Detection Proposals

Evaluation of detection proposal algorithms. The code belongs to the BMVC paper How good are detection proposals, really? and an upcoming journal paper. Have a look at the Project Page for more information.

Please contact me if you're having trouble with the code!

Plot evaluation curves

1. Get the data that you want to use from the Project Page.
2. Edit get_config.m to point to the right locations for images, candidates and so on.
3. Make sure you either start matlab in the root directory of the code or run startup.m manually once.
4. Run plot_recall_voc07.m, curves will be in the figures subdirectory.

Benchmark your own method

1. Follow Plot evaluation curves.
2. Write a wrapper function that takes an image and the number of proposal boxes and returns the proposals and scores. Proposals are a nx4 matrix, where n is the number of proposals and every row has the format [x1 x2 y1 y2] (x and y are 1-based image coordinates). See method_wrappers/ for examples.
3. Add your method to shared/get_method_configs.m
4. Run compute_recall_candidates_voc07.m passing only the config of your method as an argument. If your method is slow, you probably want to parallelize it in a cluster.
5. Run plot_recall_voc07.m, curves will be in the figures subdirectory.

You don't have to use compute_recall_candidates_voc07.m, but you can have a look to get an idea about how to save the candidates in the right format so, plot_recall_voc07.m will be able to read it.