Keras中意外的关键字参数'ragged‘

Question

尝试使用以下python代码运行经过训练的keras模型：

from keras.preprocessing.image import img_to_array
from keras.models import load_model

from imutils.video import VideoStream
from threading import Thread
import numpy as np
import imutils
import time
import cv2
import os

MODEL_PATH = "/home/pi/Documents/converted_keras/keras_model.h5"

print("[info] loading model..")
model = load_model(MODEL_PATH)


print("[info] starting vid stream..")
vs = VideoStream(usePiCamera=True).start()
time.sleep(2.0)

while True:
    frame = vs.Read()
    frame = imutils.resize(frame, width=400)

    image = cv2.resize(frame, (28, 28))
    image = image.astype("float") / 255.0
    image = img_to_array(image)
    image = np.expand_dims(image, axis=0)
    (fuel, redBall, whiteBall, none) = model.predict(image)[0]
    label = "none"
    proba = none

    if fuel > none and fuel > redBall and fuel > whiteBall:
        label = "Fuel"
        proba = fuel
    elif redBall > none and redBall > fuel and redBall > whiteBall:
        label = "Red Ball"
        proba = redBall
    elif whiteBall > none and whiteBall > redBall and whiteBall > fuel:
        label = "white ball"
        proba = whiteBall
    else:
        label = "none"
        proba = none

    label = "{}:{:.2f%}".format(label, proba * 100)
    frame = cv2.putText(frame, label, (10, 25),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF

    if key == ord("q"):
        break

print("[info] cleaning up..")
cv2.destroyAllWindows()
vs.stop()

当我用python3运行它时，我得到了以下错误：TypeError: __init__() got an unexpected keyword argument 'ragged'

是什么导致了这个错误，我该如何避免呢？

版本: Keras v2.3.1 tensorflow v1.13.1

编辑以添加：

Traceback (most recent call last):
  File "/home/pi/Documents/converted_keras/keras-script.py", line 18, in <module>
    model = load_model(MODEL_PATH)
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/saving.py", line 492, in load_wrapper
    return load_function(*args, **kwargs)
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/saving.py", line 584, in load_model
    model = _deserialize_model(h5dict, custom_objects, compile)
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/saving.py", line 274, in _deserialize_model
    model = model_from_config(model_config, custom_objects=custom_objects)
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/saving.py", line 627, in model_from_config
    return deserialize(config, custom_objects=custom_objects)
  File "/usr/local/lib/python3.7/dist-packages/keras/layers/__init__.py", line 168, in deserialize
    printable_module_name='layer')
  File "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py", line 147, in deserialize_keras_object
    list(custom_objects.items())))
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/sequential.py", line 301, in from_config
    custom_objects=custom_objects)
  File "/usr/local/lib/python3.7/dist-packages/keras/layers/__init__.py", line 168, in deserialize
    printable_module_name='layer')
  File "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py", line 147, in deserialize_keras_object
    list(custom_objects.items())))
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/sequential.py", line 301, in from_config
    custom_objects=custom_objects)
  File "/usr/local/lib/python3.7/dist-packages/keras/layers/__init__.py", line 168, in deserialize
    printable_module_name='layer')
  File "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py", line 147, in deserialize_keras_object
    list(custom_objects.items())))
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/network.py", line 1056, in from_config
    process_layer(layer_data)
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/network.py", line 1042, in process_layer
    custom_objects=custom_objects)
  File "/usr/local/lib/python3.7/dist-packages/keras/layers/__init__.py", line 168, in deserialize
    printable_module_name='layer')
  File "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py", line 149, in deserialize_keras_object
    return cls.from_config(config['config'])
  File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1179, in from_config
    return cls(**config)
  File "/usr/local/lib/python3.7/dist-packages/keras/legacy/interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)
TypeError: __init__() got an unexpected keyword argument 'ragged'

h5 file link (google drive)

Answer 1

所以我尝试了上面你提到的teachable machine的链接

事实证明，您导出的模型是从tensorflow.keras导出的，而不是直接从keras应用编程接口导出的。这两个是不同的。因此，在加载它时，可能会使用与keras API不兼容的tf.ragged张量。

您的问题的解决方案：

不要直接导入keras，因为您的模型是用Tensorflow的keras高级api保存的。将所有导入更改为tensorflow.keras

更改：

from keras.preprocessing.image import img_to_array
from keras.models import load_model

要这样做：

from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model

它会解决你的问题。

编辑:

您的所有导入都应该来自Keras或tensorflow.keras。尽管API是相同的，但几乎没有什么不同的东西，这就造成了这些问题。此外，对于tensorflow后端，tf.keras是首选，因为Keras 2.3.0是支持tensorflow以外的后端的最后一个主要版本。

从TensorFlow 2.0开始，此版本使

与tf.keras API保持同步。但是请注意，它不支持大多数TensorFlow 2.0特性，特别是急切执行。如果您需要这些功能，请使用tf.keras。这也是多后端Keras的最后一个主要版本。展望未来，我们建议用户考虑在TensorFlow 2.0中将他们的Keras代码切换到tf.keras。

Answer 2

正如@Vivek Mehta所说，首先将load_model从keras更改为tensorflow.keras，即

from tensorflow.keras.models import load_model

但即便如此，如果模型加载显示错误，如KeyError: 'sample_weight_mode'，请执行以下操作

from tensorflow.keras.models import load_model

model = load_model('model.h5', compile = False)