668 ms | 5 - 133 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 3.
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| YOLOv10-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 4.592 ms | 5 - 5 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 6.
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| YOLOv10-Detection | w8a16 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 7.
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| YOLOv10-Detection | w8a16 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN_DLC |
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| YOLOv10-Detection | w8a16 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 7.
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| YOLOv10-Detection | w8a16 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 5.
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| YOLOv10-Detection | w8a16 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 11.
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| YOLOv10-Detection | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 2.
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| YOLOv10-Detection | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 8.
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| YOLOv10-Detection | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 2.292 ms | 2 -
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| YOLOv10-Detection | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX |
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| YOLOv10-Detection | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 4.
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| YOLOv10-Detection | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX |
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| YOLOv10-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 3.
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| YOLOv10-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 3.
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| YOLOv10-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 2.
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| YOLOv10-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 2.
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| YOLOv10-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 2.
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| YOLOv10-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 2.
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| YOLOv10-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | TFLITE | 4.
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| YOLOv10-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN_DLC | 5.
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| YOLOv10-Detection | w8a8 | RB5 (Proxy) | Qualcomm® QCS8250 (Proxy) | TFLITE |
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| YOLOv10-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 3.
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| YOLOv10-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 3.
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| YOLOv10-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 2.
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| YOLOv10-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 2.
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| YOLOv10-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 2.
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| YOLOv10-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 2.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 6.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX |
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| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 1.
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| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 1.
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| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX |
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| YOLOv10-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 2.
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| YOLOv10-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 7.
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## License
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## Community
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* Join [our AI Hub Slack community](https://qualcomm
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* For questions or feedback please [reach out to us](mailto:[email protected]).
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Model may not be used for or in connection with any of the following applications:
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- Accessing essential private and public services and benefits;
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- Administration of justice and democratic processes;
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- Assessing or recognizing the emotional state of a person;
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- Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics;
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- Education and vocational training;
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- Employment and workers management;
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- Exploitation of the vulnerabilities of persons resulting in harmful behavior;
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- General purpose social scoring;
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- Law enforcement;
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- Management and operation of critical infrastructure;
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- Migration, asylum and border control management;
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- Predictive policing;
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- Real-time remote biometric identification in public spaces;
