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
hệ điều hành nhập khẩu

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
    khác:
        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，出现以下错误:TypeError: __init__() 得到了一个意外的关键字参数 'ragged'

是什么导致了错误，我该如何解决？

版本:凯拉斯 v2.3.1 tensorflow v1.13.1

编辑添加:

Traceback (cuộc gọi gần đây nhất):
  File "/home/pi/Documents/converted_keras/keras-script.py", line 18, in 
    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)

câu trả lời hay nhất

所以我尝试了上面提到的链接 teachable machine
事实证明，您导出的模型来自 tensorflow.keras 而不是直接来自 keras API。这两个是不同的。因此，在加载时可能会使用可能与 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，因为您的模型是使用 Tensorflow 的 keras 高级 api 保存的。将所有导入更改为 tensorflow.keras

变化:

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

để kết thúc này:

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

它将解决您的问题。

biên tập:
您的所有导入都应该来自 Keras hoặc tensorflow.keras。尽管是相同的 API，但很少有不同会导致此类问题。同样对于 tensorflow 后端 tf.keras 是首选，因为 Keras 2.3.0是最后一个主要版本，它将支持 tensorflow 以外的后端。

This release brings the API in sync with the tf.keras API as of TensorFlow 2.0. However note that it does not support most TensorFlow 2.0 features, in particular eager execution. If you need these features, use tf.keras. This is also the last major release of multi-backend Keras. Going forward, we recommend that users consider switching their Keras code to tf.keras in TensorFlow 2.0.

关于python - Keras 中意外的关键字参数 'ragged'，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/58878421/