def houghDetect(img, radiusMin, radiusMax):
"""
:param img: grayscale image with some circles
:return:[bounding rectangles]
"""
circles = cv2.HoughCircles(img,
cv2.HOUGH_GRADIENT,
1,
150,
param1=101,
param2=11,
minRadius=radiusMin,
maxRadius=radiusMax)
rois = []
radii = []
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
center = (i[0], i[1])
cv2.circle(img, center, 1, (0, 100, 100), 3)
radius = i[2]
if radiusMin < radius < radiusMax:
cv2.circle(img, center, radius, (255, 0, 255), 3)
roi = ImgUtils.findBoxAroundCircle(center, radius)
rois.append(roi)
radii.append(radius)
return rois, radii
def postbake1Debug(self, feed):
radiusMin = self.dim1Lower
radiusMax = self.dim1Upper
img = self.transform(feed)
circles = cv2.HoughCircles(img,
cv2.HOUGH_GRADIENT,
1,
150,
param1=101,
param2=11,
minRadius=radiusMin,
maxRadius=radiusMax)
dets = []
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
center = (i[0], i[1])
cv2.circle(img, center, 1, (0, 100, 100), 3)
radius = i[2]
if radiusMin < radius < radiusMax:
cv2.circle(img, center, radius, (255, 0, 255), 3)
dets.append(ImgUtils.findBoxAroundCircle(center, radius))
return dets