FFNet-54S: Optimized for Qualcomm Devices
FFNet-54S is a "fuss-free network" that segments street scene images with per-pixel classes like road, sidewalk, and pedestrian. Trained on the Cityscapes dataset.
This is based on the implementation of FFNet-54S 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 |
| QNN_DLC | w8a8 | 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 FFNet-54S 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 FFNet-54S on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.semantic_segmentation
Model Stats:
- Model checkpoint: ffnet54S_dBBB_cityscapes_state_dict_quarts
- Input resolution: 2048x1024
- Number of output classes: 19
- Number of parameters: 18.0M
- Model size (float): 68.8 MB
- Model size (w8a8): 17.5 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| FFNet-54S | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 13.466 ms | 29 - 256 MB | NPU |
| FFNet-54S | ONNX | float | Snapdragon® X2 Elite | 14.823 ms | 22 - 22 MB | NPU |
| FFNet-54S | ONNX | float | Snapdragon® X Elite | 34.008 ms | 24 - 24 MB | NPU |
| FFNet-54S | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 24.095 ms | 31 - 316 MB | NPU |
| FFNet-54S | ONNX | float | Qualcomm® QCS8550 (Proxy) | 34.73 ms | 24 - 27 MB | NPU |
| FFNet-54S | ONNX | float | Qualcomm® QCS9075 | 52.321 ms | 24 - 51 MB | NPU |
| FFNet-54S | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 17.857 ms | 6 - 204 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 6.909 ms | 2 - 205 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® X2 Elite | 7.379 ms | 13 - 13 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® X Elite | 11.159 ms | 12 - 12 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 6.946 ms | 7 - 265 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Qualcomm® QCS6490 | 410.214 ms | 178 - 233 MB | CPU |
| FFNet-54S | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 10.572 ms | 0 - 16 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Qualcomm® QCS9075 | 12.912 ms | 6 - 9 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Qualcomm® QCM6690 | 432.555 ms | 146 - 155 MB | CPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 11.641 ms | 2 - 201 MB | NPU |
| FFNet-54S | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 430.093 ms | 157 - 167 MB | CPU |
| FFNet-54S | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 13.653 ms | 12 - 254 MB | NPU |
| FFNet-54S | QNN_DLC | float | Snapdragon® X2 Elite | 15.899 ms | 24 - 24 MB | NPU |
| FFNet-54S | QNN_DLC | float | Snapdragon® X Elite | 39.896 ms | 24 - 24 MB | NPU |
| FFNet-54S | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 26.822 ms | 24 - 304 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 155.384 ms | 24 - 225 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 38.496 ms | 24 - 26 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® SA8775P | 53.621 ms | 24 - 225 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® QCS9075 | 66.833 ms | 24 - 52 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 77.117 ms | 9 - 280 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® SA7255P | 155.384 ms | 24 - 225 MB | NPU |
| FFNet-54S | QNN_DLC | float | Qualcomm® SA8295P | 59.262 ms | 24 - 220 MB | NPU |
| FFNet-54S | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 19.773 ms | 18 - 238 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 5.497 ms | 6 - 238 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 6.474 ms | 6 - 6 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® X Elite | 16.598 ms | 6 - 6 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 10.961 ms | 6 - 264 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 72.012 ms | 6 - 14 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 35.543 ms | 6 - 211 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 15.636 ms | 6 - 21 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® SA8775P | 16.255 ms | 6 - 212 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 18.8 ms | 6 - 14 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 144.477 ms | 6 - 244 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 22.404 ms | 6 - 266 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® SA7255P | 35.543 ms | 6 - 211 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Qualcomm® SA8295P | 21.272 ms | 6 - 215 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 7.47 ms | 6 - 226 MB | NPU |
| FFNet-54S | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 19.927 ms | 6 - 229 MB | NPU |
| FFNet-54S | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 13.699 ms | 2 - 261 MB | NPU |
| FFNet-54S | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 26.887 ms | 1 - 329 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 155.512 ms | 3 - 224 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 39.138 ms | 2 - 5 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® SA8775P | 53.698 ms | 2 - 224 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® QCS9075 | 66.529 ms | 0 - 64 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 77.052 ms | 3 - 323 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® SA7255P | 155.512 ms | 3 - 224 MB | NPU |
| FFNet-54S | TFLITE | float | Qualcomm® SA8295P | 59.289 ms | 0 - 216 MB | NPU |
| FFNet-54S | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 19.671 ms | 0 - 239 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 3.171 ms | 1 - 232 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 5.925 ms | 1 - 258 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCS6490 | 55.719 ms | 0 - 27 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 22.846 ms | 1 - 204 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 8.267 ms | 1 - 12 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® SA8775P | 8.855 ms | 1 - 205 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCS9075 | 10.042 ms | 1 - 27 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCM6690 | 118.026 ms | 1 - 237 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 13.298 ms | 0 - 261 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® SA7255P | 22.846 ms | 1 - 204 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Qualcomm® SA8295P | 13.155 ms | 1 - 206 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 4.457 ms | 0 - 220 MB | NPU |
| FFNet-54S | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 12.559 ms | 1 - 221 MB | NPU |
License
- The license for the original implementation of FFNet-54S 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.
