# cv2.putText(vis_roi,
# "%s (%s)" % (who, confidence),
# (sx1 + 2, sy1 + 20 + 20 * i),
# cv2.FONT_HERSHEY_PLAIN, 1.1, color)
winning_label = recog.get_overall_prediction(predictions)
#rect_color = recog.LABEL_COLORS[winning_label]
karlness_update = 1 if who == "Karl" else 0
else:
#rect_color = (0, 255, 255)
karlness_update = 1
karlness = KARLNESS_DECAY * karlness + (1 - KARLNESS_DECAY) * karlness_update
rect_color = (0, 255 * (1 - karlness), 255 * karlness)
draw_rects(vis_roi, subtargets, rect_color)
if not contains(next_targets, subtargets[0]):
fixed_rect = [max(0, x1-BUFFER)+sx1,max(0, y1-BUFFER)+sy1,max(0, x1-BUFFER)+sx2,max(0, y1-BUFFER)+sy2]
s_last, c_last = size_and_center(fixed_rect)
next_targets.append((
fixed_rect,
0,
VELOCITY_DECAY*velocity+(1-VELOCITY_DECAY)*np.array(diff(c_last, c)),
karlness
))
else:
# draw_rects(vis, [rect], (0,0,255))
if misses < MAX_MISSES:
subtargets = detect(roi_copy,
cascade_nested,
size=(max(30, s[0] - REFIND_BUFFER),
max(30, s[1] - REFIND_BUFFER)))
if len(subtargets) == 1:
sx1, sy1, sx2, sy2 = subtargets[0]
if not contains(next_targets, subtargets[0]):
next_targets.append(([
max(0, x1 - BUFFER) + sx1,
max(0, y1 - BUFFER) + sy1,
max(0, x1 - BUFFER) + sx2,
max(0, y1 - BUFFER) + sy2
], 0, None))
vis_roi = vis[max(0, y1 - BUFFER):min(width, y2 + BUFFER),
max(0, x1 - BUFFER):min(height, x2 + BUFFER)]
draw_rects(vis_roi, subtargets, (0, 255, 0))
cv.SaveImage("%s/roi/%s.pgm" % (output_dir, time.time()),
cv.fromarray(roi_copy, allowND=True))
cv.SaveImage(
"%s/face/%s.pgm" % (output_dir, time.time()),
cv.fromarray(roi[sx1:sx2, sy1:sy2].copy(), allowND=True))
else:
# draw_rects(vis, [rect], (0,0,255))
if misses < MAX_MISSES:
next_targets.append((rect, misses + 1, None))
targets = next_targets
if is_auto:
targeter.update_targets(targets)
# print "targets: ", len(targets)
# (sx1 + 2, sy1 + 20 + 20 * i),
# cv2.FONT_HERSHEY_PLAIN, 1.1, color)
winning_label = recog.get_overall_prediction(
predictions)
#rect_color = recog.LABEL_COLORS[winning_label]
karlness_update = 1 if who == "Karl" else 0
else:
#rect_color = (0, 255, 255)
karlness_update = 1
karlness = KARLNESS_DECAY * karlness + (
1 - KARLNESS_DECAY) * karlness_update
rect_color = (0, 255 * (1 - karlness), 255 * karlness)
draw_rects(vis_roi, subtargets, rect_color)
if not contains(next_targets, subtargets[0]):
fixed_rect = [
max(0, x1 - BUFFER) + sx1,
max(0, y1 - BUFFER) + sy1,
max(0, x1 - BUFFER) + sx2,
max(0, y1 - BUFFER) + sy2
]
s_last, c_last = size_and_center(fixed_rect)
next_targets.append(
(fixed_rect, 0, VELOCITY_DECAY * velocity +
(1 - VELOCITY_DECAY) * np.array(diff(c_last, c)),
karlness))
x1, y1, x2, y2 = rect
with the_lock:
roi = low_image[max(0, y1-BUFFER):min(width, y2+BUFFER), max(0, x1-BUFFER):min(height, x2+BUFFER)]
# draw_rects(vis, [[max(0, x1-BUFFER), max(0, y1-BUFFER), min(height, x2+BUFFER), min(width, y2+BUFFER)]], (255,0,0))
subt = clock()
s, c = size_and_center(rect)
roi_copy = roi.copy()
subtargets = detect(roi_copy, cascade_nested, size=(max(30, s[0]-REFIND_BUFFER), max(30, s[1]-REFIND_BUFFER)))
if len(subtargets) == 1:
sx1, sy1, sx2, sy2 = subtargets[0]
if not contains(next_targets, subtargets[0]):
next_targets.append(([max(0, x1-BUFFER)+sx1,max(0, y1-BUFFER)+sy1,max(0, x1-BUFFER)+sx2,max(0, y1-BUFFER)+sy2], 0, None))
vis_roi = vis[max(0, y1-BUFFER):min(width, y2+BUFFER), max(0, x1-BUFFER):min(height, x2+BUFFER)]
draw_rects(vis_roi, subtargets, (0, 255, 0))
cv.SaveImage("%s/roi/%s.pgm" % (output_dir, time.time()), cv.fromarray(roi_copy, allowND=True))
cv.SaveImage("%s/face/%s.pgm" % (output_dir, time.time()), cv.fromarray(roi[sx1:sx2, sy1:sy2].copy(), allowND=True))
else:
# draw_rects(vis, [rect], (0,0,255))
if misses < MAX_MISSES:
next_targets.append((rect, misses+1, None))
targets = next_targets
if is_auto:
targeter.update_targets(targets)
# print "targets: ", len(targets)
dt = clock() - t
# with the_lock:
# print "time: ", dt*1000