The program I'm trying to write takes in a multipage Tif file/stack and processes it by:

1. Changing tiffile to numpy arrays
2. Taking numpy arrays and turns them into tensors
3. Processes tensors and turns them back to numpy arrays
4. Finally takes said numpy arrays and turns it back into a tiff stack.

My Code:
models.py :

from django.db import models
import numpy as np
import tensorflow as tf
from PIL import Image
from django.core.files.base import ContentFile


from django.core.files.uploadedfile import InMemoryUploadedFile


# Create your models here.
class TiffModel(models.Model):
    name = models.CharField(max_length=450)
    image = models.ImageField(blank = True, null = True)

    def __str__(self):
        return self.name

    def img (self):
        return self.image

    def save(self, *args, **kwargs):
        super().save(*args, **kwargs)
        img = Image.open(self.image.path)
        images = []
        tensors = []
        processedArrays = []

        tiffStack = []
        
        # Read tif, convert each page into arrays in images[]
        for i in range(img.n_frames):
            img.seek(i)
            images.append(np.array(img))

        # Read every numpy array, convert to tensorflow, process by dividing by 2
        for x in images:
            tensorX = tf.convert_to_tensor(x)
            processedTensor = tf.math.divide(tensorX,2)
            tensors.append(processedTensor)

        # Convert back to numpy array
        for x in tensors:
            processedArrays.append(x.numpy())

        # Convert to tif
        for x in processedArrays:
            tiffStack.append(Image.fromarray(x))

        img = tiffStack[0].save(self.name + ".tiff", compression="tiff_deflate", save_all=True,
               append_images=tiffStack[1:])

        img.save(self)

The issue I'm running into is that it seems that the tiffile is not saving correctly into my original ImageField. How can I fix this?