Cannot resolve error in keras sequential model-CodePudding

I am working on a gesture recognition problem. For that I have a train set. Train set consists of multiple folders and each folder consists of a series of 30 images. From those images the model is trained. Also I have a csv file that contains the class label of each folder. The class labels are : "Left Swipe", "Right Swipe", "Stop", "Thumbs Down" and "Thumbs Up". Those labels are present in one np.array variable train_class. Now, I have created a CNN model then feeding that in a Sequential model.

The code is available in below GIT location https://github.com/subhrajyoti-ghosh/ML-and-Deep-Learning/blob/main/Gesture_Recognition.ipynb

But when I am trying to fit the model, I am receiving error. Can you please help me understanding the error and how to solve that?

CodePudding user response：

You are trying to use a TimeDistributed layer on a 2D input (batch_size, 256), which will not work, because the layer needs at least a 3D tensor. You should try using tf.keras.layers.RepeatVector:

import tensorflow as tf

resnet = tf.keras.applications.ResNet50(include_top=False,weights='imagenet',input_shape=(224,224,3))
cnn = tf.keras.Sequential([resnet])
cnn.add(tf.keras.layers.Conv2D(64,(2,2),strides=(1,1)))
cnn.add(tf.keras.layers.Conv2D(16,(3,3),strides=(1,1)))
cnn.add(tf.keras.layers.Flatten())

inputs = tf.keras.layers.Input(shape=(224,224,3))
x = cnn(inputs)
x = tf.keras.layers.RepeatVector(n=30)(x)
x = tf.keras.layers.GRU(16,return_sequences=True)(x)
x = tf.keras.layers.GRU(8)(x)
outputs = tf.keras.layers.Dense(5,activation='softmax')(x)
model = tf.keras.Model(inputs, outputs)

dummy_x = tf.random.normal((1, 224,224,3))
print(model.summary())
print(model(dummy_x))

Model: "model_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 input_14 (InputLayer)       [(None, 224, 224, 3)]     0         
                                                                 
 sequential_6 (Sequential)   (None, 256)               24121296  
                                                                 
 repeat_vector_2 (RepeatVect  (None, 30, 256)          0         
 or)                                                             
                                                                 
 gru_5 (GRU)                 (None, 30, 16)            13152     
                                                                 
 gru_6 (GRU)                 (None, 8)                 624       
                                                                 
 dense_7 (Dense)             (None, 5)                 45        
                                                                 
=================================================================
Total params: 24,135,117
Trainable params: 24,081,997
Non-trainable params: 53,120
_________________________________________________________________
None