---
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/fcn_resnet50/web-assets/model_demo.png)

# FCN-ResNet50: Optimized for Qualcomm Devices

FCN_ResNet50 is a machine learning model that can segment images from the COCO dataset. It uses ResNet50 as a backbone.

This is based on the implementation of FCN-ResNet50 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/segmentation/fcn.py).
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/fcn_resnet50) 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 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/fcn_resnet50/releases/v0.46.0/fcn_resnet50-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[FCN-ResNet50 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/fcn_resnet50)**.


### 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/fcn_resnet50) 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 [FCN-ResNet50 on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/fcn_resnet50) for usage instructions.

## Model Details

**Model Type:** Model_use_case.semantic_segmentation

**Model Stats:**
- Model checkpoint: COCO_WITH_VOC_LABELS_V1
- Input resolution: 224x224
- Number of output classes: 21
- Number of parameters: 33.0M
- Model size (float): 126 MB
- Model size (w8a8): 32.2 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| FCN-ResNet50 | ONNX | float | Snapdragon® X Elite | 43.753 ms | 63 - 63 MB | NPU
| FCN-ResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 32.391 ms | 2 - 314 MB | NPU
| FCN-ResNet50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 43.223 ms | 0 - 81 MB | NPU
| FCN-ResNet50 | ONNX | float | Qualcomm® QCS9075 | 74.573 ms | 3 - 9 MB | NPU
| FCN-ResNet50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 26.542 ms | 1 - 239 MB | NPU
| FCN-ResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 20.443 ms | 2 - 255 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Snapdragon® X Elite | 13.859 ms | 32 - 32 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 9.935 ms | 0 - 231 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Qualcomm® QCS6490 | 921.792 ms | 67 - 115 MB | CPU
| FCN-ResNet50 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 13.896 ms | 0 - 220 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Qualcomm® QCS9075 | 15.973 ms | 1 - 4 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Qualcomm® QCM6690 | 824.792 ms | 76 - 85 MB | CPU
| FCN-ResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 8.414 ms | 1 - 156 MB | NPU
| FCN-ResNet50 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 700.625 ms | 71 - 79 MB | CPU
| FCN-ResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 6.998 ms | 1 - 197 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Snapdragon® X Elite | 44.072 ms | 3 - 3 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 33.401 ms | 0 - 382 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 272.088 ms | 1 - 305 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 44.864 ms | 3 - 6 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® SA8775P | 72.053 ms | 1 - 304 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® QCS9075 | 78.033 ms | 3 - 8 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 84.665 ms | 1 - 276 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 272.088 ms | 1 - 305 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 77.345 ms | 0 - 217 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 25.991 ms | 3 - 323 MB | NPU
| FCN-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 23.219 ms | 3 - 330 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Snapdragon® X Elite | 15.207 ms | 1 - 1 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 11.408 ms | 0 - 266 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 92.892 ms | 1 - 3 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 39.344 ms | 1 - 205 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 15.051 ms | 1 - 3 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 14.56 ms | 1 - 214 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 16.824 ms | 3 - 5 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 407.762 ms | 1 - 347 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 23.958 ms | 1 - 263 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 39.344 ms | 1 - 205 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 21.86 ms | 1 - 209 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 8.765 ms | 1 - 198 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 25.963 ms | 1 - 280 MB | NPU
| FCN-ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 7.52 ms | 1 - 245 MB | NPU
| FCN-ResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 33.035 ms | 0 - 427 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 272.13 ms | 0 - 331 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 44.874 ms | 0 - 410 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® SA8775P | 72.05 ms | 0 - 333 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® QCS9075 | 77.817 ms | 0 - 71 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 84.565 ms | 1 - 319 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® SA7255P | 272.13 ms | 0 - 331 MB | NPU
| FCN-ResNet50 | TFLITE | float | Qualcomm® SA8295P | 77.444 ms | 0 - 247 MB | NPU
| FCN-ResNet50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 27.043 ms | 0 - 348 MB | NPU
| FCN-ResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 20.946 ms | 0 - 356 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 10.969 ms | 0 - 270 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCS6490 | 94.9 ms | 0 - 39 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 38.12 ms | 0 - 204 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 14.445 ms | 0 - 4 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® SA8775P | 14.511 ms | 0 - 207 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCS9075 | 15.341 ms | 0 - 35 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCM6690 | 433.506 ms | 2 - 353 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 23.285 ms | 0 - 269 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® SA7255P | 38.12 ms | 0 - 204 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Qualcomm® SA8295P | 21.104 ms | 0 - 209 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 8.433 ms | 0 - 200 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 26.062 ms | 0 - 281 MB | NPU
| FCN-ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 7.007 ms | 0 - 244 MB | NPU

## License
* The license for the original implementation of FCN-ResNet50 can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).

## References
* [Fully Convolutional Networks for Semantic Segmentation](https://arxiv.org/abs/1411.4038)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/segmentation/fcn.py)

## 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).