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77 lines
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5 KiB
Markdown
[简体中文](README_CN.md) | [English](README.md)
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# amlnn-model-playground
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# 简介
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**amlnn-model-playground**是基于**amlnn toolkit**完成**模型转换**与**部署**，实现主流常用算法的model zoo。demo包中提供完整的模型转换脚本，以及使用 **Python API**，**OpenAI API** 和 **C API** 对转换后的模型进行推理运行的完整流程。
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**目的：** 帮助用户快速上手，完成算法模型在 Amlogic NPU平台上的部署。model zoo中丰富的算法库可以更好的指导客户AI产品落地。
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# 依赖项
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- **amlnn-model-playground** 中的模型转换功能目前依赖于 Amlogic 提供的模型转换工具 **`adla-toolkit-binary-x.x.x.x`**，当前默认使用本工程的客户均已获取该工具。下一版本我们将通过 GitHub Release 公开发布该模型转换工具，计划于 2026 年第一季度（2026Q1）正式发布。
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- **Android编译**依赖NDK工具链，当前建议使用**r25c**版本，下载链接:https://github.com/android/ndk/wiki/Unsupported-Downloads
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- **Linux编译**依赖工具链:**gcc-arm-10.3-2021.07-x86_64-arm-none-linux-gnueabihf** ,下载链接：https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads/
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# 支持列表
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| Category | Model_name | Dtype | Platform |
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| ---------------------- | ------------------------------------------------------------ | ------ | ------------- |
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| Classification | [mobilenet_v2](https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224_quant.tgz) | INT8 | A311D2/S905X5 |
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| Classification | [resnet50-v2](https://github.com/onnx/models/blob/8e893eb39b131f6d3970be6ebd525327d3df34ea/vision/classification/resnet/model/resnet50-v2-7.onnx) | INT8 | A311D2/S905X5 |
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| Object Detection | [yolov8](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 |
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| Object Detection | [yolov11](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 |
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| Object Detection | [yoloworld](https://github.com/AILab-CVC/YOLO-World) | INT8 | A311D2/S905X5 |
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| Object Detection | [yoloe](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 |
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| Face Key Points | [retinaface](https://github.com/biubug6/Pytorch_Retinaface) | INT8 | A311D2/S905X5 |
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| Text Detection | ppocr-det | INT8 | A311D2/S905X5 |
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| Pose Estimation | blazepose_detect | INT8 | A311D2/S905X5 |
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| Pose Estimation | blazepose_landmark | INT8 | A311D2/S905X5 |
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| Voiceprint recognition | [ECAPA-TDNN](https://github.com/TaoRuijie/ECAPA-TDNN) | Hybrid | A311D2/S905X5 |
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| Speech Recognition | [whisper](https://github.com/openai/whisper) | Hybrid | A311D2/S905X5 |
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| Image-Text Matching | [clip](https://huggingface.co/openai/clip-vit-base-patch32) | Hybrid | A311D2/S905X5 |
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| Chat LLM | deepseek | Hybrid | A311D2/S905X5 |
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# Benchmark List(FPS)
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| Examples | Model_name | input_shapes | Dtype | S905X5 | A311D2 |
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| ------------------ | ------------ | ---------------- | ----- | ------ | ------ |
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| mobilenet | mobilenet_v2 | [1, 3, 224, 224] | INT8 |1047.54 | 798.94 |
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| resnet | resnet50-v2 | [1, 3, 224, 224] | INT8 | 106.78 | 128.91 |
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| yolov8 | yolov8l | [1, 3, 640, 640] | INT8 | 11.55 | 11.12 |
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| yolov11 | yolov11n | [1, 3, 640, 640] | INT8 | 41.14 | 41.48 |
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| yoloworld | yoloworld | [1, 3, 480, 640] | INT8 | 19.38 | 19.04 |
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| yoloe | yoloe | [1, 3, 288, 512] | INT8 | 53.9 | 37.8 |
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| retinaface | retinaface | [1, 3, 320, 320] | INT8 | 341.99 | 305.89 |
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| ppocr-det | paddleocrv4-det | [1, 3, 640, 640] | INT8 | 37.66 | 38.85 |
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| blazepose_detect | blazepose_detection | [1, 3, 224, 224] | INT8 | 476.29 | 461.74 |
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| blazepose_landmark | blazepose_landmark_full | [1, 3, 256, 256] | INT16 | 84.59 | 70.31 |
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| Whisper | encoder_tiny_en | [1, 80, 3000] | Hybrid | 0.71 | 0.58 |
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| Whisper | decoder_tiny_en | [1, 1500, 384]&[1, 48] | Hybrid | 10.35 | 9.22 |
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| Clip | clip-vit-base-patch32 | [1, 3, 224, 224] | Hybrid | 7.48 | 6.82 |
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- 性能数据是使用natvie case测试出的模型在NPU上的运行时间，如无特殊说明，不包含前后处理的耗时。
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- \表示暂时不支持。
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# Examples 编译
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每个**example**目录下面都有**build-android.sh** 和**build-linux.sh**脚本，编译步骤参考对应example目录下的**README.md**文件的**第四章节**
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# **Release Notes**
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| Version | Description |
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| ------- | ------------- |
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| 1.0.0 | First Version |
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