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 1.27.1 | 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:
- Input resolution: 1x3x1200x1200
- Model checkpoint: resnet34-ssd1200
- Model size (float): 76.2 MB
- Number of parameters: 20.0M
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| ResNet34-SSD | ONNX | float | Snapdragon® X2 Elite | 38.442 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® X Elite | 74.356 ms | 28 - 28 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 51.09 ms | 2 - 476 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 127.69 ms | 1 - 381 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 126.98 ms | 16 - 36 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 73.472 ms | 0 - 31 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® QCS8450 | 127.69 ms | 1 - 381 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 119.369 ms | 16 - 36 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 74.356 ms | 28 - 28 MB | NPU |
| ResNet34-SSD | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 43.309 ms | 3 - 272 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Elite Mobile | 43.309 ms | 3 - 272 MB | NPU |
| ResNet34-SSD | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 33.494 ms | 1 - 287 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® X2 Elite | 41.949 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® X Elite | 82.836 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 65.369 ms | 16 - 385 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 156.304 ms | 6 - 423 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 140.983 ms | 17 - 36 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 83.693 ms | 17 - 42 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA8775P | 125.468 ms | 16 - 270 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA8650P | 125.468 ms | 16 - 270 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA8255P | 125.468 ms | 16 - 270 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® QCS8450 | 156.304 ms | 6 - 423 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 125.389 ms | 17 - 35 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 82.836 ms | 17 - 17 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 44.274 ms | 16 - 281 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA7255P | 435.133 ms | 16 - 269 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Qualcomm® SA8295P | 133.816 ms | 0 - 224 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 44.274 ms | 16 - 281 MB | NPU |
| ResNet34-SSD | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 37.75 ms | 12 - 373 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 52.132 ms | 1 - 531 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 147.077 ms | 1 - 349 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 127.175 ms | 0 - 63 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 74.787 ms | 0 - 3 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8775P | 117.85 ms | 1 - 318 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8650P | 117.85 ms | 1 - 318 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8255P | 117.85 ms | 1 - 318 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® QCS8450 | 147.077 ms | 1 - 349 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 118.152 ms | 0 - 62 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 42.153 ms | 0 - 290 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA7255P | 419.768 ms | 1 - 311 MB | NPU |
| ResNet34-SSD | TFLITE | float | Qualcomm® SA8295P | 125.506 ms | 1 - 230 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Elite Mobile | 42.153 ms | 0 - 290 MB | NPU |
| ResNet34-SSD | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 35.345 ms | 0 - 384 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.
