My tf version is 2.18 that doesn’t support pb file.
So i searched on google and then wrote these code.
import os
import tensorflow as tf
from tensorflow.keras.preprocessing import image
pb_model_dir = "model_data/"
h5_model = "./saved_model.h5"
# Loading the Tensorflow Saved Model (PB)
model = tf.saved_model.load(pb_model_dir)
# Saving the Model in H5 Format
tf.keras.models.save_model(model, h5_model)
But there is a error
AttributeError: '_UserObject' object has no attribute 'get_config'
I tried tf.keras.models.load_model too but the there is also a error
File format not supported: filepath=model_data/. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(model_data/, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).
Many people seem to solve this problem by using one of above ways, but it didn’t work at my environment. How to convert pb file to h5??