region growing_regionPCNN_基于pcnn区域生长图像分割算法_pcnn_区域生长_图像分割_

# BSD500-Segmentation-Evaluator This repo is used to evaluate the results of segmentation with BSD500 dataset, including Probabilistic Rand Index (PRI), Variation of Information (VI) and Segmentation Covering (SC). This repo provide the python code for calculating the PRI, VI and SC between a single prediction and groundTruth. The python code is completed with reference to the matlab code which are provided by the BSD500 benchmark. reference: [https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html](https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html) ## Dependencies ``` # Build a conda enviroment conda create -n bsd-evaluation python=3.7 source activate bsd-evaluation conda install numpy pip install scipy tqdm scikit-image matplotlib ``` ## Testing data      ## Testing Example ``` cd python python test_bench.py ``` ## Results: - mean SC is: 0.6355703654947689 - mean PRI is: 0.828961683464492 - mean VI is: 1.507315850885107