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using OpenCV
function detect(img::OpenCV.InputArray, cascade)
rects = OpenCV.detectMultiScale(cascade, img, scaleFactor=1.3, minNeighbors=Int32(4), minSize=OpenCV.Size{Int32}(30, 30), flags=OpenCV.CASCADE_SCALE_IMAGE)
processed_rects = []
for rect in rects
push!(processed_rects, (rect.x, rect.y, rect.width+rect.x, rect.height+rect.y))
end
return processed_rects
end
function draw_rects(img, rects, color)
for x in rects
OpenCV.rectangle(img, OpenCV.Point{Int32}(x[1], x[2]), OpenCV.Point{Int32}(x[3], x[4]), color, thickness = Int32(2))
end
end
cap = OpenCV.VideoCapture(Int32(0))
# Replace the paths for the classifiers before running
cascade = OpenCV.CascadeClassifier("haarcascade_frontalface_alt.xml")
nested = OpenCV.CascadeClassifier("haarcascade_eye.xml")
OpenCV.namedWindow("facedetect")
while true
ret, img = OpenCV.read(cap)
if ret==false
print("Webcam stopped")
break
end
gray = OpenCV.cvtColor(img, OpenCV.COLOR_BGR2GRAY)
gray = OpenCV.equalizeHist(gray)
rects = detect(gray, cascade)
vis = copy(img)
draw_rects(vis, rects, (0.0, 255.0, 0.0))
if ~OpenCV.empty(nested)
for x in rects
roi = view(gray, :, Int(x[1]):Int(x[3]), Int(x[2]):Int(x[4]))
subrects = detect(roi, nested)
draw_view = view(vis, :, Int(x[1]):Int(x[3]), Int(x[2]):Int(x[4]))
draw_rects(draw_view, subrects, (255.0, 0.0, 0.0))
end
end
OpenCV.imshow("facedetect", vis)
if OpenCV.waitKey(Int32(5))==27
break
end
end
OpenCV.release(cap)
OpenCV.destroyAllWindows()
print("Stopped")
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