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EfficientNet-Lite4

Image Classification
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android
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v0.57.0

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See https://github.com/qualcomm/ai-hub-models/releases/v0.57.0 for changelog.

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  1. LICENSE +1 -0
  2. README.md +173 -0
  3. release_assets.json +53 -0
LICENSE ADDED
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+ The license of the original trained model can be found at https://github.com/RangiLyu/EfficientNet-Lite/blob/main/LICENSE.
README.md ADDED
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+ ---
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+ library_name: pytorch
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+ license: other
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+ tags:
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+ - backbone
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+ - bu_auto
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+ - android
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+ pipeline_tag: image-classification
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+
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+ ---
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+
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+ ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/web-assets/model_demo.png)
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+
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+ # EfficientNet-Lite4: Optimized for Qualcomm Devices
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+
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+ EfficientNet-Lite4 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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+
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+ This is based on the implementation of EfficientNet-Lite4 found [here](https://github.com/RangiLyu/EfficientNet-Lite).
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+ 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/v0.57.0/src/qai_hub_models/models/efficientnet_lite4) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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+
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+ 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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+
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+ ## Getting Started
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+ There are two ways to deploy this model on your device:
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+
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+ ### Option 1: Download Pre-Exported Models
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+
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+ Below are pre-exported model assets ready for deployment.
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+
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+ | Runtime | Precision | Chipset | SDK Versions | Download |
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+ |---|---|---|---|---|
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+ | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.26.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-onnx-float.zip)
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+ | ONNX | w8a8 | Universal | QAIRT 2.45, ONNX Runtime 1.26.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-onnx-w8a8.zip)
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+ | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-qnn_dlc-float.zip)
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+ | QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-qnn_dlc-w8a8.zip)
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+ | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-tflite-float.zip)
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+ | TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-tflite-w8a8.zip)
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+
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+ For more device-specific assets and performance metrics, visit **[EfficientNet-Lite4 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/efficientnet_lite4)**.
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+
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+
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+ ### Option 2: Export with Custom Configurations
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+
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+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.57.0/src/qai_hub_models/models/efficientnet_lite4) Python library to compile and export the model with your own:
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+ - Custom weights (e.g., fine-tuned checkpoints)
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+ - Custom input shapes
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+ - Target device and runtime configurations
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+
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+ This option is ideal if you need to customize the model beyond the default configuration provided here.
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+
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+ See our repository for [EfficientNet-Lite4 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.57.0/src/qai_hub_models/models/efficientnet_lite4) for usage instructions.
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+
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+ ## Model Details
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+
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+ **Model Type:** Model_use_case.image_classification
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+
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+ **Model Stats:**
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+ - Model checkpoint: Imagenet
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+ - Input resolution: 300x300
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+ - Number of parameters: 13.01M
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+ - Model size (float): 51.9 MB
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+
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+ ## Performance Summary
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+ | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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+ |---|---|---|---|---|---|---
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® X2 Elite | 1.454 ms | 1 - 1 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® X Elite | 2.739 ms | 29 - 29 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 1.905 ms | 0 - 101 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 5.519 ms | 1 - 103 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 2.627 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Qualcomm® QCS8450 | 5.519 ms | 1 - 103 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® 8 Elite Mobile | 1.5 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Qualcomm® QCS9075 | 4.109 ms | 1 - 4 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.141 ms | 0 - 57 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Qualcomm® QCS8750 | 1.5 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | float | Qualcomm® QCS7181 | 2.739 ms | 29 - 29 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® X2 Elite | 0.638 ms | 1 - 1 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® X Elite | 1.259 ms | 15 - 15 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.858 ms | 0 - 109 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.079 ms | 0 - 116 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS6490 | 6.025 ms | 0 - 3 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.217 ms | 0 - 142 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS8450 | 2.079 ms | 0 - 116 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.586 ms | 0 - 72 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS9075 | 1.4 ms | 0 - 3 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.597 ms | 0 - 72 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Snapdragon® 8 Elite Mobile | 0.685 ms | 0 - 72 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCM6690 | 10.87 ms | 0 - 193 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS7790 | 1.597 ms | 0 - 72 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS8750 | 0.685 ms | 0 - 72 MB | NPU
