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johko / computer-vision-course

This repo is the homebase of a community driven course on Computer Vision with Neural Networks. Feel free to join us on the Hugging Face discord: hf.co/join/discord
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DRAFT - mdx for Synthetic Data Creation lung images #105

Closed kfahn22 closed 6 months ago

kfahn22 commented 7 months ago

This is a first draft for the section on generating lung images with DCGAN. Note that I am not thrilled with the quality of the lung images. I have started looking into Medfusion (which uses to diffusors) to see if the images can be improved, although not sure about the time-frame to implement.

lung_images

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merveenoyan commented on 2023-12-09T05:04:06Z ----------------------------------------------------------------

Again, having dataset hosted at hugging face gives you a lot of convenience with one line:

python

from datasets import load_dataset

ds = load_dataset(DATASET_ID)


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merveenoyan commented on 2023-12-09T05:04:07Z ----------------------------------------------------------------

I think seeing one or two should be enough :')


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merveenoyan commented on 2023-12-09T05:04:08Z ----------------------------------------------------------------

I think it would be nicer if we could visualize every x epochs


kfahn22 commented on 2023-12-16T00:19:13Z ----------------------------------------------------------------

done

merveenoyan commented 7 months ago

I think using kaggle adds quite a lot of complexity. Overall the notebook is pretty informative. I'd like to have @MKhalusova add her views too!

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MKhalusova commented on 2023-12-11T14:17:45Z ----------------------------------------------------------------

reproducible


_kfahn22 commented on 2023-12-16T00:19:26Z_ ----------------------------------------------------------------

thanks fixed

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johko commented on 2023-12-12T22:07:31Z ----------------------------------------------------------------

Do you know and can you add the hardware requirements people need to run the whole notebook including the training? Or at least if it is running in colab and with which GPU if you know that.


kfahn22 commented on 2023-12-16T00:44:23Z ----------------------------------------------------------------

Sorry, I am not exactly sure what you are saying. This notebook ran in High-Ram (although it took several hours)- is that what you are referring to?

MKhalusova commented on 2023-12-18T13:39:08Z ----------------------------------------------------------------

I agree with Johannes - it would be useful to add a note specifying what setup a learner might need to run this notebook (e.g. Google Colab with High RAM A100).

This is especially important when the free version of Colab is not enough to run the notebook (I think it's only T4, and no high-RAM).

This is something that would be great to add to all the notebooks (but especially the ones that won't run on the free tier)

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johko commented on 2023-12-12T22:07:32Z ----------------------------------------------------------------

We will use we make use a utility function to plot the loaded images.


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johko commented on 2023-12-12T22:07:33Z ----------------------------------------------------------------

-> And now let's look at lung images that have been labeled as pneumonia.


kfahn22 commented on 2023-12-16T00:30:58Z ----------------------------------------------------------------

I have to admit I really struggled trying to show the images after they were downloaded from the Hub. I am guessing there must be an easy way to do it, but I haven't figured it out. I can filter them to a folder, but that cell was taking A REALLY LONG TIME and I decided it wasn't worth it. I have settled on just showing one image. If you can tell me how to edit I will update.

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johko commented on 2023-12-12T22:07:34Z ----------------------------------------------------------------

First, we us define some parameters.


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johko commented on 2023-12-12T22:07:35Z ----------------------------------------------------------------

The model weights sare randomly....


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merveenoyan commented on 2023-12-15T07:17:27Z ----------------------------------------------------------------

There's few typos here


kfahn22 commented on 2023-12-16T00:23:07Z ----------------------------------------------------------------

Have see the misspelling on preprocess. Are there others?

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merveenoyan commented on 2023-12-15T07:17:27Z ----------------------------------------------------------------

You can add the citation at the bottom not to break the flow


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merveenoyan commented on 2023-12-15T07:17:28Z ----------------------------------------------------------------

Would be better to have more intuitive naming for variables for better readability, e.g. generative_network or gen_net would be better


kfahn22 commented on 2023-12-18T19:32:11Z ----------------------------------------------------------------

Done

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merveenoyan commented on 2023-12-15T07:17:29Z ----------------------------------------------------------------

Line #14.            ############################

You don't need to leave these


_kfahn22 commented on 2023-12-18T19:32:44Z_ ----------------------------------------------------------------

Done

kfahn22 commented 6 months ago

done

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kfahn22 commented 6 months ago

thanks fixed

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kfahn22 commented 6 months ago

Have see the misspelling on preprocess. Are there others?

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kfahn22 commented 6 months ago

I have to admit I really struggled trying to show the images after they were downloaded from the Hub. I am guessing there must be an easy way to do it, but I haven't figured it out. I can filter them to a folder, but that cell was taking A REALLY LONG TIME and I decided it wasn't worth it. I have settled on just showing one image. If you can tell me how to edit I will update.

