correspondPixels function need :bmap1 and bmap2 must be the same size

why someone not have error

function [thrs,cntR,sumR,cntP,sumP,V] = edgesEvalImg( E, G, varargin )

% Calculate edge precision/recall results for single edge image.

%

% Enhanced replacement for evaluation_bdry_image() from BSDS500 code:

% http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/

% Uses same format and is fully compatible with evaluation_bdry_image.

% Given default prms results are *identical* to evaluation_bdry_image.

%

% In addition to performing the evaluation, this function can optionally

% create a visualization of the matches and errors for a given edge result.

% The visualization of edge matches V has the following color coding:

% green=true positive, blue=false positive, red=false negative

% If multiple ground truth labels are given the false negatives have

% varying strength (and true positives can match *any* ground truth).

%

% This function calls the mex file correspondPixels. Pre-compiled binaries

% for some systems are provided in /private, source for correspondPixels is

% available as part of the BSDS500 dataset (see link above). Note:

% correspondPixels is computationally expensive and very slow in practice.

%

% USAGE

% [thrs,cntR,sumR,cntP,sumP,V] = edgesEvalImg( E, G, [prms] )

%

% INPUTS

% E - [h x w] edge probability map (may be a filename)

% G - file containing a cell of ground truth boundaries

% prms - parameters (struct or name/value pairs)

% .out - [''] optional output file for writing results

% .thrs - [99] number or vector of thresholds for evaluation

% .maxDist - [.0075] maximum tolerance for edge match

% .thin - [1] if true thin boundary maps

%

% OUTPUTS

% thrs - [Kx1] vector of threshold values

% cntR,sumR - [Kx1] ratios give recall per threshold

% cntP,sumP - [Kx1] ratios give precision per threshold

% V - [hxwx3xK] visualization of edge matches

%

% EXAMPLE

%

% See also edgesEvalDir

%

% Structured Edge Detection Toolbox Version 3.01

% Code written by Piotr Dollar, 2014.

% Licensed under the MSR-LA Full Rights License [see license.txt]

% get additional parameters

dfs={ 'out','', 'thrs',99, 'maxDist',.0075, 'thin',1 };

[out,thrs,maxDist,thin] = getPrmDflt(varargin,dfs,1);

if(any(mod(thrs,1)>0)), K=length(thrs); thrs=thrs(:); else

K=thrs; thrs=linspace(1/(K+1),1-1/(K+1),K)'; end

% load edges (E) and ground truth (G)

if(all(ischar(E))), E=double(imread(E))/255; end

G=load(G); G=G.groundTruth; n=length(G);

for g=1:n, G{g}=double(G{g}.Boundaries); end

% evaluate edge result at each threshold

Z=zeros(K,1); cntR=Z; sumR=Z; cntP=Z; sumP=Z;

if(nargout>=6), V=zeros([size(E) 3 K]); end

for k = 1:K

% threshhold and thin E

% E1 = double(E>=max(eps,thrs(k)));

% fprintf('E=%s\n', class(E));

E1 = double(str2double(E)>=max(eps,thrs(k)));

if(thin), E1=double(bwmorph(E1,'thin',inf)); end

% compare to each ground truth in turn and accumualte

Z=zeros(size(E)); matchE=Z; matchG=Z; allG=Z;

for g = 1:n

fprintf('eq=%d\n', eq(G{g},E1));

% fprintf('G=%f\n', G{g});

% here error!!!!

[matchE1,matchG1] = correspondPixels(E1,G{g},maxDist);

matchE = matchE | matchE1>0;

matchG = matchG + double(matchG1>0);

allG = allG + G{g};

end

% compute recall (summed over each gt image)

cntR(k) = sum(matchG(:)); sumR(k) = sum(allG(:));

% compute precision (edges can match any gt image)

cntP(k) = nnz(matchE); sumP(k) = nnz(E1);

% optinally create visualization of matches

if(nargout<6), continue; end; cs=[1 0 0; 0 .7 0; .7 .8 1]; cs=cs-1;

FP=E1-matchE; TP=matchE; FN=(allG-matchG)/n;

for g=1:3, V(:,:,g,k)=max(0,1+FN*cs(1,g)+TP*cs(2,g)+FP*cs(3,g)); end

V(:,2:end,:,k) = min(V(:,2:end,:,k),V(:,1:end-1,:,k));

V(2:end,:,:,k) = min(V(2:end,:,:,k),V(1:end-1,:,:,k));

end

% if output file specified write results to disk

if(isempty(out)), return; end; fid=fopen(out,'w'); assert(fid~=1);

fprintf(fid,'%10g %10g %10g %10g %10g\n',[thrs cntR sumR cntP sumP]');

fclose(fid);

end

[kai]

I met the same issue...