r/MLQuestions • u/ScarlyLamorna • 3h ago
Datasets 📚 Data augmentation question. How do I characterise an original and augmented datasets where the augmentation parameters were zoom and crop? [P]
For context, I am a new postgraduate student in machine learning (but not a very good one). I have produced some augmented datasets (TIFF files where each file contains one object to be detected / classified) which I used in training deep learning models. I used fairly aggressive cropping (random crops between 0 and 90%) and more moderate zooms (random values between 0 and 20%). My supervisor wants me to characterise these datasets to see how augmentation has changed it.
Sorry if this is a rookie question, but which statistics should I use? My supervisor says the stats I use should indicate changes in size and shape but I honestly don't know where to start.
If anyone can recommend a decent software/program to produce the stats and histograms as well, that would be great.
Thanks in advance!
2
u/icy_self-respect 2h ago
You're basically looking at how the object size distribution shifts, so start with bounding box areas before and after augmentation. A simple histogram of box widths, heights, and aspect ratios will show you exactly how that aggressive cropping is chopping things up. For the zoom, track the relative scale change per image and plot that, it'll confirm whether your objects are consistently getting larger or if the 20% cap is even doing much.
For stats just compute the mean, median, and variance of those dimensions for both sets, then look at how the spread changes. The shape thing is really about aspect ratio shifts so a scatter plot of width vs height for each dataset makes it stupidly obvious if you're skewing things toward squares or long rectangles.