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Implementation of bit-exact resize. Internal calls to linear resize updated to use bit-exact version. (#9468)

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This commit is contained in:
Vitaly Tuzov
2017-12-13 15:00:38 +03:00
committed by Vadim Pisarevsky
parent 84ee4d701a
commit 51cb56ef2c
57 changed files with 1300 additions and 112 deletions
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samples/cpp/3calibration.cpp
+1 -1
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@@ -347,7 +347,7 @@ int main( int argc, char** argv )
remap(view, rview, map1[k1], map2[k1], INTER_LINEAR);
}
printf("%s %s %s\n", imageList[i*3].c_str(), imageList[i*3+1].c_str(), imageList[i*3+2].c_str());
resize( canvas, small_canvas, Size(1500, 1500/3) );
resize( canvas, small_canvas, Size(1500, 1500/3), 0, 0, INTER_LINEAR_EXACT );
for( k = 0; k < small_canvas.rows; k += 16 )
line(small_canvas, Point(0, k), Point(small_canvas.cols, k), Scalar(0,255,0), 1);
imshow("rectified", small_canvas);
samples/cpp/bgfg_segm.cpp
+1 -1
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@@ -70,7 +70,7 @@ int main(int argc, const char** argv)
if( img0.empty() )
break;
resize(img0, img, Size(640, 640*img0.rows/img0.cols), INTER_LINEAR);
resize(img0, img, Size(640, 640*img0.rows/img0.cols), 0, 0, INTER_LINEAR_EXACT);
if( fgimg.empty() )
fgimg.create(img.size(), img.type());
samples/cpp/facedetect.cpp
+1 -1
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@@ -174,7 +174,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
cvtColor( img, gray, COLOR_BGR2GRAY );
double fx = 1 / scale;
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR_EXACT );
equalizeHist( smallImg, smallImg );
t = (double)getTickCount();
samples/cpp/image_alignment.cpp
+1 -1
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@@ -232,7 +232,7 @@ int main (const int argc, const char * argv[])
}
else{ //apply random warp to input image
resize(inputImage, target_image, Size(216, 216));
resize(inputImage, target_image, Size(216, 216), 0, 0, INTER_LINEAR_EXACT);
Mat warpGround;
RNG rng(getTickCount());
double angle;
samples/cpp/shape_example.cpp
+3 -3
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@@ -80,7 +80,7 @@ int main(int argc, char** argv)
queryName<<path<<indexQuery<<".png";
Mat query=imread(queryName.str(), IMREAD_GRAYSCALE);
Mat queryToShow;
resize(query, queryToShow, sz2Sh);
resize(query, queryToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
imshow("QUERY", queryToShow);
moveWindow("TEST", 0,0);
vector<Point> contQuery = simpleContour(query);
@@ -95,7 +95,7 @@ int main(int argc, char** argv)
cout<<"name: "<<iiname.str()<<endl;
Mat iiIm=imread(iiname.str(), 0);
Mat iiToShow;
resize(iiIm, iiToShow, sz2Sh);
resize(iiIm, iiToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
imshow("TEST", iiToShow);
moveWindow("TEST", sz2Sh.width+50,0);
vector<Point> contii = simpleContour(iiIm);
@@ -112,7 +112,7 @@ int main(int argc, char** argv)
bestname<<path<<bestMatch<<".png";
Mat iiIm=imread(bestname.str(), 0);
Mat bestToShow;
resize(iiIm, bestToShow, sz2Sh);
resize(iiIm, bestToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
imshow("BEST MATCH", bestToShow);
moveWindow("BEST MATCH", sz2Sh.width+50,0);
waitKey();
samples/cpp/smiledetect.cpp
+1 -1
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@@ -135,7 +135,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
cvtColor( img, gray, COLOR_BGR2GRAY );
double fx = 1 / scale;
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR_EXACT );
equalizeHist( smallImg, smallImg );
cascade.detectMultiScale( smallImg, faces,
samples/cpp/stereo_calib.cpp
+2 -2
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@@ -100,7 +100,7 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, b
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
resize(img, timg, Size(), scale, scale, INTER_LINEAR_EXACT);
found = findChessboardCorners(timg, boardSize, corners,
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);
if( found )
@@ -120,7 +120,7 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, b
cvtColor(img, cimg, COLOR_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640./MAX(img.rows, img.cols);
resize(cimg, cimg1, Size(), sf, sf);
resize(cimg, cimg1, Size(), sf, sf, INTER_LINEAR_EXACT);
imshow("corners", cimg1);
char c = (char)waitKey(500);
if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
samples/cpp/stitching_detailed.cpp
+4 -4
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@@ -465,7 +465,7 @@ int main(int argc, char* argv[])
work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area()));
is_work_scale_set = true;
}
resize(full_img, img, Size(), work_scale, work_scale);
resize(full_img, img, Size(), work_scale, work_scale, INTER_LINEAR_EXACT);
}
if (!is_seam_scale_set)
{
@@ -478,7 +478,7 @@ int main(int argc, char* argv[])
features[i].img_idx = i;
LOGLN("Features in image #" << i+1 << ": " << features[i].keypoints.size());
resize(full_img, img, Size(), seam_scale, seam_scale);
resize(full_img, img, Size(), seam_scale, seam_scale, INTER_LINEAR_EXACT);
images[i] = img.clone();
}
@@ -805,7 +805,7 @@ int main(int argc, char* argv[])
}
}
if (abs(compose_scale - 1) > 1e-1)
resize(full_img, img, Size(), compose_scale, compose_scale);
resize(full_img, img, Size(), compose_scale, compose_scale, INTER_LINEAR_EXACT);
else
img = full_img;
full_img.release();
@@ -831,7 +831,7 @@ int main(int argc, char* argv[])
mask.release();
dilate(masks_warped[img_idx], dilated_mask, Mat());
resize(dilated_mask, seam_mask, mask_warped.size());
resize(dilated_mask, seam_mask, mask_warped.size(), 0, 0, INTER_LINEAR_EXACT);
mask_warped = seam_mask & mask_warped;
if (!blender && !timelapse)
samples/cpp/train_HOG.cpp
+1 -1
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@@ -344,7 +344,7 @@ int main( int argc, char** argv )
for ( size_t j = 0; j < detections.size(); j++ )
{
Mat detection = full_neg_lst[i]( detections[j] ).clone();
resize( detection, detection, pos_image_size );
resize( detection, detection, pos_image_size, 0, 0, INTER_LINEAR_EXACT);
neg_lst.push_back( detection );
}