ResNet34-SSD: Optimized for Qualcomm Devices
ResNet34-SSD is a single-stage object detection model that integrates the ResNet34 backbone with the SSD (Single Shot MultiBox Detector) framework. It is optimized for real-time detection tasks and supports multiple deployment backends including PyTorch, TensorFlow, and ONNX.
This is based on the implementation of ResNet34-SSD 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
There are two ways to deploy this model on your device:
Option 1: Download Pre-Exported Models
Below are pre-exported model assets ready for deployment.
| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit ResNet34-SSD on Qualcomm® AI Hub.
Option 2: Export with Custom Configurations
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
This option is ideal if you need to customize the model beyond the default configuration provided here.
See our repository for ResNet34-SSD on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.object_detection
Model Stats:
- Model checkpoint: resnet34-ssd1200
- Input resolution: 1x3x1200x1200
- Number of parameters: 20.0M
- Model size (float): 76.2 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| ResNet34-SSD | ONNX | float | Snapdragon® X2 Elite | 43.349 ms | 164 - 164 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® X Elite | 88.337 ms | 132 - 132 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 63.557 ms | 17 - 507 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 177.876 ms | 17 - 437 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS8550 (Proxy) | 86.745 ms | 0 - 32 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS8450 | 177.876 ms | 17 - 437 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Elite Mobile | 52.014 ms | 1 - 422 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 38.567 ms | 1 - 494 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS9075 | 153.507 ms | 16 - 78 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS8750 | 52.014 ms | 1 - 422 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS7181 | 88.337 ms | 132 - 132 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® X2 Elite | 62.483 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® X Elite | 129.833 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 85.129 ms | 16 - 605 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 259.163 ms | 16 - 522 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS8275 | 481.99 ms | 16 - 383 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 134.915 ms | 17 - 19 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS8450 | 259.163 ms | 16 - 522 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 67.26 ms | 16 - 391 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA8295P | 183.207 ms | 1 - 329 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 51.973 ms | 0 - 547 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA7255P | 481.99 ms | 16 - 383 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS9075 | 194.463 ms | 17 - 35 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS8750 | 67.26 ms | 16 - 391 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS7181 | 129.833 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 107.277 ms | 0 - 542 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 243.208 ms | 1 - 619 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS8275 | 513.425 ms | 0 - 378 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 143.989 ms | 6 - 9 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8775P | 462.59 ms | 18 - 107 MB | CPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8650P | 462.59 ms | 18 - 107 MB | CPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8255P | 462.59 ms | 18 - 107 MB | CPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS8450 | 243.208 ms | 1 - 619 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Elite Mobile | 87.467 ms | 0 - 403 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8295P | 201.906 ms | 0 - 353 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 71.678 ms | 0 - 570 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA7255P | 513.425 ms | 0 - 378 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS9075 | 199.528 ms | 0 - 64 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS8750 | 87.467 ms | 0 - 403 MB | NPU |
License
- The license for the original implementation of ResNet34-SSD 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.