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移动端AI与ML应用开发:基于iOS和Android
book

移动端AI与ML应用开发:基于iOS和Android

by Laurence Moroney
January 2023
Intermediate to advanced
288 pages
6h 6m
Chinese
China Machine Press
Content preview from 移动端AI与ML应用开发:基于iOS和Android
134
|
8
8.3.2
编写
Kotlin
代码与模型交互
尽管你使用的是 Kotlin,但你的源文件位于
java
目录中。打开它,你会看到一个包含你
的包名称的文件夹。你应该在其中看到
MainActivity.kt
文件。双击此文件在代码编辑器
中打开它。
首先,你需要一个从
assets
目录加载 TensorFlow Lite 模型的辅助函数:
private fun loadModelFile(assetManager: AssetManager,
modelPath: String): ByteBuffer {
val fileDescriptor = assetManager.openFd(modelPath)
val inputStream = FileInputStream(fileDescriptor.fileDescriptor)
val fileChannel = inputStream.channel
val startOffset = fileDescriptor.startOffset
val declaredLength = fileDescriptor.declaredLength
return fileChannel.map(FileChannel.MapMode.READ_ONLY,
startOffset, declaredLength)
}
由于
.tflite
文件实际上是解释器将用来构建内部神经网络模型的权重和偏差的二进制区
块,因此它是 Android ...
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Publisher Resources

ISBN: 9787111713081