# Netatmo technical test The subject is available here: [Test Algo](./test_algo.pdf) ## TODO - [ ] document - [X] dumb packing - [ ] skyline - [X] add raygui - [X] resize box - [X] delete box in gui by clicking - [ ] wrap stb_rect_pack? - [X] change bbox api to origin + size - [X] dummy A2 - [X] package ## Installation ## Notes ### Question 1 > As a preprocessing step of a second algorithm A2, we would like to combine all > the regions corresponding to the bounding boxes into a new image FRegions of > dimension D × D, where D given by A2 and D < min(M, N ) This is a packing problem, as described on [Wikipedia][1]. Since this is NP-hard, we know the "exact" solution might be unreachable but we could find a solution that is good enough for our needs. I looked up some solutions online and found a great article by David Colson: "[Exploring rectangle packing algorithms][2]". It gives a lot a references and compares different algorithms. I decided at first to implement his naive "row packer" to quickly have an implementation and try it out. ### Question 2 > A2 then takes as input F Regions and outputs new bounding boxes B′. We would > like now to compute the location of each of these new bounding boxes in F > reference To map the new bounding boxes into the original frame F, we need to have a mapping between the bounding boxes of F and the ones we packed into FRegions. During the packing, I saved the bounding boxes position in FRegions, so the mapping was straightforward: 1. detect in which bounding box in FRegions the new bounding box is contained 2. apply the transformation from FRegions to F Because we look into every bounding box to find the enclosing one, we have a complexity of N^2. Depending of the numbers of boxes, it could be problematic. We can make it faster by using a spatially sorted structure like a quad-tree, but it seems a bit overkill in this case. If we didn't have knowledge of the bounding boxes position in FRegions, we could recompute them by looking at pixel similarity between F and FRegions but it would be costly, and a bit wasteful since we already computed the bounding boxes. ### Question 3 > We would like now to be able to provide to the algorithm A2 either the > region-based image or the initial image without transformation, which > modifications to your code architecture do you suggest in order to handle > this? To support either a packed image (the region-based one) or a sparse image (the initial image limited to the bounding boxes), the easiest solution is to add support for a binary mask. In the same way A2 is suppose to ignore zeros valud in the region-based frame, it could be modified to ignore areas in an image where the mask is set to zero. ## GUI In order to easily debug and better visualize the problem, I chose to implement a minimal GUI using [raylib][3]. You can build it with `./build-gui.sh` (you need to installed [raylib required libraries](https://github.com/raysan5/raylib/wiki/Working-on-GNU-Linux)). You can add, move, and resize boxes. Processing steps are triggered with buttons. ## CLI A commandline sample is also available, in case the raylib library cannot be built, or if we need to benchmark performance. You can build it with `./build-cli.sh` (you need to installed [raylib required libraries](https://github.com/raysan5/raylib/wiki/Working-on-GNU-Linux)). ## PNG support I chose to support PNG files through the stb files: [github.com/nothings/stb](https://github.com/nothings/stb). I could have implemented basic image support with the PNM format but I think it is nicer to support common image formats with a simple library. ## 3rd party libraries I use 2 external libraries for better visualization: - stb files (for PNG) - raylib (for GUI) I don't rely on them for the algorithm implementation and the core of the exercise doesn't rely on external libraries. To avoid name collision, I created my own namespace `freling`. ## References [1]: https://en.wikipedia.org/wiki/Packing_problems#Packing_of_rectangles [2]: https://www.david-colson.com/2020/03/10/exploring-rect-packing.html [3]: https://github.com/raysan5/raylib