Hey! So we are done with week 1 ...
What did you do this week?
Finishing this week, I can now feed Keras models and images to ELI5 and make it show visualisations of them. I have wrapped a working Grad-CAM implementation I found on GitHub, and made changes to it such as ability to choose a layer and prediction to do Grad-CAM on. Grad-CAM produces a “heatmap”, so I have added an “image formatter” that takes that heatmap and overlays it over the original image. During the week I caught up with my mentors, going through the Grad-CAM paper, and called with some Scrapy students to get to know each other.
What is coming up next?
Week 2 will be a split between two activities. First, I will do testing. It will be essential to add some automated tests using PyTest and tox. Some manual tests using different datasets and models would also be nice. Secondly, I will need to perform optimisations, refactorings, and improvements to the code added in week 1. One interesting task will be making Grad-CAM work beyond classification-based models, i.e. regression, etc. I hope that by the end of week 2 or 3 my branch will be in a good shape for a Pull Request.
Did you get stuck anywhere?
I had troubles with implementing/wrapping Grad-CAM itself (more on that in the upcoming weekly blog, but testing what works THEN changing things, and mentors’ advice, had certainly helped). A slight blocker was also low responsiveness of my machine when testing with large models in memory. Fortunately smaller models exist so I don’t always have to use VGG16!
1 down and 11 more to go! Thanks for reading!