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js: added fillPoly() and fillConvexPoly()

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This commit is contained in:
Thang Tran 2019-06-20 19:56:23 +02:00
parent 264679a725
commit 2a67375239
2 changed files with 85 additions and 1 deletions
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3
modules/js/src/embindgen.py
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@ -112,7 +112,8 @@ imgproc = {'': ['Canny', 'GaussianBlur', 'Laplacian', 'HoughLines', 'HoughLinesP
'goodFeaturesToTrack','grabCut','initUndistortRectifyMap', 'integral','integral2', 'isContourConvex', 'line', \ 'goodFeaturesToTrack','grabCut','initUndistortRectifyMap', 'integral','integral2', 'isContourConvex', 'line', \
'matchShapes', 'matchTemplate','medianBlur', 'minAreaRect', 'minEnclosingCircle', 'moments', 'morphologyEx', \ 'matchShapes', 'matchTemplate','medianBlur', 'minAreaRect', 'minEnclosingCircle', 'moments', 'morphologyEx', \
'pointPolygonTest', 'putText','pyrDown','pyrUp','rectangle','remap', 'resize','sepFilter2D','threshold', \ 'pointPolygonTest', 'putText','pyrDown','pyrUp','rectangle','remap', 'resize','sepFilter2D','threshold', \
'undistort','warpAffine','warpPerspective','watershed'], 'undistort','warpAffine','warpPerspective','watershed', \
'fillPoly', 'fillConvexPoly'],
'CLAHE': ['apply', 'collectGarbage', 'getClipLimit', 'getTilesGridSize', 'setClipLimit', 'setTilesGridSize']} 'CLAHE': ['apply', 'collectGarbage', 'getClipLimit', 'getTilesGridSize', 'setClipLimit', 'setTilesGridSize']}
objdetect = {'': ['groupRectangles'], objdetect = {'': ['groupRectangles'],

83
modules/js/test/test_imgproc.js
View File

@ -201,6 +201,89 @@ QUnit.test('test_imgProc', function(assert) {
expected_img.delete(); expected_img.delete();
compare_result.delete(); compare_result.delete();
} }
// fillPoly
{
let img_width = 6;
let img_height = 6;
let img = new cv.Mat.zeros(img_height, img_width, cv.CV_8UC1);
let npts = 4;
let square_point_data = new Uint8Array([
1, 1,
4, 1,
4, 4,
1, 4]);
let square_points = cv.matFromArray(npts, 1, cv.CV_32SC2, square_point_data);
let pts = new cv.MatVector();
pts.push_back (square_points);
let color = new cv.Scalar (255);
let expected_img_data = new Uint8Array([
0, 0, 0, 0, 0, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 0, 0, 0, 0, 0]);
let expected_img = cv.matFromArray(img_height, img_width, cv.CV_8UC1, expected_img_data);
cv.fillPoly(img, pts, color);
let compare_result = new cv.Mat(img_height, img_width, cv.CV_8UC1);
cv.compare (img, expected_img, compare_result, cv.CMP_EQ);
// expect every pixels are the same.
assert.equal (cv.countNonZero(compare_result), img.total());
img.delete();
square_points.delete();
pts.delete();
expected_img.delete();
compare_result.delete();
}
// fillConvexPoly
{
let img_width = 6;
let img_height = 6;
let img = new cv.Mat.zeros(img_height, img_width, cv.CV_8UC1);
let npts = 4;
let square_point_data = new Uint8Array([
1, 1,
4, 1,
4, 4,
1, 4]);
let square_points = cv.matFromArray(npts, 1, cv.CV_32SC2, square_point_data);
let color = new cv.Scalar (255);
let expected_img_data = new Uint8Array([
0, 0, 0, 0, 0, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 255, 255, 255, 255, 0,
0, 0, 0, 0, 0, 0]);
let expected_img = cv.matFromArray(img_height, img_width, cv.CV_8UC1, expected_img_data);
cv.fillConvexPoly(img, square_points, color);
let compare_result = new cv.Mat(img_height, img_width, cv.CV_8UC1);
cv.compare (img, expected_img, compare_result, cv.CMP_EQ);
// expect every pixels are the same.
assert.equal (cv.countNonZero(compare_result), img.total());
img.delete();
square_points.delete();
expected_img.delete();
compare_result.delete();
}
}); });
QUnit.test('test_segmentation', function(assert) { QUnit.test('test_segmentation', function(assert) {