From 2177e08f64edd7576d243745e289cbdc3e646ca9 Mon Sep 17 00:00:00 2001 From: dengliu1105 <842031513@qq.com> Date: Tue, 27 Jan 2026 09:33:45 +0800 Subject: [PATCH] Delete unnecessary readme file --- README.md | 2 -- README_CN.md | 77 ---------------------------------------------------- 2 files changed, 79 deletions(-) delete mode 100644 README_CN.md diff --git a/README.md b/README.md index c6ae85f..491648e 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,3 @@ -[简体中文](README_CN.md) | [English](README.md)
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@@ -85,4 +84,3 @@ ​ - diff --git a/README_CN.md b/README_CN.md deleted file mode 100644 index 6450deb..0000000 --- a/README_CN.md +++ /dev/null @@ -1,77 +0,0 @@ -[简体中文](README_CN.md) | [English](README.md) - -# amlnn-model-playground - -# 简介 - -​ **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。 - -**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。 - - - -# 依赖项 - -- **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。 -- **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 -- **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/ - -# 支持列表 - -| Category | Model_name | Dtype | Platform | -| ---------------------- | ------------------------------------------------------------ | ------ | ------------- | -| 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 | -| Classification | [resnet50-v2](https://github.com/onnx/models/blob/8e893eb39b131f6d3970be6ebd525327d3df34ea/vision/classification/resnet/model/resnet50-v2-7.onnx) | INT8 | A311D2/S905X5 | -| Object Detection | [yolov8](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 | -| Object Detection | [yolov11](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 | -| Object Detection | [yoloworld](https://github.com/AILab-CVC/YOLO-World) | INT8 | A311D2/S905X5 | -| Object Detection | [yoloe](https://github.com/ultralytics/ultralytics) | INT8 | A311D2/S905X5 | -| Face Key Points | [retinaface](https://github.com/biubug6/Pytorch_Retinaface) | INT8 | A311D2/S905X5 | -| Text Detection | ppocr-det | INT8 | A311D2/S905X5 | -| Pose Estimation | blazepose_detect | INT8 | A311D2/S905X5 | -| Pose Estimation | blazepose_landmark | INT8 | A311D2/S905X5 | -| Voiceprint recognition | [ECAPA-TDNN](https://github.com/TaoRuijie/ECAPA-TDNN) | Hybrid | A311D2/S905X5 | -| Speech Recognition | [whisper](https://github.com/openai/whisper) | Hybrid | A311D2/S905X5 | -| Image-Text Matching | [clip](https://huggingface.co/openai/clip-vit-base-patch32) | Hybrid | A311D2/S905X5 | -| Chat LLM | deepseek | Hybrid | A311D2/S905X5 | - - - -# Benchmark List(FPS) - -| Examples | Model_name | input_shapes | Dtype | S905X5 | A311D2 | -| ------------------ | ------------ | ---------------- | ----- | ------ | ------ | -| mobilenet | mobilenet_v2 | [1, 3, 224, 224] | INT8 |1047.54 | 798.94 | -| resnet | resnet50-v2 | [1, 3, 224, 224] | INT8 | 106.78 | 128.91 | -| yolov8 | yolov8l | [1, 3, 640, 640] | INT8 | 11.55 | 11.12 | -| yolov11 | yolov11n | [1, 3, 640, 640] | INT8 | 41.14 | 41.48 | -| yoloworld | yoloworld | [1, 3, 480, 640] | INT8 | 19.38 | 19.04 | -| yoloe | yoloe | [1, 3, 288, 512] | INT8 | 53.9 | 37.8 | -| retinaface | retinaface | [1, 3, 320, 320] | INT8 | 341.99 | 305.89 | -| ppocr-det | paddleocrv4-det | [1, 3, 640, 640] | INT8 | 37.66 | 38.85 | -| blazepose_detect | blazepose_detection | [1, 3, 224, 224] | INT8 | 476.29 | 461.74 | -| blazepose_landmark | blazepose_landmark_full | [1, 3, 256, 256] | INT16 | 84.59 | 70.31 | -| Whisper | encoder_tiny_en | [1, 80, 3000] | Hybrid | 0.71 | 0.58 | -| Whisper | decoder_tiny_en | [1, 1500, 384]&[1, 48] | Hybrid | 10.35 | 9.22 | -| Clip | clip-vit-base-patch32 | [1, 3, 224, 224] | Hybrid | 7.48 | 6.82 | - -- 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。 -- \表示暂时不支持。 - -# Examples 编译 - -​ 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** - - - -# **Release Notes** - -| Version | Description | -| ------- | ------------- | -| 1.0.0 | First Version | - - - - - -​ \ No newline at end of file