Tensorflow对象检测-将.pb文件转换为tflite

Question

我尝试将冻结的SSD mobilenet v2模型转换为TFLITE格式以供Android使用。这是我所有的步骤：

1. 我使用模型动物园的ssd_mobilenet_v2_coco_2018_03_29模型对TF Object Detection API的train.py文件进行了重新训练。（好）

2. 使用TF Object Detection API也提供的export_inference_graph.p y 将训练后的model.ckpt导出到冻结的模型文件。（好）

3. 使用GPU和仅允许CPU在python中测试冻结的图形。有用。（好）

不利之处在于，我尝试使用以下代码：

import tensorflow as tf
tf.enable_eager_execution()
saved_model_dir = 'inference_graph/saved_model/'
converter = tf.contrib.lite.TFLiteConverter.from_saved_model(saved_model_dir,input_arrays=input_arrays,output_arrays=output_arrays,input_shapes={"image_tensor": [1, 832, 832, 3]})
converter.post_training_quantize = True

首先，我尝试不向函数添加输入shapes参数，但是没有用。从那时起，我读到您可以在这里写任何无关紧要的内容。

直到这一行的输出：

INFO:tensorflow:Saver not created because there are no variables in the graph to restore
INFO:tensorflow:The specified SavedModel has no variables; no checkpoints were restored.
INFO:tensorflow:The given SavedModel MetaGraphDef contains SignatureDefs with the following keys: {'serving_default'}
INFO:tensorflow:input tensors info: 
INFO:tensorflow:Tensor's key in saved_model's tensor_map: inputs
INFO:tensorflow: tensor name: image_tensor:0, shape: (-1, -1, -1, 3), type: DT_UINT8
INFO:tensorflow:output tensors info: 
INFO:tensorflow:Tensor's key in saved_model's tensor_map: num_detections
INFO:tensorflow: tensor name: num_detections:0, shape: (-1), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: detection_boxes
INFO:tensorflow: tensor name: detection_boxes:0, shape: (-1, 100, 4), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: detection_scores
INFO:tensorflow: tensor name: detection_scores:0, shape: (-1, 100), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: detection_classes
INFO:tensorflow: tensor name: detection_classes:0, shape: (-1, 100), type: DT_FLOAT
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
INFO:tensorflow:The specified SavedModel has no variables; no checkpoints were restored.
INFO:tensorflow:Froze 0 variables.
INFO:tensorflow:Converted 0 variables to const ops.

然后我想转换：

tflite_quantized_model = converter.convert()

这是输出：

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-6-61a136476642> in <module>
----> 1 tflite_quantized_model = converter.convert()

~/.local/lib/python3.5/site-packages/tensorflow/contrib/lite/python/lite.py in convert(self)
    451           input_tensors=self._input_tensors,
    452           output_tensors=self._output_tensors,
--> 453           **converter_kwargs)
    454     else:
    455       # Graphs without valid tensors cannot be loaded into tf.Session since they

~/.local/lib/python3.5/site-packages/tensorflow/contrib/lite/python/convert.py in toco_convert_impl(input_data, input_tensors, output_tensors, *args, **kwargs)
    340   data = toco_convert_protos(model_flags.SerializeToString(),
    341                              toco_flags.SerializeToString(),
--> 342                              input_data.SerializeToString())
    343   return data
    344 

~/.local/lib/python3.5/site-packages/tensorflow/contrib/lite/python/convert.py in toco_convert_protos(model_flags_str, toco_flags_str, input_data_str)
    133     else:
    134       raise RuntimeError("TOCO failed see console for info.\n%s\n%s\n" %
--> 135                          (stdout, stderr))
    136 
    137 

RuntimeError: TOCO failed see console for info.

我无法在此处复制控制台输出，因此它超出了30000个字符的限制，但是在这里您可以看到它：https : //pastebin.com/UyT2x2Vk

在这一点上，请帮助，我应该怎么做才能使它:(

我的配置：Ubuntu 16.04，Tensorflow-GPU 1.12

感谢andvance！

Answer 1

上周遇到了同样的问题，请按照此处描述的步骤解决。

基本上，问题在于它们的主脚本不支持SSD模型。我没有使用bazel它，但是使用了tflite_convert实用程序。

export_tflite_ssd_graph.py在使用脚本之前，请仔细阅读其所有选项（主要是--max_detections挽救了我的性命）。

希望这可以帮助。

编辑：您的第2步无效。如果save_model包含SSD，则无法将其转换为tflite模型。您需要使用export_tflite_ssd_graph.py脚本导出训练有素的model.ckpt，并使用.pb创建的文件通过该tflite_convert工具将其转换为tflite 。