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- Recommender systems of social media platforms;
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- Scraping of facial images (from the internet or otherwise); and/or
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- Subliminal manipulation
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This model is an implementation of YOLOv10-Detection found [here](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models/yolo/detect).
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This repository provides scripts to run YOLOv10-Detection on Qualcomm® devices.
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More details on model performance across various devices, can be found
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[here](https://aihub.qualcomm.com/models/yolov10_det).
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**WARNING**: The model assets are not readily available for download due to licensing restrictions.
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### Model Details
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| Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model
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|---|---|---|---|---|---|---|---|---|
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| YOLOv10-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 16.29 ms | 0 - 41 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 12.906 ms | 1 - 99 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 9.095 ms | 0 - 40 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 9.1 ms | 5 - 45 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 6.01 ms | 0 - 19 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 3.942 ms | 0 - 72 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 7.407 ms | 0 - 41 MB | NPU | -- |
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| YOLOv10-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 5.461 ms | 2 - 104 MB | NPU | -- |
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| YOLOv10-Detection | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 16.29 ms | 0 - 41 MB | NPU | -- |
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| YOLOv10-Detection | float | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 12.906 ms | 1 - 99 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 6.023 ms | 0 - 19 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 3.978 ms | 0 - 59 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 10.425 ms | 0 - 27 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 8.267 ms | 3 - 37 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 6.115 ms | 0 - 19 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 3.966 ms | 0 - 61 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 7.407 ms | 0 - 41 MB | NPU | -- |
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| YOLOv10-Detection | float | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 5.461 ms | 2 - 104 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 6.029 ms | 0 - 10 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 3.953 ms | 0 - 67 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 5.742 ms | 0 - 82 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 4.365 ms | 0 - 57 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 2.794 ms | 5 - 215 MB | NPU | -- |
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| YOLOv10-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 4.167 ms | 0 - 162 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 3.46 ms | 0 - 47 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 2.668 ms | 5 - 133 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 3.602 ms | 5 - 88 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 4.592 ms | 5 - 5 MB | NPU | -- |
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| YOLOv10-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 6.195 ms | 5 - 5 MB | NPU | -- |
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| YOLOv10-Detection | w8a16 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 7.54 ms | 2 - 35 MB | NPU | -- |
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| YOLOv10-Detection | w8a16 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 4.733 ms | 2 - 41 MB | NPU | -- |
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| YOLOv10-Detection | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 4.037 ms | 2 - 14 MB | NPU | -- |
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73 |
+
| YOLOv10-Detection | w8a16 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 4.662 ms | 2 - 36 MB | NPU | -- |
|
74 |
+
| YOLOv10-Detection | w8a16 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN_DLC | 13.307 ms | 2 - 38 MB | NPU | -- |
|
75 |
+
| YOLOv10-Detection | w8a16 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 7.54 ms | 2 - 35 MB | NPU | -- |
|
76 |
+
| YOLOv10-Detection | w8a16 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 4.051 ms | 2 - 15 MB | NPU | -- |
|
77 |
+
| YOLOv10-Detection | w8a16 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 5.358 ms | 2 - 37 MB | NPU | -- |
|
78 |
+
| YOLOv10-Detection | w8a16 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 4.034 ms | 2 - 14 MB | NPU | -- |
|
79 |
+
| YOLOv10-Detection | w8a16 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 4.662 ms | 2 - 36 MB | NPU | -- |
|
80 |
+
| YOLOv10-Detection | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 4.053 ms | 2 - 14 MB | NPU | -- |
|
81 |
+
| YOLOv10-Detection | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 11.693 ms | 1 - 36 MB | NPU | -- |
|
82 |
+
| YOLOv10-Detection | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 2.714 ms | 2 - 44 MB | NPU | -- |
|
83 |
+
| YOLOv10-Detection | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 8.689 ms | 2 - 153 MB | NPU | -- |
|
84 |
+
| YOLOv10-Detection | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 2.292 ms | 2 - 39 MB | NPU | -- |
|
85 |
+
| YOLOv10-Detection | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 8.067 ms | 2 - 87 MB | NPU | -- |
|
86 |
+
| YOLOv10-Detection | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 4.658 ms | 20 - 20 MB | NPU | -- |
