ValueError: expected 4D input (got 3D input)

This error is typically raised when you are trying to feed a 3D data into a neural network model that expects a 4D input.

In general, a 4D input tensor has the following dimensions: (batch_size, height, width, channels). Whereas, a 3D tensor has the following dimensions: (height, width, channels).

To fix this error, you need to reshape your input data to have a batch dimension. This can be achieved using the `reshape()` method in NumPy or TensorFlow, depending on the framework you are using.

For example, if you have a 3D input tensor `x` with dimensions (height, width, channels), you can add a batch dimension by using the following code in NumPy:

x = x.reshape(1, height, width, channels)

Similarly, in TensorFlow, you can use the `tf.expand_dims()` method to add a batch dimension:

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

By adding a batch dimension, you can now feed your 3D input data into a neural network model that expects a 4D input.