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currently making human action recognition to detect a cheating kind on the exam from CCTV using AlexNet+LSTM

My Data are raw images in each class folder with like this

But I got error like this:

ValueError: in user code:

/usr/local/lib/python3.7/dist-packages/keras/engine/training.py:830 train_function  *
    return step_function(self, iterator)
/usr/local/lib/python3.7/dist-packages/keras/engine/training.py:813 run_step  *
    outputs = model.train_step(data)
/usr/local/lib/python3.7/dist-packages/keras/engine/training.py:770 train_step  *
    y_pred = self(x, training=True)
/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py:989 __call__  *
    input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
/usr/local/lib/python3.7/dist-packages/keras/engine/input_spec.py:212 assert_input_compatibility  *
    raise ValueError('Input ' + str(input_index) + ' of layer ' +

ValueError: Input 0 of layer sequential_10 is incompatible with the layer: expected ndim=5, found ndim=4. Full shape received: (None, None, None, None)

The error comes when I do the model.fit.

From what I read it said that the problem at the input_shape but I am still doesn't found the solution to my problem the link of my code at collab can be found here,

I still don't understand what is the problem, I check the documentation for input_shape in TimeDistributed and it's the same for (timeSteps, height, width, channels)

I did try to remaking the model but the problem is still the same

is it from my ImageDataGenerator?

I would appreciate if anybody has the experience in this matter and tries to help my problem

Thank you so much!

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1 Answer 1

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The TimeDistributed documentation says the input should have shape (batch, time, others . . .). In your case (a batch of images in a time series), the shape should be (batch, time, r, g, b).

But the image data generator in your code is reading images from a directory in a batch, outputting tensors with shape (batch, r, g, b). So you are missing the time dimension.

If you want to use TimeDistributed layers, then you'll need to assemble your images as a time-series, then apply batching.

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  • $\begingroup$ hello thank you for your comment and sorry for the late reply, do you know where can i found how to assembles my images as time-series that you mentioned? bit lost here Thank you so much $\endgroup$
    – JuniorPython
    Commented Jul 1, 2021 at 3:25
  • $\begingroup$ Do your images have some sort of temporal order to them? For example, are they short video clips or something? $\endgroup$
    – zachdj
    Commented Jul 1, 2021 at 13:58
  • $\begingroup$ If your images are time-ordered, you will probably need to write your own data loader. It would read all the images in a given time series and place them into a single tensor. If your images are not time-ordered, then you can just stop using the TimeDistributed layers :) $\endgroup$
    – zachdj
    Commented Jul 1, 2021 at 13:59
  • $\begingroup$ yes at first it's a short clips video, i make it into frame so i can sort it into each class folder $\endgroup$
    – JuniorPython
    Commented Jul 1, 2021 at 15:54
  • $\begingroup$ so it's better to just use the short clip video as input instead of the raw images then? $\endgroup$
    – JuniorPython
    Commented Jul 1, 2021 at 15:55

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