|
87 |
+
| YOLOv10-Detection | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 12.651 ms | 2 - 2 MB | NPU | -- |
|
88 |
+
| YOLOv10-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 3.681 ms | 0 - 24 MB | NPU | -- |
|
89 |
+
| YOLOv10-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 3.715 ms | 1 - 27 MB | NPU | -- |
|
90 |
+
| YOLOv10-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 2.049 ms | 0 - 40 MB | NPU | -- |
|
91 |
+
| YOLOv10-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 2.085 ms | 1 - 35 MB | NPU | -- |
|
92 |
+
| YOLOv10-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 1.821 ms | 0 - 14 MB | NPU | -- |
|
93 |
+
| YOLOv10-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 1.825 ms | 1 - 13 MB | NPU | -- |
|
94 |
+
| YOLOv10-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 2.282 ms | 0 - 25 MB | NPU | -- |
|
95 |
+
| YOLOv10-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 2.259 ms | 1 - 29 MB | NPU | -- |
|
96 |
+
| YOLOv10-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | TFLITE | 4.132 ms | 0 - 31 MB | NPU | -- |
|
97 |
+
| YOLOv10-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN_DLC | 5.391 ms | 1 - 33 MB | NPU | -- |
|
98 |
+
| YOLOv10-Detection | w8a8 | RB5 (Proxy) | Qualcomm® QCS8250 (Proxy) | TFLITE | 64.773 ms | 2 - 12 MB | NPU | -- |
|
99 |
+
| YOLOv10-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 3.681 ms | 0 - 24 MB | NPU | -- |
|
100 |
+
| YOLOv10-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 3.715 ms | 1 - 27 MB | NPU | -- |
|
101 |
+
| YOLOv10-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 1.829 ms | 0 - 13 MB | NPU | -- |
|
102 |
+
| YOLOv10-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 1.828 ms | 1 - 14 MB | NPU | -- |
|
103 |
+
| YOLOv10-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 2.635 ms | 0 - 27 MB | NPU | -- |
|
104 |
+
| YOLOv10-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 2.611 ms | 1 - 31 MB | NPU | -- |
|
105 |
+
| YOLOv10-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 1.83 ms | 0 - 14 MB | NPU | -- |
|
106 |
+
| YOLOv10-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 1.826 ms | 1 - 12 MB | NPU | -- |
|
107 |
+
| YOLOv10-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 2.282 ms | 0 - 25 MB | NPU | -- |
|
108 |
+
| YOLOv10-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 2.259 ms | 1 - 29 MB | NPU | -- |
|
109 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 1.837 ms | 0 - 13 MB | NPU | -- |
|
110 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 1.831 ms | 1 - 14 MB | NPU | -- |
|
111 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 6.805 ms | 0 - 32 MB | NPU | -- |
|
112 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 1.214 ms | 0 - 35 MB | NPU | -- |
|
113 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 1.241 ms | 1 - 36 MB | NPU | -- |
|
114 |
+
| YOLOv10-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 5.009 ms | 1 - 81 MB | NPU | -- |
|
115 |
+
| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 1.115 ms | 0 - 28 MB | NPU | -- |
|
116 |
+
| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 1.087 ms | 1 - 34 MB | NPU | -- |
|
117 |
+
| YOLOv10-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 3.538 ms | 1 - 83 MB | NPU | -- |
|
118 |
+
| YOLOv10-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 2.155 ms | 11 - 11 MB | NPU | -- |
|
119 |
+
| YOLOv10-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 7.466 ms | 1 - 1 MB | NPU | -- |
|
120 |
+
|
121 |
+
|
122 |
+
|
123 |
+
|
124 |
+
## Installation
|
125 |
+
|
126 |
+
|
127 |
+
Install the package via pip:
|
128 |
+
```bash
|
129 |
+
pip install "qai-hub-models[yolov10-det]"
|
130 |
+
```
|
131 |
+
|
132 |
+
|
133 |
+
## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
|
134 |
+
|
135 |
+
Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
|
136 |
+
Qualcomm® ID. Once signed in navigate to `Account -> Settings -> API Token`.
|
137 |
+
|
138 |
+
With this API token, you can configure your client to run models on the cloud
|
139 |
+
hosted devices.
|
140 |
+
```bash
|
141 |
+
qai-hub configure --api_token API_TOKEN
|
142 |
+
```
|
143 |
+
Navigate to [docs](https://app.aihub.qualcomm.com/docs/) for more information.
|
144 |
+
|
145 |
+
|
146 |
+
|
147 |
+
## Demo off target
|
148 |
+
|
149 |
+
The package contains a simple end-to-end demo that downloads pre-trained
|
150 |
+
weights and runs this model on a sample input.
|
151 |
+
|
152 |
+
```bash
|
153 |
+
python -m qai_hub_models.models.yolov10_det.demo
|
154 |
+
```
|
155 |
+
|
156 |
+
The above demo runs a reference implementation of pre-processing, model
|
157 |
+
inference, and post processing.
|
158 |
+
|
159 |
+
**NOTE**: If you want running in a Jupyter Notebook or Google Colab like
|
160 |
+
environment, please add the following to your cell (instead of the above).
|
161 |
+
```
|
162 |
+
%run -m qai_hub_models.models.yolov10_det.demo
|
163 |
+
```
|
164 |
+
|
165 |
+
|
166 |
+
### Run model on a cloud-hosted device
|
167 |
+
|
168 |
+
In addition to the demo, you can also run the model on a cloud-hosted Qualcomm®
|
169 |
+
device. This script does the following:
|
170 |
+
* Performance check on-device on a cloud-hosted device
|
171 |
+
* Downloads compiled assets that can be deployed on-device for Android.
|
172 |
+
* Accuracy check between PyTorch and on-device outputs.
|
173 |
+
|
174 |
+
```bash
|
175 |
+
python -m qai_hub_models.models.yolov10_det.export
|
176 |
+
```
|
177 |
+
|
178 |
+
|
179 |
+
|
180 |
+
## How does this work?
|
181 |
+
|
182 |
+
This [export script](https://aihub.qualcomm.com/models/yolov10_det/qai_hub_models/models/YOLOv10-Detection/export.py)
|
183 |
+
leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model
|
184 |
+
on-device. Lets go through each step below in detail:
|
185 |
+
|
186 |
+
Step 1: **Compile model for on-device deployment**
|
187 |
+
|
188 |
+
To compile a PyTorch model for on-device deployment, we first trace the model
|
189 |
+
in memory using the `jit.trace` and then call the `submit_compile_job` API.
