hrgentry/edge_eval_python

Edge Eval Python

A python implementation of edge eval.

The logic of the code is almost the same as that of the origin MATLAB implementation (see References).

Requirements

Python3
Numpy
Scipy >= 1.6.0
g++
Matplotlib

Install

1. clone repository

git clone https://github.com/Walstruzz/edge_eval_python.git
cd edge_eval_python

2. compile cxx library

Most of the code in this folder is copied from davidstutz/extended-berkeley-segmentation-benchmark.

Actually, there is a more efficient function in Scipy that can solve the CSA problem without compiling the following cxx codes...

cd cxx/src
source build.sh

Usage

1. save your results

from scipy.io import savemat

key = "result"
result = your_method(image)
savemat(save_name, {key: image})

2.eval

python main.py --alg "HED" --model_name_list "hed" --result_dir examples/hed_result \
--save_dir examples/hed_eval_result --gt_dir examples/bsds500_gt --key result \
--file_format .mat --workers -1

Result(BSDS 500)

ODS	OIS	AP	R50
0.789	0.806	0.810	0.897

Note

Because of the difference in calculation precision and the sensitivity of NMS threshold, the edge images may be slightly different.
match_edge_maps samples points randomly (so as Matlab).
Python and Matlab index files in different order, resulting in different order of eval_bdry_img.txt.
Python version is slower than Matlab version. Should I implement more functions in cxx/lib/solve_cas.so?

hrgentry / edge_eval_python