np::ndarray cleanVOC( const np::ndarray& lbl ) {
unsigned char * plbl = (unsigned char *)lbl.get_data();
np::ndarray r = np::zeros( lbl.get_nd(), lbl.get_shape(), np::dtype::get_builtin<short>() );
short * pr = (short *)r.get_data();
for( int i=0; i<lbl.shape(0)*lbl.shape(1); i++ )
pr[i] = (plbl[i]>250)?-2:(short)plbl[i]-1;
return r;
}
/**************** other ****************/
static np::ndarray extractPatch( const np::ndarray &a, const RMatrixXi & l, const VectorXi & s ) {
// Check the input
if( !(a.get_flags() & np::ndarray::C_CONTIGUOUS) )
throw std::invalid_argument( "Contiguous array required!" );
if( l.cols() != a.get_nd() )
throw std::invalid_argument("location dimension does not match matrix");
if( l.cols() != s.size() )
throw std::invalid_argument("patch size and locations have different dimension");
for( int i=0; i<l.rows(); i++ )
for( int j=0; j<s.size(); j++ )
if( l(i,j)<0 || l(i,j)+s[j] > a.shape(j) )
throw std::invalid_argument("location out of range! Dimension "+std::to_string(j)+" : "+std::to_string(l(i,j))+" + "+std::to_string(s[j])+" ( 0 .. "+std::to_string(a.shape(j))+" )");
const int itemsize = a.get_dtype().get_itemsize();
// Create the output array
std::vector<Py_intptr_t> out_size;
out_size.push_back( l.rows() );
for( int i=0; i<s.size(); i++ )
if( s[i]>1 )
out_size.push_back( s[i] );
np::ndarray res = np::empty( out_size.size(), out_size.data(), a.get_dtype() );
// Prepare the patches
const int ls = s[s.size()-1]; // Radius of the last dimension
std::vector<int> patch_offsets(1,0);
for( int d=0; d<s.size()-1; d++ ) {
std::vector<int> opo = patch_offsets;
patch_offsets.clear();
for( int i=0; i<s[d]; i++ )
for( int o: opo )
patch_offsets.push_back( a.shape(d+1)*(o+i) );
}
const char * pa = a.get_data();
char * pres = res.get_data();
for( int i=0,k=0; i<l.rows(); i++ ) {
int o=0;
for( int d=0; d<s.size(); d++ )
o = a.shape(d)*o + l(i,d);
// Extract the patches
for( int po: patch_offsets ) {
memcpy( pres+k*itemsize, pa+(po+o)*itemsize, ls*itemsize );
k += ls;
}
}
return res;
}
np::ndarray boundaryDistance( const np::ndarray & sg ) {
checkArray( sg, short, 2, 2, true );
const int W = sg.shape(1), H = sg.shape(0);
np::ndarray r = np::zeros( make_tuple(H,W), np::dtype::get_builtin<float>() );
const short * psg = (const short*)sg.get_data();
float * pr = (float*) r.get_data();
std::fill( pr, pr+W*H, 1e10 );
for( int it=0; it<10; it++ ) {
for( int j=0,k=0; j<H; j++ )
for( int i=0; i<W; i++,k++ ) {
if( i ) {
if( psg[k] != psg[k-1] )
pr[k] = 0;
else
pr[k] = std::min( pr[k], pr[k-1]+1 );
}
if( j ) {
if( psg[k] != psg[k-W] )
pr[k] = 0;
else
pr[k] = std::min( pr[k], pr[k-W]+1 );
}
}
for( int j=H-1,k=W*H-1; j>=0; j-- )
for( int i=W-1; i>=0; i--,k-- ) {
if( i ) {
if( psg[k] != psg[k-1] )
pr[k-1] = 0;
else
pr[k-1] = std::min( pr[k]+1, pr[k-1] );
}
if( j ) {
if( psg[k] != psg[k-W] )
pr[k-W] = 0;
else
pr[k-W] = std::min( pr[k]+1, pr[k-W] );
}
}
}
return r;
}