---
library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-segmentation

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/web-assets/model_demo.png)

# FFNet-78S: Optimized for Qualcomm Devices

FFNet-78S 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-78S found [here](https://github.com/Qualcomm-AI-research/FFNet).
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/ffnet_78s) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).

Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) 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 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/ffnet_78s/releases/v0.47.0/ffnet_78s-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[FFNet-78S on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/ffnet_78s)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/ffnet_78s) 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-78S on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/ffnet_78s) for usage instructions.

## Model Details

**Model Type:** Model_use_case.semantic_segmentation

**Model Stats:**
- Model checkpoint: ffnet78S_dBBB_cityscapes_state_dict_quarts
- Input resolution: 2048x1024
- Number of output classes: 19
- Number of parameters: 27.5M
- Model size (float): 105 MB
- Model size (w8a8): 26.7 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| FFNet-78S | ONNX | float | Snapdragon® X Elite | 37.916 ms | 30 - 30 MB | NPU
| FFNet-78S | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 27.087 ms | 2 - 303 MB | NPU
| FFNet-78S | ONNX | float | Qualcomm® QCS8550 (Proxy) | 38.819 ms | 24 - 55 MB | NPU
| FFNet-78S | ONNX | float | Qualcomm® QCS9075 | 59.465 ms | 24 - 51 MB | NPU
| FFNet-78S | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 20.025 ms | 7 - 210 MB | NPU
| FFNet-78S | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 17.186 ms | 29 - 258 MB | NPU
| FFNet-78S | ONNX | float | Snapdragon® X2 Elite | 18.088 ms | 30 - 30 MB | NPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® X Elite | 14.864 ms | 21 - 21 MB | NPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 11.802 ms | 7 - 294 MB | NPU
| FFNet-78S | ONNX | w8a8 | Qualcomm® QCS6490 | 488.89 ms | 168 - 224 MB | CPU
| FFNet-78S | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 15.459 ms | 0 - 392 MB | NPU
| FFNet-78S | ONNX | w8a8 | Qualcomm® QCS9075 | 14.458 ms | 6 - 9 MB | NPU
| FFNet-78S | ONNX | w8a8 | Qualcomm® QCM6690 | 536.573 ms | 132 - 142 MB | CPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 8.799 ms | 1 - 214 MB | NPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 530.544 ms | 147 - 157 MB | CPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 7.305 ms | 2 - 220 MB | NPU
| FFNet-78S | ONNX | w8a8 | Snapdragon® X2 Elite | 7.905 ms | 22 - 22 MB | NPU
| FFNet-78S | QNN_DLC | float | Snapdragon® X Elite | 43.796 ms | 24 - 24 MB | NPU
| FFNet-78S | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 29.532 ms | 24 - 332 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 186.934 ms | 24 - 235 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 42.346 ms | 24 - 39 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® SA8775P | 60.781 ms | 24 - 235 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® QCS9075 | 73.761 ms | 24 - 52 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 84.171 ms | 2 - 292 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® SA7255P | 186.934 ms | 24 - 235 MB | NPU
| FFNet-78S | QNN_DLC | float | Qualcomm® SA8295P | 66.03 ms | 24 - 230 MB | NPU
| FFNet-78S | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 21.693 ms | 22 - 250 MB | NPU
| FFNet-78S | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 15.51 ms | 24 - 276 MB | NPU
| FFNet-78S | QNN_DLC | float | Snapdragon® X2 Elite | 18.002 ms | 24 - 24 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® X Elite | 17.748 ms | 6 - 6 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 11.653 ms | 6 - 285 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 72.404 ms | 6 - 14 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 39.165 ms | 6 - 217 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 16.791 ms | 6 - 8 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® SA8775P | 77.741 ms | 6 - 217 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 19.433 ms | 6 - 14 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 165.866 ms | 6 - 253 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 24.066 ms | 6 - 288 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® SA7255P | 39.165 ms | 6 - 217 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Qualcomm® SA8295P | 23.322 ms | 6 - 220 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 7.965 ms | 6 - 233 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 22.462 ms | 6 - 237 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 5.897 ms | 6 - 255 MB | NPU
| FFNet-78S | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 7.054 ms | 6 - 6 MB | NPU
| FFNet-78S | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 29.472 ms | 0 - 387 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 186.973 ms | 3 - 248 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 43.022 ms | 2 - 5 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® SA8775P | 282.888 ms | 3 - 248 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® QCS9075 | 72.981 ms | 0 - 82 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 84.408 ms | 1 - 374 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® SA7255P | 186.973 ms | 3 - 248 MB | NPU
| FFNet-78S | TFLITE | float | Qualcomm® SA8295P | 66.076 ms | 2 - 244 MB | NPU
| FFNet-78S | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 21.685 ms | 1 - 265 MB | NPU
| FFNet-78S | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 15.447 ms | 2 - 284 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 6.444 ms | 1 - 284 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCS6490 | 57.085 ms | 1 - 36 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 26.379 ms | 1 - 210 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 9.065 ms | 1 - 3 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® SA8775P | 42.19 ms | 1 - 211 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCS9075 | 10.987 ms | 1 - 36 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCM6690 | 140.078 ms | 1 - 247 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 18.364 ms | 4 - 289 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® SA7255P | 26.379 ms | 1 - 210 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Qualcomm® SA8295P | 14.995 ms | 1 - 214 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 4.956 ms | 0 - 229 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 14.715 ms | 0 - 230 MB | NPU
| FFNet-78S | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 3.594 ms | 1 - 249 MB | NPU

## License
* The license for the original implementation of FFNet-78S can be found
  [here](https://github.com/Qualcomm-AI-research/FFNet/blob/master/LICENSE).

## References
* [Simple and Efficient Architectures for Semantic Segmentation](https://arxiv.org/abs/2206.08236)
* [Source Model Implementation](https://github.com/Qualcomm-AI-research/FFNet)

## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).