Ejemplo n.º 1
0
img = img_as_ubyte(rgb2grey(lena()))

img_grey = cv2.equalizeHist(rgb2grey(img))

ImageViewer(img_grey).show()
 
cascade = cv2.CascadeClassifier('/usr/share/opencv/haarcascades/haarcascade_frontalface_alt.xml')
rects = cascade.detectMultiScale(img_grey, scaleFactor=1.1,
                                 minNeighbors=3,
                                 minSize=(20,20),
                                 flags = cv.CV_HAAR_SCALE_IMAGE)

# x y w h -> x1 y1 x2 y2
rects[:,2:] += rects[:,:2]

boxes(img,rects)

capture = cv.CaptureFromCAM(0)
frame = np.asarray(cv.QueryFrame(capture)[:,:]).copy()
frame_grey = img_as_ubyte(rgb2grey(frame))
del(capture)

ImageViewer(frame).show()

rects = cascade.detectMultiScale(frame_grey, scaleFactor=1.1,
                                 minNeighbors=3,
                                 minSize=(20,20),
                                 flags = cv.CV_HAAR_SCALE_IMAGE)
rects[:,2:] += rects[:,:2]

boxes(frame_grey,rects)
Ejemplo n.º 2
0
bkg = GaussianBlur(background, kernel, blur) 
cur = GaussianBlur(current, kernel, blur)

ImageViewer(cur).show()

# get absolute difference between images
absdiff = abs(img_as_float(cur) - img_as_float(bkg))

ImageViewer(absdiff).show()

grey = rgb2grey(absdiff)

# threshold automatically
thresholded = grey > threshold_otsu(grey)

ImageViewer(thresholded).show()

dilated = binary_dilation(thresholded, disk(9))

ImageViewer(dilated).show()

filtered = remove_small_objects(dilated, 7000)

ImageViewer(filtered).show()

# draw box around the car
props = regionprops(label(filtered),properties=['BoundingBox'])

boxes(current,[props[0]['BoundingBox']])