def find_pentagons(contours):
pentagons = []
for ctr in contours:
area = cv2.contourArea(ctr)
# area test
if area < 400: continue
simp_ctr = cv2.approxPolyDP(ctr, 3, True)
simp_area = cv2.contourArea(simp_ctr)
if simp_area < 400: continue
if len(simp_ctr) != 5: continue
edges = [
LA.norm(a - b) for a, b in zip(simp_ctr, np.roll(simp_ctr, 2))
]
ratios = [(1 - e / edges[0])**2 for e in edges]
passr = [r for r in ratios if r > 0.2]
if len(passr) > 0: continue
pentagons.append(simp_ctr)
return pentagons
if __name__ == "__main__":
cam = OpenCV_Cam()
cam.cam_loop(contour_proc)
return frame
def find_milkbox(contours):
pentagons = []
for ctr in contours:
vecs = zip(ctr, np.roll(ctr, 1))
normalized_vecs = []
for vec in vecs:
length = LA.norm(vec[0] - vec[1])
norm_vec = (vec[0] - vec[1]) / length
normalized_vecs.append(norm_vec)
paired_vecs = zip(normalized_vecs, np.roll(normalized_vecs, 2))
count = 0
for pair in paired_vecs:
angle = np.inner(pair[0], pair[1])
if angle < 0.05:
count = count + 1
if count != 2:
continue
pentagons.append(ctr)
return pentagons
if __name__ == "__main__":
cam = OpenCV_Cam()
cam.cam_loop(contour_proc)
