What input shape should I take in first layer of Sequential model when the dimensions of the images are (2048*1536)
I would resize first the images with cv2.resize(). Do you really need all the information from such a big image?
For a sequential Model it follows for example:

model = models.Sequential()
model.add(layers.Conv2D(32,(3,3), activation='relu', input_shape = (height,width, ndim)))
...,
where height and width denote your input image dimensions and ndim = 1 for greyscale and ndim = 3 for colored images.
I am having an image dataset each image is of dimensions=(2048,1536).In ImageDataGenerator to fetch data from the directory, I have used the same target size i.e (2048,1536) but while making Sequential model first layer, what input shape should I have to use?? Will it be same as (2048,1536) or I can take any random shape like (224,224).