| --- |
| library_name: pytorch |
| license: other |
| tags: |
| - backbone |
| - bu_auto |
| - android |
| pipeline_tag: image-classification |
|
|
| --- |
| |
|  |
|
|
| # ResNet50: Optimized for Qualcomm Devices |
|
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| ResNet50 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases. |
|
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| This is based on the implementation of ResNet50 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py). |
| This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/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. |
|
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| ## Getting Started |
| There are two ways to deploy this model on your device: |
|
|
| ### Option 1: Download Pre-Exported Models |
|
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| Below are pre-exported model assets ready for deployment. |
|
|
| | Runtime | Precision | Chipset | SDK Versions | Download | |
| |---|---|---|---|---| |
| | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-onnx-float.zip) |
| | ONNX | w8a8 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-onnx-w8a8.zip) |
| | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-qnn_dlc-float.zip) |
| | QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-qnn_dlc-w8a8.zip) |
| | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-tflite-float.zip) |
| | TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet50/releases/v0.59.0/resnet50-tflite-w8a8.zip) |
|
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| For more device-specific assets and performance metrics, visit **[ResNet50 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnet50)**. |
|
|
|
|
| ### Option 2: Export with Custom Configurations |
|
|
| Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/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 [ResNet50 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/resnet50) for usage instructions. |
|
|
| ## Model Details |
|
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| **Model Type:** Model_use_case.image_classification |
| |
| **Model Stats:** |
| - Model checkpoint: Imagenet |
| - Input resolution: 224x224 |
| - Number of parameters: 25.5M |
| - Model size (float): 97.4 MB |
| - Model size (w8a8): 25.1 MB |
| |
| ## Performance Summary |
| | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
| |---|---|---|---|---|---|--- |
| | ResNet50 | ONNX | float | Snapdragon® X2 Elite | 0.986 ms | 2 - 2 MB | NPU |
| | ResNet50 | ONNX | float | Snapdragon® X Elite | 1.917 ms | 50 - 50 MB | NPU |
| | ResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 1.465 ms | 0 - 79 MB | NPU |
| | ResNet50 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 3.19 ms | 0 - 63 MB | NPU |
| | ResNet50 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.971 ms | 0 - 58 MB | NPU |
| | ResNet50 | ONNX | float | Qualcomm® QCS8450 | 3.19 ms | 0 - 63 MB | NPU |
| | ResNet50 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 3.016 ms | 0 - 4 MB | NPU |
| | ResNet50 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 1.917 ms | 50 - 50 MB | NPU |
| | ResNet50 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 1.207 ms | 0 - 51 MB | NPU |
| | ResNet50 | ONNX | float | Snapdragon® 8 Elite Mobile | 1.207 ms | 0 - 51 MB | NPU |
| | ResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.054 ms | 0 - 53 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® X2 Elite | 0.41 ms | 1 - 1 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® X Elite | 0.833 ms | 25 - 25 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.678 ms | 0 - 83 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 1.204 ms | 0 - 85 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 3.71 ms | 0 - 3 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.905 ms | 0 - 67 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® QCS8450 | 1.204 ms | 0 - 85 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 1.007 ms | 0 - 3 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 0.833 ms | 25 - 25 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 0.577 ms | 0 - 49 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite Mobile | 0.577 ms | 0 - 49 MB | NPU |
| | ResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.559 ms | 0 - 50 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® X2 Elite | 1.247 ms | 1 - 1 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® X Elite | 2.332 ms | 1 - 1 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 1.607 ms | 0 - 79 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 3.734 ms | 0 - 61 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 10.725 ms | 1 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 2.212 ms | 0 - 3 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® SA8775P | 3.35 ms | 1 - 47 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® SA8650P | 3.35 ms | 1 - 47 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® SA8255P | 3.35 ms | 1 - 47 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® QCS8450 | 3.734 ms | 0 - 61 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 3.181 ms | 3 - 5 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 2.332 ms | 1 - 1 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 1.268 ms | 1 - 50 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 10.725 ms | 1 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 3.642 ms | 0 - 28 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 1.268 ms | 1 - 50 MB | NPU |
| | ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.1 ms | 1 - 49 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.529 ms | 0 - 0 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.945 ms | 0 - 0 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.678 ms | 0 - 78 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 1.193 ms | 0 - 79 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 3.77 ms | 0 - 2 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8275 | 2.05 ms | 0 - 45 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.893 ms | 0 - 2 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 1.089 ms | 0 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8650P | 1.089 ms | 0 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8255P | 1.089 ms | 0 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 1.193 ms | 0 - 79 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 0.986 ms | 0 - 2 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 0.945 ms | 0 - 0 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 6.612 ms | 0 - 164 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 1.224 ms | 0 - 51 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 0.536 ms | 0 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 2.05 ms | 0 - 45 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.431 ms | 0 - 42 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 0.536 ms | 0 - 46 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.494 ms | 0 - 44 MB | NPU |
| | ResNet50 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.224 ms | 0 - 51 MB | NPU |
| | ResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 1.586 ms | 0 - 112 MB | NPU |
| | ResNet50 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 3.729 ms | 0 - 97 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 10.664 ms | 0 - 69 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 2.218 ms | 0 - 2 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® SA8775P | 3.343 ms | 0 - 70 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® SA8650P | 3.343 ms | 0 - 70 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® SA8255P | 3.343 ms | 0 - 70 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® QCS8450 | 3.729 ms | 0 - 97 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 3.125 ms | 0 - 52 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 1.25 ms | 0 - 72 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® SA7255P | 10.664 ms | 0 - 69 MB | NPU |
| | ResNet50 | TFLITE | float | Qualcomm® SA8295P | 3.636 ms | 0 - 50 MB | NPU |
| | ResNet50 | TFLITE | float | Snapdragon® 8 Elite Mobile | 1.25 ms | 0 - 72 MB | NPU |
| | ResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.09 ms | 0 - 66 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.569 ms | 0 - 73 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 1.05 ms | 0 - 81 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 3.649 ms | 0 - 27 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS8275 | 1.755 ms | 0 - 42 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.758 ms | 0 - 1 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® SA8775P | 0.964 ms | 0 - 45 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® SA8650P | 0.964 ms | 0 - 45 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® SA8255P | 0.964 ms | 0 - 45 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® QCS8450 | 1.05 ms | 0 - 81 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 0.89 ms | 0 - 27 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 6.191 ms | 0 - 161 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 1.096 ms | 0 - 49 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 0.485 ms | 0 - 40 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® SA7255P | 1.755 ms | 0 - 42 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Qualcomm® SA8295P | 1.278 ms | 0 - 40 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite Mobile | 0.485 ms | 0 - 40 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.448 ms | 0 - 47 MB | NPU |
| | ResNet50 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.096 ms | 0 - 49 MB | NPU |
| |
| ## License |
| * The license for the original implementation of ResNet50 can be found |
| [here](https://github.com/pytorch/vision/blob/main/LICENSE). |
| |
| ## References |
| * [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) |
| * [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/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). |
| |