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Yolo-R

Object Detection
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real_time
android
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metadata 
library_name: pytorch
license: other
tags:
  - bu_auto
  - real_time
  - android
pipeline_tag: object-detection

Yolo-R: Optimized for Qualcomm Devices

YoloR is a machine learning model that predicts bounding boxes and classes of objects in an image.

This is based on the implementation of Yolo-R 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 Yolo-R on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.object_detection

Model Stats:

  • Model checkpoint: yolor_p6
  • Input resolution: 640x640
  • Number of parameters: 4.68M
  • Model size (float): 17.9 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
Yolo-R ONNX float Snapdragon® X Elite 59.708 ms 75 - 75 MB NPU
Yolo-R ONNX float Snapdragon® 8 Gen 3 Mobile 46.21 ms 2 - 291 MB NPU
Yolo-R ONNX float Qualcomm® QCS8550 (Proxy) 63.877 ms 5 - 8 MB NPU
Yolo-R ONNX float Qualcomm® QCS9075 81.653 ms 5 - 12 MB NPU
Yolo-R ONNX float Snapdragon® 8 Elite For Galaxy Mobile 32.462 ms 1 - 173 MB NPU
Yolo-R ONNX float Snapdragon® 8 Elite Gen 5 Mobile 30.32 ms 0 - 245 MB NPU
Yolo-R ONNX w8a16 Snapdragon® X Elite 31.604 ms 41 - 41 MB NPU
Yolo-R ONNX w8a16 Snapdragon® 8 Gen 3 Mobile 22.018 ms 1 - 397 MB NPU
Yolo-R ONNX w8a16 Qualcomm® QCS6490 2301.178 ms 124 - 142 MB CPU
Yolo-R ONNX w8a16 Qualcomm® QCS8550 (Proxy) 37.456 ms 0 - 424 MB NPU
Yolo-R ONNX w8a16 Qualcomm® QCS9075 32.023 ms 1 - 6 MB NPU
Yolo-R ONNX w8a16 Qualcomm® QCM6690 1155.802 ms 36 - 48 MB CPU
Yolo-R ONNX w8a16 Snapdragon® 8 Elite For Galaxy Mobile 17.63 ms 1 - 292 MB NPU
Yolo-R ONNX w8a16 Snapdragon® 7 Gen 4 Mobile 1089.713 ms 124 - 137 MB CPU
Yolo-R ONNX w8a16 Snapdragon® 8 Elite Gen 5 Mobile 18.688 ms 0 - 368 MB NPU
Yolo-R QNN_DLC float Snapdragon® X Elite 29.858 ms 5 - 5 MB NPU
Yolo-R QNN_DLC float Snapdragon® 8 Gen 3 Mobile 22.895 ms 5 - 344 MB NPU
Yolo-R QNN_DLC float Qualcomm® QCS8275 (Proxy) 100.474 ms 1 - 273 MB NPU
Yolo-R QNN_DLC float Qualcomm® QCS8550 (Proxy) 30.237 ms 5 - 7 MB NPU
Yolo-R QNN_DLC float Qualcomm® SA8775P 35.561 ms 1 - 276 MB NPU
Yolo-R QNN_DLC float Qualcomm® QCS9075 37.297 ms 5 - 11 MB NPU
Yolo-R QNN_DLC float Qualcomm® QCS8450 (Proxy) 49.525 ms 4 - 379 MB NPU
Yolo-R QNN_DLC float Qualcomm® SA7255P 100.474 ms 1 - 273 MB NPU
Yolo-R QNN_DLC float Qualcomm® SA8295P 43.831 ms 0 - 321 MB NPU
Yolo-R QNN_DLC float Snapdragon® 8 Elite For Galaxy Mobile 18.211 ms 5 - 237 MB NPU
Yolo-R QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 14.214 ms 5 - 313 MB NPU
Yolo-R TFLITE float Snapdragon® 8 Gen 3 Mobile 38.894 ms 0 - 449 MB NPU
Yolo-R TFLITE float Qualcomm® QCS8275 (Proxy) 135.572 ms 1 - 323 MB NPU
Yolo-R TFLITE float Qualcomm® QCS8550 (Proxy) 58.257 ms 1 - 3 MB NPU
Yolo-R TFLITE float Qualcomm® SA8775P 61.1 ms 1 - 338 MB NPU
Yolo-R TFLITE float Qualcomm® QCS9075 50.135 ms 1 - 86 MB NPU
Yolo-R TFLITE float Qualcomm® QCS8450 (Proxy) 87.963 ms 1 - 470 MB NPU
Yolo-R TFLITE float Qualcomm® SA7255P 135.572 ms 1 - 323 MB NPU
Yolo-R TFLITE float Qualcomm® SA8295P 73.377 ms 1 - 356 MB NPU
Yolo-R TFLITE float Snapdragon® 8 Elite For Galaxy Mobile 31.364 ms 0 - 281 MB NPU
Yolo-R TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 25.844 ms 1 - 344 MB NPU

License

  • The license for the original implementation of Yolo-R can be found here.

References

Community