ncnn-android-yolov5-master_yolov5手机版下载资源-CSDN下载

共712个文件

h：316个

cmake：60个

json：46个

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《ncnn-android-yolov5-master：Android平台上实现Yolov5的深度学习框架解析》在当前的计算机视觉领域，深度学习模型如Yolov5因其高效的实时目标检测性能而备受关注。ncnn是一个轻量级且高性能的深度学习推理框架，特别适合于移动端的应用。当将ncnn与Yolov5结合，可以为Android平台带来强大的目标检测功能。本文将详细介绍“ncnn-android-yolov5-master”项目，以及如何在Android设备上部署和运行这个工程。我们要了解Yolov5。YOLO（You Only Look Once）是一种基于深度学习的目标检测算法，以其快速和准确的特性受到广泛欢迎。Yolov5是该系列的最新版本，它在模型结构、训练策略和优化方面进行了改进，进一步提高了检测速度和精度。ncnn则是一个由腾讯优图实验室开发的C++推理库，专注于移动平台的神经网络计算，支持CPU、GPU等多种硬件加速。 “ncnn-android-yolov5-master”项目提供了将预训练的Yolov5模型移植到Android平台的完整解决方案。该压缩包包含以下关键文件和目录： 1. `model`：存储预训练的Yolov5模型权重文件，这是运行目标检测的核心部分。 2. `src`：源代码目录，包含了将ncnn模型转换为Android可执行代码的必要文件，如JNI接口和C++实现。 3. `jni`：Java Native Interface，用于Java层与C++层之间的通信，实现Android应用调用ncnn进行推理。 4. `Android.mk`和`Application.mk`：Android NDK构建系统文件，用于编译C++代码并生成.so动态链接库。 5. `AndroidManifest.xml`：Android应用的配置文件，定义了应用的基本属性和权限需求。 6. `build.gradle`：Gradle构建脚本，用于构建和打包Android应用。要成功运行这个项目，开发者需要具备以下基础知识： 1. Android开发：熟悉Android Studio，了解Activity、Intent等基本概念。 2. Java和C++编程：能够阅读和修改Java和C++代码。 3. Android NDK：理解NDK环境，能进行JNI编程。 4. ncnn框架：理解ncnn的API和模型加载流程。 5. Yolov5模型：了解其架构和预测过程。具体步骤如下： 1. 设置环境：确保安装了Android Studio、Android SDK、NDK，并配置好环境变量。 2. 导入项目：将“ncnn-android-yolov5-master”导入Android Studio。 3. 编译库：使用NDK编译源码，生成.so库文件。 4. 配置模型：将预训练的Yolov5模型权重文件放入合适的位置，并在代码中指定路径。 5. 运行应用：在Android设备或模拟器上运行应用，通过摄像头或上传图片进行目标检测。总结来说，“ncnn-android-yolov5-master”项目为开发者提供了一种在Android设备上实现Yolov5目标检测的便捷途径。通过理解ncnn框架、Yolov5模型以及Android应用开发的相关知识，开发者可以将这一技术应用于各种移动应用场景，如智能安防、自动驾驶、图像分析等。尽管实现过程涉及到多个技术层面，但随着对这些领域的深入理解和实践，开发者将能够灵活地在Android平台上构建自己的深度学习应用。

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ncnn-android-yolov5-master （712个子文件）

libncnn.a 20.6MB

libncnn.a 17.52MB

libncnn.a 11.06MB

libncnn.a 8.3MB

libMachineIndependent.a 4.25MB

libMachineIndependent.a 3.96MB

libMachineIndependent.a 3.52MB

libMachineIndependent.a 3.4MB

libSPIRV.a 1.26MB

libSPIRV.a 1.08MB

libSPIRV.a 1023KB

libSPIRV.a 943KB

libglslang.a 52KB

libglslang.a 43KB

libGenericCodeGen.a 25KB

libGenericCodeGen.a 23KB

libGenericCodeGen.a 22KB

libGenericCodeGen.a 17KB

libOSDependent.a 6KB

libOSDependent.a 5KB

libOSDependent.a 4KB

libOGLCompiler.a 4KB

libOGLCompiler.a 3KB

resources-debug.ap_ 2KB

resources-release.ap_ 2KB

com.tencent.yolov5ncnn-debug.apk 29.12MB

gradlew.bat 2KB

yolov5s.bin 27.56MB

executionHistory.bin 173KB

ompver_CXX.bin 80KB

CMakeDetermineCompilerABI_CXX.bin 80KB

CMakeDetermineCompilerABI_C.bin 80KB

feature_tests.bin 80KB

ompver_C.bin 80KB

fileHashes.bin 25KB

outputFiles.bin 22KB

taskHistory.bin 18KB

resourceHashesCache.bin 18KB

feature_tests.bin 14KB

ompver_CXX.bin 10KB

CMakeDetermineCompilerABI_CXX.bin 10KB

CMakeDetermineCompilerABI_C.bin 10KB

ompver_C.bin 10KB

last-build.bin 1B

feature_tests.c 762B

OpenMPCheckVersion.c 622B

OpenMPTryFlag.c 102B

cmake.check_cache 86B

MainActivity.class 8KB

MainActivity$3.class 1KB

MainActivity$2.class 1KB

MainActivity$3.class 1KB

MainActivity$2.class 1KB

MainActivity$1.class 1KB

BuildConfig.class 723B

YoloV5Ncnn.class 669B

YoloV5Ncnn$Obj.class 610B

BuildConfig.class 588B

R$id.class 509B

R.class 451B

R$string.class 410B

R$layout.class 406B

CMakeCXXCompiler.cmake 6KB

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