運行 Keras h5 model

Question

我正在嘗試運行這個 h5 model 在這里找到的 ALASKA2 圖像隱寫分析比賽。

我想使用以下代碼預測 RGB 圖像c1.bmp的 label：

import efficientnet.tfkeras as efn
import tensorflow as tf
from tensorflow import keras
import numpy as np


def decode_image(filename, image_size=(512, 512)):
    bits = tf.io.read_file(filename)
    image = tf.image.decode_bmp(bits, channels=3)
    image = tf.cast(image, tf.float32) / 255.0
    image = tf.image.resize(image, image_size)

    return image


img = decode_image('imgs/c1.bmp')
model = keras.models.load_model("model.h5")
print(model.predict(img, verbose=1))

但是，運行此代碼會導致此錯誤：

File "alaska.py", line 20, in <module>
    print(model.predict(img, verbose=1))
  File "Python38\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1629, in predict
    tmp_batch_outputs = self.predict_function(iterator)
  File "Python38\lib\site-packages\tensorflow\python\eager\def_function.py", line 828, in __call__
    result = self._call(*args, **kwds)
  File "Python38\lib\site-packages\tensorflow\python\eager\def_function.py", line 871, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "Python38\lib\site-packages\tensorflow\python\eager\def_function.py", line 725, in _initialize
    self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
  File "Python38\lib\site-packages\tensorflow\python\eager\function.py", line 2969, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "Python38\lib\site-packages\tensorflow\python\eager\function.py", line 3361, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "Python38\lib\site-packages\tensorflow\python\eager\function.py", line 3196, in _create_graph_function
    func_graph_module.func_graph_from_py_func(
  File "Python38\lib\site-packages\tensorflow\python\framework\func_graph.py", line 990, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "Python38\lib\site-packages\tensorflow\python\eager\def_function.py", line 634, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "Python38\lib\site-packages\tensorflow\python\framework\func_graph.py", line 977, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

    Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1478 predict_function  *
        return step_function(self, iterator)
    Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1468 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1259 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2730 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
   Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3417 _call_for_each_replica
        return fn(*args, **kwargs)
    Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1461 run_step  **
        outputs = model.predict_step(data)
    Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1434 predict_step
        return self(x, training=False)
    Python38\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:998 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
    Python38\lib\site-packages\tensorflow\python\keras\engine\input_spec.py:271 assert_input_compatibility
        raise ValueError('Input ' + str(input_index) +

    ValueError: Input 0 is incompatible with layer sequential: expected shape=(None, 512, 512, 3), found shape=(32, 512, 3)

我有 Python 3.8.7 和 tensorflow 2.4.1 並使用 Pycharm 在 ZAEA234288CE0A39 中。

這個錯誤是什么意思，我該如何解決？

Answer 1

您忘記添加批次維度。 只需將以下轉換添加到ddecode_image function：

image = tf.expand_dims(image, axis=0)