Yolo-v5: Optimized for Mobile Deployment
Real-time object detection optimized for mobile and edge
YoloV5 is a machine learning model that predicts bounding boxes and classes of objects in an image.
This model is an implementation of Yolo-v5 found here.
More details on model performance across various devices, can be found here.
Model Details
- Model Type: Model_use_case.object_detection
- Model Stats:
- Model checkpoint: YoloV5-M
- Input resolution: 640x640
- Number of parameters: 21.2M
- Model size: 81.1 MB
| Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model |
|---|---|---|---|---|---|---|---|---|
| Yolo-v5 | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 72.237 ms | 6 - 80 MB | NPU | -- |
| Yolo-v5 | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN | 67.981 ms | 1 - 11 MB | NPU | -- |
| Yolo-v5 | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 34.752 ms | 6 - 85 MB | NPU | -- |
| Yolo-v5 | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN | 36.689 ms | 5 - 58 MB | NPU | -- |
| Yolo-v5 | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 22.909 ms | 1 - 33 MB | NPU | -- |
| Yolo-v5 | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 20.59 ms | 5 - 14 MB | NPU | -- |
| Yolo-v5 | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 28.768 ms | 6 - 81 MB | NPU | -- |
| Yolo-v5 | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN | 26.83 ms | 3 - 16 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 22.965 ms | 6 - 38 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 20.664 ms | 5 - 38 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 23.117 ms | 2 - 132 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 17.537 ms | 4 - 102 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 16.097 ms | 5 - 128 MB | NPU | -- |
| Yolo-v5 | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 18.075 ms | 3 - 139 MB | NPU | -- |
| Yolo-v5 | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 16.197 ms | 5 - 82 MB | NPU | -- |
| Yolo-v5 | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN | 13.158 ms | 5 - 127 MB | NPU | -- |
| Yolo-v5 | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 16.483 ms | 7 - 133 MB | NPU | -- |
| Yolo-v5 | float | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 21.104 ms | 5 - 5 MB | NPU | -- |
| Yolo-v5 | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 25.84 ms | 39 - 39 MB | NPU | -- |
| Yolo-v5 | w8a16 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN | 25.413 ms | 0 - 10 MB | NPU | -- |
| Yolo-v5 | w8a16 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN | 17.219 ms | 2 - 85 MB | NPU | -- |
| Yolo-v5 | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 12.515 ms | 2 - 5 MB | NPU | -- |
| Yolo-v5 | w8a16 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN | 12.829 ms | 2 - 16 MB | NPU | -- |
| Yolo-v5 | w8a16 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN | 55.56 ms | 2 - 14 MB | NPU | -- |
| Yolo-v5 | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 12.485 ms | 2 - 27 MB | NPU | -- |
| Yolo-v5 | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 18.84 ms | 1 - 69 MB | NPU | -- |
| Yolo-v5 | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 8.295 ms | 2 - 80 MB | NPU | -- |
| Yolo-v5 | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 13.29 ms | 0 - 171 MB | NPU | -- |
| Yolo-v5 | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN | 7.295 ms | 2 - 73 MB | NPU | -- |
| Yolo-v5 | w8a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 9.545 ms | 2 - 161 MB | NPU | -- |
| Yolo-v5 | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 13.351 ms | 2 - 2 MB | NPU | -- |
| Yolo-v5 | w8a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 22.063 ms | 20 - 20 MB | NPU | -- |
License
- The license for the original implementation of Yolo-v5 can be found here.
- The license for the compiled assets for on-device deployment 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.
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
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support