Hello, this is my very first Tenserflow project, Please help me to solve the issue below the description.
Traceback (most recent call last):
  File "C:\Tensorflow\workspace\training_demo\training2\1.py", line 40, in <module>
    model.add(ResNet50(include_top=False, pooling='avg', weights=resnet_weights_path))
  File "C:\Users\kamil\.conda\envs\tensorflow\lib\site-packages\tensorflow\python\keras\applications\resnet.py", line 457, in ResNet50
    return ResNet(stack_fn, False, True, 'resnet50', include_top, weights,
  File "C:\Users\kamil\.conda\envs\tensorflow\lib\site-packages\tensorflow\python\keras\applications\resnet.py", line 124, in ResNet
    raise ValueError('The `weights` argument should be either '
ValueError: The `weights` argument should be either `None` (random initialization), `imagenet` (pre-training on ImageNet), or the path to the weights file to be loaded.

(tensorflow) C:\Tensorflow\workspace\training_demo\training2>

Code:
image_size = 224

data_generator_with_aug = ImageDataGenerator(preprocessing_function=preprocess_input,

                                             horizontal_flip=True,

                                             width_shift_range=0.2,

                                             height_shift_range=0.2)

train_path='C:/Tensorflow/workspace/training_demo/training2/training'

train_generator = data_generator_with_aug.flow_from_directory(train_path,

                                                     target_size=(image_size, image_size),

                                                     batch_size=24,

                                                     class_mode='categorical')

data_generator_with_no_aug = ImageDataGenerator(preprocessing_function=preprocess_input)

validation_path='C:/Tensorflow/workspace/training_demo/training2/validation'

validation_generator = data_generator_with_no_aug.flow_from_directory(validation_path,

                                                          target_size=(image_size, image_size),

                                                          batch_size=24,

                                                          class_mode='categorical')

resnet_weights_path = 'C:/Tensorflow/workspace/training_demo/training2resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5'#'C:/Tensorflow/workspace/training_demo/training2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5'

#resnet_weights_path = 'C:/Users/kamil/.keras/models/resnet50_weights_th_dim_ordering_th_kernels_notop.h5'

model = Sequential()

model.add(ResNet50(include_top=False, pooling='avg', weights=resnet_weights_path))

num_classes = 10

model.add(Dense(num_classes, activation='softmax'))

# Say not to train first layer (ResNet) model. It is already trained

model.layers[0].trainable = False

model.compile(optimizer='sgd', loss='categorical_crossentropy', metrics=['accuracy'])

model.fit_generator(train_generator,

steps_per_epoch=3,

epochs=20,

validation_data=validation_generator,

validation_steps=1)

I use my images and my json file with 3 classes.