Mask image in tensorflow

Question

Can I use keras.Layers to build custom layer to mask to whole dataset and return masked dataset. That is

class AttnMask(Layer):
    def __init__(self, img_size, attention_map):
        super().__init__()

        self.imgSize = img_size
        self.attentionMap = attention_map

    def call(self, x, *args, **kwargs):
        return tf.math.multiply(x, self.attentionMap)

And to call the function

attenMaskLayer = attention_mask.AttnMask(img_size, attention_map)
maskedDataset = attenMaskLayer(dataset)

the dataset is retrieve from the directory hierarchy via tf.keras.preprocessing.image.ImageDataGenerator() and train_datagen.flow_from_directory() method.

Now it will return error ValueError: Only input tensors may be passed as positional arguments. The following argument value should be passed as a keyword argument: <keras.src.legacy.preprocessing.image.DirectoryIterator object at 0x00000169F47DF500> (of type <class 'keras.src.legacy.preprocessing.image.DirectoryIterator'>)

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furas
– furas

2025-09-27 13:52:27 +00:00
Commented Sep 27 at 13:52 — furas
– furas, Commented Sep 27 at 13:52

hamed danesh · Accepted Answer · 2025-09-27 19:37:53Z

0

Yes you can, but the problem is you are passing a python iterator to keras.Layers which only accepts tensors (Error mansions it). what you need to do is to convert your dataset to a tensor then pass it to keras.Layers.
to do this you may use convert_to_tensor function from tensorflow. your code would be something like:

import tensorflow as tf
from tensorflow.keras.layers import Layer

class AttnMask(Layer):
    def __init__(self, attentionMap):
        super().__init__()
        self.attentionMap = tf.convert_to_tensor(attentionMap, dtype=tf.float32)

    def call(self, x):
        return x * self.attentionMap

if __name__ =="__main__":
inputLayer = tf.keras.Input(shape=(img_size, img_size, 3))
maskedDataset = AttnMask(attentionMap)(inputLayer)
model = tf.keras.Model(inputs=inputLayer, outputs=maskedDataset)

answered Sep 27 at 19:37

hamed danesh

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