Image Cropping Tool Written in Python3

During many of my previous computer graphics and visualization projects, I needed to create screenshots of rendering results to include as figures in a thesis, report or paper. However, the screenshots my visualization programs output are usually exactly the size of the viewport. So every time when I wanted to include some visualization result, I needed to first make sure that the data set fills a large portion of the screen and then manually crop the image to remove unwanted borders.

Repeating this process over and over is really bothersome, so I took the time to write a small tool that does this work for me in an automated fashion. A link to the program can be found here:

Figure 1: A ring line data set by Candelaresi and Brandenburg [2011]1 rendered using The magnetic field strength is mapped to color.

Figure 2: A carved cube hex-mesh data set by Livesu et al. [2020]2 rendered using The scaled Jacobian (a measure for cell deformation) is mapped to color and opacity.

The program is relatively simple, as it can only detect single-color backgrounds. It can also cope with RGBA images. Optionally, the user can specify a border size in pixels that should be kept when cropping.

  1. Simon Candelaresi and Axel Brandenburg. 2011. Decay of helical and nonhelical magnetic knots. Physical Review E 84, 1 (Jul 2011). ↩︎

  2. Marco Livesu, Nico Pietroni, Enrico Puppo, Alla Sheffer, and Paolo Cignoni. 2020. LoopyCuts: Practical Feature-Preserving Block Decomposition for Strongly Hex-Dominant Meshing. ACM Transactions on Graphics 39, 4 (2020). ↩︎