|
190 |
+
|
191 |
+
```python
|
192 |
+
import torch
|
193 |
|
194 |
+
import qai_hub as hub
|
195 |
+
from qai_hub_models.models.yolov10_det import Model
|
196 |
|
197 |
+
# Load the model
|
198 |
+
torch_model = Model.from_pretrained()
|
199 |
+
|
200 |
+
# Device
|
201 |
+
device = hub.Device("Samsung Galaxy S24")
|
202 |
+
|
203 |
+
# Trace model
|
204 |
+
input_shape = torch_model.get_input_spec()
|
205 |
+
sample_inputs = torch_model.sample_inputs()
|
206 |
+
|
207 |
+
pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()])
|
208 |
+
|
209 |
+
# Compile model on a specific device
|
210 |
+
compile_job = hub.submit_compile_job(
|
211 |
+
model=pt_model,
|
212 |
+
device=device,
|
213 |
+
input_specs=torch_model.get_input_spec(),
|
214 |
+
)
|
215 |
+
|
216 |
+
# Get target model to run on-device
|
217 |
+
target_model = compile_job.get_target_model()
|
218 |
+
|
219 |
+
```
|
220 |
+
|
221 |
+
|
222 |
+
Step 2: **Performance profiling on cloud-hosted device**
|
223 |
+
|
224 |
+
After compiling models from step 1. Models can be profiled model on-device using the
|
225 |
+
`target_model`. Note that this scripts runs the model on a device automatically
|
226 |
+
provisioned in the cloud. Once the job is submitted, you can navigate to a
|
227 |
+
provided job URL to view a variety of on-device performance metrics.
|
228 |
+
```python
|
229 |
+
profile_job = hub.submit_profile_job(
|
230 |
+
model=target_model,
|
231 |
+
device=device,
|
232 |
+
)
|
233 |
+
|
234 |
+
```
|
235 |
+
|
236 |
+
Step 3: **Verify on-device accuracy**
|
237 |
+
|
238 |
+
To verify the accuracy of the model on-device, you can run on-device inference
|
239 |
+
on sample input data on the same cloud hosted device.
|
240 |
+
```python
|
241 |
+
input_data = torch_model.sample_inputs()
|
242 |
+
inference_job = hub.submit_inference_job(
|
243 |
+
model=target_model,
|
244 |
+
device=device,
|
245 |
+
inputs=input_data,
|
246 |
+
)
|
247 |
+
on_device_output = inference_job.download_output_data()
|
248 |
+
|
249 |
+
```
|
250 |
+
With the output of the model, you can compute like PSNR, relative errors or
|
251 |
+
spot check the output with expected output.
|
252 |
+
|
253 |
+
**Note**: This on-device profiling and inference requires access to Qualcomm®
|
254 |
+
AI Hub. [Sign up for access](https://myaccount.qualcomm.com/signup).
|
255 |
+
|
256 |
+
|
257 |
+
|
258 |
+
## Run demo on a cloud-hosted device
|
259 |
+
|
260 |
+
You can also run the demo on-device.
|
261 |
+
|
262 |
+
```bash
|
263 |
+
python -m qai_hub_models.models.yolov10_det.demo --eval-mode on-device
|
264 |
+
```
|
265 |
+
|
266 |
+
**NOTE**: If you want running in a Jupyter Notebook or Google Colab like
|
267 |
+
environment, please add the following to your cell (instead of the above).
|
268 |
+
```
|
269 |
+
%run -m qai_hub_models.models.yolov10_det.demo -- --eval-mode on-device
|
270 |
+
```
|
271 |
+
|
272 |
+
|
273 |
+
## Deploying compiled model to Android
|
274 |
+
|
275 |
+
|
276 |
+
The models can be deployed using multiple runtimes:
|
277 |
+
- TensorFlow Lite (`.tflite` export): [This
|
278 |
+
tutorial](https://www.tensorflow.org/lite/android/quickstart) provides a
|
279 |
+
guide to deploy the .tflite model in an Android application.
|
280 |
+
|
281 |
+
|
282 |
+
- QNN (`.so` export ): This [sample
|
283 |
+
app](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/sample_app.html)
|
284 |
+
provides instructions on how to use the `.so` shared library in an Android application.
|
285 |
+
|
286 |
+
|
287 |
+
## View on Qualcomm® AI Hub
|
288 |
+
Get more details on YOLOv10-Detection's performance across various devices [here](https://aihub.qualcomm.com/models/yolov10_det).
|
289 |
+
Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
|
290 |
|
291 |
|
292 |
## License
|
|
|
303 |
|
304 |
|
305 |
## Community
|
306 |
+
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
|
307 |
* For questions or feedback please [reach out to us](mailto:[email protected]).
|
308 |
|
309 |
+
|
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