无法将冻结的模型文件.pb转换为.tflite

Question

import tensorflow as tf

path = "C:/Users/LAWSSSS/Desktop/convert_pb_2_tflite/frozen_inference_graph-SteelRoll.pb"

inputs = ["image_tensor"]
outputs = ["detection_boxes"]

converter = tf.lite.TFLiteConverter.from_frozen_graph(path, inputs, outputs, input_shapes={"image_tensor":[1,640,360,3]})
converter.post_training_quantize = True
tflite_model = converter.convert()

open("frozen_inference_graph-SteelRoll.tflite", "wb").write(tflite_model)

一般来说，我对Tensorflow是新手。我尝试使用上面的代码将.pb转换为.tflite。但是，我得到一个错误：

array.data_type == array.final_data_type Array "image_tensor" has mis-matching actual and final data types (data_type=uint8, final_data_type=float).
Fatal Python error: Aborted

我如何解决这个问题

Answer 1

将模型输入（图像张量占位符）更改为数据类型为tf.float32