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kfahn22 commented 6 months ago

I am sorry, I am not sure what this is referring to. Please let me know if I still need to fix.

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kfahn22 commented 6 months ago

Sorry, I am not exactly sure what you are saying. This notebook ran in High-Ram (although it took several hours)- is that what you are referring to?

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kfahn22 commented 6 months ago

I have substantially edit the notebook. I tried to address the comments, but I might have missed some things. Please let me know what I still need to update. Note that the results seem to be highly dependent on the seed value, which I am still finding hard to believe. At any rate, I changed the seed value to 22 (as much as a Hitchhiker's nerd as I am, 42 led to a poor outcome). Also, I am wondering if the model is suffering from mode collapse since at least to me the verified images look similar. I edited the mdx file to discuss this.

kfahn22 commented 6 months ago

I have also added links to the training GIF and image showing the verified synthetic Xray images.

MKhalusova commented 6 months ago

I agree with Johannes - it would be useful to add a note specifying what setup a learner might need to run this notebook (e.g. Google Colab with High RAM A100).

This is especially important when the free version of Colab is not enough to run the notebook (I think it's only T4, and no high-RAM).

This is something that would be great to add to all the notebooks (but especially the ones that won't run on the free tier)

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MKhalusova commented on 2023-12-18T15:11:19Z ----------------------------------------------------------------

It would be nice to add a sentence or two about the transformations that you do when preprocessing the dataset.


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MKhalusova commented on 2023-12-18T15:11:20Z ----------------------------------------------------------------

Line #12.    # GPU or CPU (Not having at least 1 GPU can prevent code from working)

This is something that should be mentioned in the introduction


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MKhalusova commented on 2023-12-18T15:11:21Z ----------------------------------------------------------------

Why not take a look at an image before making transformations?


kfahn22 commented on 2023-12-18T17:43:33Z ----------------------------------------------------------------

I have changed the code to display 4 normal images and 4 pneumonia images, but they are all big.

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MKhalusova commented on 2023-12-18T15:11:22Z ----------------------------------------------------------------

Line #2.    device = torch.device("cuda:0" if (torch.cuda.is_available() and nb_gpu > 0) else "cpu")

This might be redundant, you define the device earlier.


_kfahn22 commented on 2023-12-18T17:43:52Z_ ----------------------------------------------------------------

Fixed

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MKhalusova commented on 2023-12-18T15:11:22Z ----------------------------------------------------------------

It's great that you have comments in the code, but it would also be helpful to have a quick description of what happens in the loop here, before the code.


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MKhalusova commented on 2023-12-18T15:11:23Z ----------------------------------------------------------------

Add a couple of sentences about what we see here - whether this is what we expect to see or not, what conclusions can we make etc.

This is another opportunity to guide a learner to understand better what's going on. Share your knowledge :)


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MKhalusova commented on 2023-12-18T15:11:24Z ----------------------------------------------------------------

Earlier in the notebook, you log in to Hugging Face Hub. It would make sense to push the model to Hub, and then, for inference, get it here from Hub.


kfahn22 commented on 2023-12-18T18:02:28Z ----------------------------------------------------------------

I thought about pushing the model to the Hub, but I wondered whether the model was good enough. I am exploring MedFusion, which first trains a VAE or VAEGAN and then trains further with a Diffusor.

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MKhalusova commented on 2023-12-18T15:11:25Z ----------------------------------------------------------------

Again, a couple of words would be great about why we need the post-processing, what kind of post-processing is needed, etc..


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MKhalusova commented on 2023-12-18T15:11:26Z ----------------------------------------------------------------

I'm not sure I understand what "verified" means in this context.


kfahn22 commented on 2023-12-18T20:09:59Z ----------------------------------------------------------------

I have changed the naming and added an explanation.

kfahn22 commented 6 months ago

I have changed the code to display 4 normal images and 4 pneumonia images, but they are all big.

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kfahn22 commented 6 months ago

Fixed

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kfahn22 commented 6 months ago

I thought about pushing the model to the Hub, but I wondered whether the model was good enough. I am exploring MedFusion, which first trains a VAE or VAEGAN and then trains further with a Diffusor.

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kfahn22 commented 6 months ago

Done

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kfahn22 commented 6 months ago

Done

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kfahn22 commented 6 months ago

I have changed the naming and added an explanation.

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kfahn22 commented 6 months ago

Sorry this took me a while. I realized that in changing the code to download the dataset from the hub, I introduced a bug.

I think I have addressed all of the comments on the notebook. I have added a discussion on preprocessing, training, the plot, and "good" images. I also added a link to the notebook.

Please let me know if there is anything else--thank you!

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