怎么把.pb转换成.tflite？ [英] How to convert from .pb to .tflite?

问题描述

我使用 Pytorch 创建了一个对象检测模型，然后从 .pth 转换为 .onnx ，然后是 .pb ，但现在我需要将其转换为 .tflite 对于Android应用程序！怎么做？这是我的第一次。

I have created a object detection model using Pytorch and then converted from .pth to .onnx and then .pb, but now I need to convert it into .tflite for android app! How to do it? It's my first time.

input_arrays  = [64, 3, 224, 224] 

output_arrays = ? 

用于二进制分类。

我有是从pytorch完成的，但我发现要查看的所有内容都是来自keras或Tensorflow ...

I have done it from pytorch but everything I find to look at was from keras or Tensorflow...

这是我用来将其从 .pb 到 .tflie

converter = lite.TFLiteConverter.from_frozen_graph(
  model/model.pb , input_arrays, output arrays )
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)

!tflite_convert \
   --output_file= model/model.tflite \
   --graph_def_file= model/model.pb \
   --input_arrays= input_arrays \
   -- output_arrays= output_arrays

我认为这与输入数组有关和输出数组，但不确定。 graph_def_file 应该存储 model.pb 吗？

I think it has something to do with input arrays and output arrays, but not sure about it. Is graph_def_file supposed to store model.pb ?

推荐答案

使用以下代码时，无需指定输入和输出数组：

No need to specify input and output array, when using the following code:

import tensorflow as tf

converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)

尝试

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