January 2023
Intermediate to advanced
288 pages
6h 6m
Chinese
Content preview from 移动端AI与ML应用开发：基于iOS和Android
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更深入：了解
TensorFlow Lite
|
133
<Button
android:id="@+id/convertButton"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:text="Convert">
</Button>
</LinearLayout>
</LinearLayout>
在开始编码之前，你需要将 TFLite 文件导入你的应用程序中。你可以看看接下来怎么做。
8.3.1
导入
TFLite
文件
首先要做的是在你的项目中创建一个资产文件夹。为此，请导航到项目资源管理器中的
app/src/main
文件夹，右键单击主文件夹并选择新建目录，称之为
assets
。将你在训练模
型后下载的
.tflite
文件拖到该目录中。如果你之前没有创建此文件，那么可以在本书的
GitHub 存储库中找到它。
如果你收到有关文件不在正确目录中的警告，因此模型绑定被禁用，那么忽略它是安全
的。模型绑定是我们稍后将探讨的，它适用于许多固定场景：它允许你轻松导入
.tflite
模型，不需要本示例中说明的许多手动步骤。在这里，我们将深入探讨如何在 Android
Studio 中使用 TFLite 文件的具体细节。
将资产添加到 Android Studio 后，你的项目资源管理器应该如图 8-3 所示。
图
8-3
：将
TFLite
文件添加为资产文件
现在一切都设置好了，我们可以开始编码了！ ...
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