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ResNet-Mixed-Convolution

Video Classification
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ResNet-Mixed-Convolution
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---
library_name: pytorch
license: other
tags:
- backbone
- android
pipeline_tag: video-classification

---

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

# ResNet-Mixed-Convolution: Optimized for Qualcomm Devices

ResNet Mixed Convolutions is a network with a mixture of 2D and 3D convolutions used for video understanding.

This is based on the implementation of ResNet-Mixed-Convolution found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/video/resnet.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/resnet_mixed) 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/resnet_mixed/releases/v0.46.0/resnet_mixed-onnx-float.zip)
| ONNX | w8a16 | Universal | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_mixed/releases/v0.46.0/resnet_mixed-onnx-w8a16.zip)
| QNN_DLC | float | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_mixed/releases/v0.46.0/resnet_mixed-qnn_dlc-float.zip)
| QNN_DLC | w8a16 | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_mixed/releases/v0.46.0/resnet_mixed-qnn_dlc-w8a16.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/resnet_mixed/releases/v0.46.0/resnet_mixed-tflite-float.zip)

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


### 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/resnet_mixed) 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 [ResNet-Mixed-Convolution on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/resnet_mixed) for usage instructions.

## Model Details

**Model Type:** Model_use_case.video_classification

**Model Stats:**
- Model checkpoint: Kinetics-400
- Input resolution: 112x112
- Number of parameters: 11.7M
- Model size (float): 44.6 MB
- Model size (w8a16): 11.5 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| ResNet-Mixed-Convolution | ONNX | float | Snapdragon® X Elite | 14.062 ms | 22 - 22 MB | NPU
| ResNet-Mixed-Convolution | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 9.988 ms | 2 - 235 MB | NPU
| ResNet-Mixed-Convolution | ONNX | float | Qualcomm® QCS8550 (Proxy) | 13.721 ms | 0 - 38 MB | NPU
| ResNet-Mixed-Convolution | ONNX | float | Qualcomm® QCS9075 | 27.604 ms | 2 - 5 MB | NPU
| ResNet-Mixed-Convolution | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 8.173 ms | 0 - 167 MB | NPU
| ResNet-Mixed-Convolution | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.86 ms | 2 - 167 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Snapdragon® X Elite | 9.123 ms | 12 - 12 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 6.522 ms | 1 - 195 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Qualcomm® QCS6490 | 1728.182 ms | 45 - 62 MB | CPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 8.78 ms | 0 - 232 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Qualcomm® QCS9075 | 9.303 ms | 1 - 4 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Qualcomm® QCM6690 | 890.317 ms | 106 - 113 MB | CPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 5.341 ms | 1 - 135 MB | NPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 881.492 ms | 105 - 112 MB | CPU
| ResNet-Mixed-Convolution | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 3.904 ms | 0 - 138 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Snapdragon® X Elite | 14.152 ms | 2 - 2 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 9.536 ms | 0 - 282 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 13.367 ms | 2 - 5 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Qualcomm® SA8775P | 25.055 ms | 1 - 223 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Qualcomm® QCS9075 | 27.978 ms | 2 - 6 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 27.577 ms | 0 - 240 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Qualcomm® SA8295P | 26.689 ms | 0 - 192 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 7.684 ms | 2 - 227 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.76 ms | 2 - 233 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Snapdragon® X Elite | 9.877 ms | 1 - 1 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 6.654 ms | 1 - 255 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® QCS6490 | 37.276 ms | 1 - 4 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 9.22 ms | 1 - 3 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® SA8775P | 9.288 ms | 1 - 191 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 10.377 ms | 1 - 4 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 178.522 ms | 1 - 208 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® QCS8450 (Proxy) | 12.996 ms | 1 - 255 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Qualcomm® SA8295P | 16.239 ms | 1 - 192 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 5.261 ms | 1 - 186 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 15.94 ms | 1 - 197 MB | NPU
| ResNet-Mixed-Convolution | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 3.995 ms | 1 - 190 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 218.735 ms | 0 - 313 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 585.16 ms | 0 - 252 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 313.312 ms | 0 - 2 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® SA8775P | 296.864 ms | 0 - 252 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® QCS9075 | 321.486 ms | 0 - 28 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 345.498 ms | 0 - 277 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® SA7255P | 585.16 ms | 0 - 252 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Qualcomm® SA8295P | 353.223 ms | 0 - 234 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 203.459 ms | 0 - 257 MB | NPU
| ResNet-Mixed-Convolution | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 189.334 ms | 0 - 254 MB | NPU

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

## References
* [A Closer Look at Spatiotemporal Convolutions for Action Recognition](https://arxiv.org/abs/1711.11248)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/video/resnet.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).