Need to load 4D images into python array for cellpose analysis and Npari Display

Question

I'm out of my depth. I'm trying to load tiff stacks of X = 512, Y = 512 Z = 50 (each slice in the tiff stack) and time is each tiff stack in the file directory. When I try some example code or code from Chat GPT (which is gleaned from the few examples online) I get a tiff array that states its shape to be x = 50, y = 512 and z = 512. The call to cellpose fails because I'm asking it to output to four arrays. Here's the source I tried modifying/correcting from chat GTP and running. (yes I know chat GPT is abysmal. I'm comparing it to code examples and trying common sense corrections to no avail. Python isn't the language I know. I was really good with Visual Basic back in the day. If you don't know cellpose and/or napari then just any help with loading the array correctly would be a real boon. Thank you.

import os
import napari
import tifffile as tf
from cellpose import models
from cellpose.models import CellposeModel

# Set the directory path
directory_path = r"C:\Optic Tectum\processed\Optic Tectucm"
models_directory = r"C:\Optic Tectum\processed\models"

# Get a list of all TIFF files in the directory
tiff_files = [f for f in os.listdir(directory_path) if f.endswith('.tif')]

# Load custom Napari model
model_filename = "OT3_20230716_231844"
custom_model_path = os.path.join(models_directory, f"{model_filename}")
custom_model = models.CellposeModel(gpu=False, pretrained_model=custom_model_path)

print(custom_model_path)

# Load and process each TIFF Z stack
for tiff_file in tiff_files:
    # Construct the full file path
    file_path = os.path.join(directory_path, tiff_file)
    
    # Load the TIFF Z stack
    tiff_stack = tf.imread(file_path)
    
    # Check the shape of the stack (X, Y, Z)
    x_size, y_size, z_size = tiff_stack.shape
    print(f"Processing {tiff_file}: X={x_size}, Y={y_size}, Z={z_size}")
    
    # Use napari to visualize the Z stack
    viewer = napari.Viewer()
    viewer.add_image(tiff_stack, name='Z Stack')
    
    # Use custom Napari model for segmentation
    masks, flows, styles, diams = custom_model.eval(tiff_stack, diameter=18, channels=[0, 0])
    
    # Add segmentation results to the napari viewer
    viewer.add_image(masks, name='Segmentation Masks', colormap='red', blending='additive')
    
    # Keep the napari viewer open until you close it
    napari.run()

# Note: Adjust the parameters in the custom Cellpose model initialization according to your needs.

I was expecting 4D napari output with the original image layer, label/masks layer, flows layer and maybe an outlines layer.