如何将 .pb 转换为 TFLite 格式? [英] How to convert .pb to TFLite format?

问题描述

我下载了我在 Azure 认知服务中训练的模型的 retrained_graph.pb 和 retrained_labels.txt 文件.现在我想使用该模型制作一个 Android 应用程序，为此我必须将其转换为 TFLite 格式.我使用了 toco，但出现以下错误:

I downloaded a retrained_graph.pb and retrained_labels.txt file of a model I trained in Azure cognitive service. Now I want to make an Android app using that model and to do so I have to convert it to TFLite format. I used toco and I am getting the following error:

ValueError: Invalid tensors 'input' were found.

我基本上是按照本教程进行的，并且在第 4 步中遇到问题并且直接复制粘贴终端代码:https://heartbeat.fritz.ai/neural-networks-on-mobile-devices-with-tensorflow-lite-a-tutorial-85b41f53230c

I am basically following this tutorial and have problem on step 4 and direcly copy pasted the terminal code: https://heartbeat.fritz.ai/neural-networks-on-mobile-devices-with-tensorflow-lite-a-tutorial-85b41f53230c

推荐答案

我在这里胡乱猜测，也许您输入了 input_arrays=input.这可能不是真的.使用此脚本查找冻结推理图的输入和输出数组的名称

I am making a wild guess here, maybe you entered input_arrays=input. Which may not be true. Use this script to find the name of the input and output arrays of the frozen inference graph

import tensorflow as tf
gf = tf.GraphDef()   
m_file = open('frozen_inference_graph.pb','rb')
gf.ParseFromString(m_file.read())

with open('somefile.txt', 'a') as the_file:
    for n in gf.node:
        the_file.write(n.name+'\n')

file = open('somefile.txt','r')
data = file.readlines()
print "output name = "
print data[len(data)-1]

print "Input name = "
file.seek ( 0 )
print file.readline()

就我而言，它们是:

output name: SemanticPredictions
input name: ImageTensor

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