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Resolved issues with multiple face detection

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esimov
2019-08-09 11:48:35 +03:00
parent adad6e2c06
commit f1b1e9e380
2 changed files with 23 additions and 24 deletions
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30
examples/puploc/puploc.py
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@@ -36,7 +36,7 @@ def process_frame(pixs):
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 4,))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 5,))
# The first value of the buffer aray represents the buffer length.
dets_len = res[0][0]
@@ -44,7 +44,7 @@ def process_frame(pixs):
# We have to consider the pupil pair added into the list.
# That's why we are multiplying the detection length with 3.
dets = list(res.reshape(-1, 4))[0:dets_len*3]
dets = list(res.reshape(-1, 5))[0:dets_len*3]
return dets
# initialize the camera
@@ -69,21 +69,21 @@ while(True):
dets = process_frame(pixs) # pixs needs to be numpy.uint8 array
if dets is not None:
for det in dets[0:1]:
# We know that the detected faces are taking place in the first positions of the multidimensional array.
for det in dets:
if det[3] > 50:
cv2.circle(frame, (int(det[1]), int(det[0])), int(det[2]/2.0), (0, 0, 255), 2)
if det[4] == 1: # 1 == face; 0 == pupil
cv2.circle(frame, (int(det[1]), int(det[0])), int(det[2]/2.0), (0, 0, 255), 2)
else:
if showPupil:
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if showEyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 0), 2
)
for det in dets[1:]:
if det[3] > 50:
if showPupil:
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if showEyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 0), 2
)
cv2.imshow('', frame)
key = cv2.waitKey(1)