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optional downsample #978

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Aug 30, 2023
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optional downsample #978

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12 changes: 8 additions & 4 deletions examples/tracking/visual/PyCV_TrackFeaturesFwdBck.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -49,17 +49,21 @@ function goodFeaturesToTrack(im1, feature_params; mask=nothing)
cv.goodFeaturesToTrack(collect(reinterpret(UInt8, im1)), mask=collect(reinterpret(UInt8,mask)), feature_params...)
end

function goodFeaturesToTrackORB(im1; mask=nothing, orb = cv.ORB_create(), downsample::Int=5, tolerance::Real = 0.1)
function goodFeaturesToTrackORB(im1; mask=nothing, orb = cv.ORB_create(), downsample::Int=1, tolerance::Real = 0.1)
# gray = cv2.cvtColor(im1,cv.COLOR_BGR2GRAY)
# kypts, decrs = orb.detectAndCompute(gray,None)
# https://docs.opencv.org/3.4/d1/d89/tutorial_py_orb.html
# find the keypoints with ORB
img = collect(reinterpret(UInt8, im1))
kp = orb.detect(img, collect(reinterpret(UInt8,mask)))

# downselect a better distribution of features
rows, cols = size(img,1), size(img,2)
sel_kp = ssc(kp, orb.getMaxFeatures() ÷ downsample, tolerance, cols, rows)
sel_kp = if 1 < downsample
# downselect a better distribution of features
rows, cols = size(img,1), size(img,2)
ssc(kp, orb.getMaxFeatures() ÷ downsample, tolerance, cols, rows)
else
kp
end

# compute the descriptors with ORB
kp_, des = orb.compute(img, sel_kp)
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