Simple code for convolution and a CNN to denoise an image with real-time display in Python / PyTorch

Code from scratch in Python and PyTorch for a convolutional neural network (CNN) to denoise an image
Basic principles covered
Real-time image display

[@jpbacano]

Nice video, Andrew! I just have one question: What would you do if you didn't have the true image? Thank you!

[@AndrewJReader]

Many thanks! You can do a self supervised approach - a very simple example being to artificially create a noisier version of the image that you have, and train the CNN to denoise that back to the version of the image that had not been made noisier. Then use that trained CNN on the original image. But there are other methods that are more sophisticated of course.

[@mohsen865]

I would like to express my sincere gratitude to you for your fantastic teaching videos that have helped me a lot in implementing projects. you have always inspired me with such easily understanable solutions to complex problems.

[@AndrewJReader]

Thank you so much for your feedback, this really means a lot!

[@manolisnikolakakis7292]

My thanks professor Reader, your videos have been a valuable source of information in my understanding of nuclear imaging.

[@AndrewJReader]

Thank you, very glad you find my videos helpful

[@manigandanshanmugam4686]

Hi sir your videos are very helpful to understand and learn and is there any books to learn python code for medical image.

[@AndrewJReader]

Many thanks for your feedback. There are surely books available on this topic, although I have not found one in particular. I will hopefully write my own book at some point....

[@usmanahmedawan1171]

Thank You Professor. It helped a lot in research and implementation.

[@AndrewJReader]

Glad to hear it was helpful! Thanks for the feedback.

[@manolisnikolakakis7385]

Once again excellent video professor Reader thank you so much

[@AndrewJReader]

Really appreciate the feedback, many thanks!

[@stevechiu4384]

👋It is a wonderful video to show the concept. How can I download your code to try it out.

[@AndrewJReader]

Thanks Steve for your encouraging feedback. I only do these teaching videos for now, with no repository (yet?) of code. The key is to explain the principles really, and encourage people to write their own code.

[@ThisIsAli1983]

Thank you Andrew for posting such informative and valuable videos. There is a lack of such content out there. Keep up this great work

[@AndrewJReader]

Thanks Ali, really appreciate your encouragement.

[@learn2444]

You help me a lot to get a good intuition for my programming solutions. Keep up you help us a lot

[@AndrewJReader]

Very good to know, many thanks for the encouragement

[@jeevagasundaram]

Can i use max-pooling as one of the layer here?

[@AndrewJReader]

Absolutely. With max pooling though you need to be careful with the size of the feature maps. In this video I use an image output that is the same size as the input. So if using max pooling or other downsampling methods, then be sure also to up sample to deliver the correctly sized output. Hope that makes sense.

[@jeevagasundaram]

@@AndrewJReader thank you professor 👍

[@zachariaschalampalakis5535]

Thank you for this nice "Behind The Scenes" video.

[@AndrewJReader]

Glad you found it helpful Zach! Hope all is going well for you.

[@princegyaidoo2817]

Thank you so much prof. but how do i convolve image with a kernel matrix using numpy only

[@AndrewJReader]

Thanks for your comment. You can use numpy arrays with SciPy: docs.scipy.org/doc/scipy/reference/generated/scipy.signal.convolve2d.html

[@ajithbm3753]

I'm doing project which is similar to this, is there a way to get Kt from you ?

[@AndrewJReader]

Thanks for the comment - not sure that I can offer dedicated input to a project, but I'm usually able to reply to specific questions here in the comments for the video. Best wishes for your project!

[@bourdayrachid3855]

You are the best teacher

[@AndrewJReader]

Very kind, thanks for the feedback!

[@Rauly_Caribe]

Thank you Andrew! That is a very helpful video!

[@AndrewJReader]

Thanks for the feedback Paulo, good to know this is helpful!

[@vicktorlambokdesrony5530]

Can i run in notebook ?

[@AndrewJReader]

You can find how this would be adaptable to a notebook, for example, by checking the last part of this video: kzbin.info/www/bejne/f5mohXdqo7h9m8U It's only the display parts that need to be adapted.

[@mohsen865]

wish you the best

[@AndrewJReader]

Thank you again Mohsen