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+ | EfficientNet-Lite4 | ONNX | w8a8 | Qualcomm® QCS7181 | 1.259 ms | 15 - 15 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® X2 Elite | 1.923 ms | 1 - 1 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® X Elite | 3.494 ms | 1 - 1 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.189 ms | 0 - 99 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 6.871 ms | 0 - 100 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS8275 | 15.29 ms | 1 - 53 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 3.157 ms | 1 - 3 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® SA8775P | 4.773 ms | 1 - 53 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® SA8650P | 4.773 ms | 1 - 53 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® SA8255P | 4.773 ms | 1 - 53 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS8450 | 6.871 ms | 0 - 100 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 1.686 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS9075 | 4.504 ms | 1 - 4 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® SA8295P | 6.451 ms | 1 - 50 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.268 ms | 1 - 57 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® SA7255P | 15.29 ms | 1 - 53 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS8750 | 1.686 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | float | Qualcomm® QCS7181 | 3.494 ms | 1 - 1 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.749 ms | 0 - 0 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® X Elite | 1.457 ms | 0 - 0 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.897 ms | 0 - 97 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.287 ms | 0 - 105 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 7.119 ms | 0 - 2 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS8275 | 3.346 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.258 ms | 0 - 10 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 1.605 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® SA8650P | 1.605 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® SA8255P | 1.605 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 2.287 ms | 0 - 105 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.509 ms | 0 - 66 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 3.346 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 1.409 ms | 2 - 4 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.627 ms | 0 - 63 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 0.641 ms | 0 - 65 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 11.088 ms | 0 - 184 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 2.491 ms | 0 - 59 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS7790 | 1.627 ms | 0 - 63 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS8750 | 0.641 ms | 0 - 65 MB | NPU
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+ | EfficientNet-Lite4 | QNN_DLC | w8a8 | Qualcomm® QCS7181 | 1.457 ms | 0 - 0 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.193 ms | 0 - 114 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 6.681 ms | 0 - 112 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® QCS8275 | 15.316 ms | 0 - 65 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.107 ms | 0 - 2 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® SA8775P | 4.819 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® SA8650P | 4.819 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® SA8255P | 4.819 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® QCS8450 | 6.681 ms | 0 - 112 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Snapdragon® 8 Elite Mobile | 1.687 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® QCS9075 | 4.524 ms | 0 - 32 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® SA8295P | 6.45 ms | 0 - 55 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.262 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® SA7255P | 15.316 ms | 0 - 65 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | float | Qualcomm® QCS8750 | 1.687 ms | 0 - 67 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.647 ms | 0 - 97 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 1.73 ms | 0 - 103 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS6490 | 5.697 ms | 0 - 30 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS8275 | 2.744 ms | 0 - 57 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.904 ms | 0 - 46 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® SA8775P | 1.269 ms | 0 - 60 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® SA8650P | 1.269 ms | 0 - 60 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® SA8255P | 1.269 ms | 0 - 60 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS8450 | 1.73 ms | 0 - 103 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.405 ms | 0 - 62 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® SA7255P | 2.744 ms | 0 - 57 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS9075 | 1.051 ms | 0 - 17 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.235 ms | 0 - 58 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Snapdragon® 8 Elite Mobile | 0.509 ms | 0 - 65 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCM6690 | 9.942 ms | 0 - 180 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® SA8295P | 2.116 ms | 0 - 54 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS7790 | 1.235 ms | 0 - 58 MB | NPU
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+ | EfficientNet-Lite4 | TFLITE | w8a8 | Qualcomm® QCS8750 | 0.509 ms | 0 - 65 MB | NPU
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+
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+ ## License
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+ * The license for the original implementation of EfficientNet-Lite4 can be found
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+ [here](https://github.com/RangiLyu/EfficientNet-Lite/blob/main/LICENSE).
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+
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+ ## References
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+ * [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946)
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+ * [Source Model Implementation](https://github.com/RangiLyu/EfficientNet-Lite)
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+
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+ ## Community
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+ * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
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+ * For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).
release_assets.json ADDED
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+ {
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+ "version": "0.57.0",
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+ "precisions": {
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+ "float": {
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+ "universal_assets": {
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+ "tflite": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327",
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+ "litert": "1.4.4"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-tflite-float.zip"
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+ },
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+ "qnn_dlc": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-qnn_dlc-float.zip"
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+ },
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+ "onnx": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327",
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+ "onnx_runtime": "1.26.0"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-onnx-float.zip"
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+ }
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+ }
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+ },
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+ "w8a8": {
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+ "universal_assets": {
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+ "tflite": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327",
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+ "litert": "1.4.4"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-tflite-w8a8.zip"
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+ },
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+ "qnn_dlc": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-qnn_dlc-w8a8.zip"
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+ },
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+ "onnx": {
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+ "tool_versions": {
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+ "qairt": "2.45.0.260326154327",
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+ "onnx_runtime": "1.26.0"
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+ },
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_lite4/releases/v0.57.0/efficientnet_lite4-onnx-w8a8.zip"
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+ }
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+ }
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+ }
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+ }
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+ }