PidNet: Optimized for Qualcomm Devices
PIDNet (Proportional-Integral-Derivative Network) is a real-time semantic segmentation model based on PID controllers
This is based on the implementation of PidNet 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 2.42, ONNX Runtime 1.24.3 | Download |
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
| TFLITE | w8a8 | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit PidNet 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 PidNet on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.semantic_segmentation
Model Stats:
- Model checkpoint: PIDNet_S_Cityscapes_val.pt
- Inference latency: RealTime
- Input resolution: 1024x2048
- Number of output classes: 19
- Number of parameters: 8.06M
- Model size (float): 29.1 MB
- Model size (w8a8): 8.02 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| PidNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 12.147 ms | 30 - 298 MB | NPU |
| PidNet | ONNX | float | Snapdragon® X2 Elite | 13.032 ms | 22 - 22 MB | NPU |
| PidNet | ONNX | float | Snapdragon® X Elite | 32.73 ms | 24 - 24 MB | NPU |
| PidNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 23.118 ms | 26 - 343 MB | NPU |
| PidNet | ONNX | float | Qualcomm® QCS8550 (Proxy) | 32.643 ms | 24 - 26 MB | NPU |
| PidNet | ONNX | float | Qualcomm® QCS9075 | 47.321 ms | 24 - 51 MB | NPU |
| PidNet | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 15.98 ms | 7 - 220 MB | NPU |
| PidNet | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 44.593 ms | 73 - 293 MB | NPU |
| PidNet | ONNX | w8a8 | Snapdragon® X2 Elite | 45.557 ms | 134 - 134 MB | NPU |
| PidNet | ONNX | w8a8 | Snapdragon® X Elite | 89.567 ms | 133 - 133 MB | NPU |
| PidNet | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 45.633 ms | 80 - 341 MB | NPU |
| PidNet | ONNX | w8a8 | Qualcomm® QCS6490 | 386.898 ms | 197 - 216 MB | CPU |
| PidNet | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 59.858 ms | 101 - 109 MB | NPU |
| PidNet | ONNX | w8a8 | Qualcomm® QCS9075 | 65.921 ms | 103 - 106 MB | NPU |
| PidNet | ONNX | w8a8 | Qualcomm® QCM6690 | 347.589 ms | 141 - 151 MB | CPU |
| PidNet | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 44.093 ms | 105 - 310 MB | NPU |
| PidNet | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 327.416 ms | 134 - 145 MB | CPU |
| PidNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 12.004 ms | 14 - 284 MB | NPU |
| PidNet | QNN_DLC | float | Snapdragon® X2 Elite | 13.481 ms | 24 - 24 MB | NPU |
| PidNet | QNN_DLC | float | Snapdragon® X Elite | 38.887 ms | 24 - 24 MB | NPU |
| PidNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 25.629 ms | 23 - 326 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 117.732 ms | 24 - 241 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 37.235 ms | 24 - 274 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® SA8775P | 46.582 ms | 24 - 242 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® QCS9075 | 61.125 ms | 24 - 52 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 75.848 ms | 4 - 309 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® SA7255P | 117.732 ms | 24 - 241 MB | NPU |
| PidNet | QNN_DLC | float | Qualcomm® SA8295P | 51.99 ms | 24 - 253 MB | NPU |
| PidNet | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 18.254 ms | 18 - 264 MB | NPU |
| PidNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 12.686 ms | 2 - 275 MB | NPU |
| PidNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 25.059 ms | 0 - 319 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 116.587 ms | 2 - 231 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 36.389 ms | 2 - 6 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® SA8775P | 45.288 ms | 2 - 233 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® QCS9075 | 59.754 ms | 0 - 45 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 74.773 ms | 3 - 330 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® SA7255P | 116.587 ms | 2 - 231 MB | NPU |
| PidNet | TFLITE | float | Qualcomm® SA8295P | 50.984 ms | 2 - 245 MB | NPU |
| PidNet | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 18.843 ms | 2 - 256 MB | NPU |
| PidNet | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 22.222 ms | 0 - 262 MB | NPU |
| PidNet | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 37.809 ms | 1 - 267 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCS6490 | 208.912 ms | 3 - 73 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 98.277 ms | 1 - 214 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 50.448 ms | 1 - 4 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® SA8775P | 51.011 ms | 1 - 213 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCS9075 | 52.894 ms | 1 - 17 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCM6690 | 238.604 ms | 1 - 233 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 58.791 ms | 0 - 265 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® SA7255P | 98.277 ms | 1 - 214 MB | NPU |
| PidNet | TFLITE | w8a8 | Qualcomm® SA8295P | 58.058 ms | 1 - 218 MB | NPU |
| PidNet | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 70.006 ms | 1 - 237 MB | NPU |
| PidNet | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 66.96 ms | 1 - 219 MB | NPU |
License
- The license for the original implementation of PidNet can be found here.
References
- PIDNet A Real-time Semantic Segmentation Network Inspired from PID Controller Segmentation of Road Scenes
- Source Model Implementation
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.
