video_mosaic = pb.FactoryVideoMosaic(np.uint8).mosaic(config_tracker)
video_mosaic.configure(1000, 500, scale=0.5)
image_input = video_mosaic.get_image_type().create_boof_image(0, 0)
boof_color = None
while True:
# Capture sequence frame-by-frame
ret, frame = cap.read()
# Convert it into a boofcv image
boof_color = pb.ndarray_to_boof(frame, boof_color)
# Convert it into the image type required by the tracker
pb.convert_boof_image(boof_color, image_input)
# Track the point objects
time0 = time.time() * 1000.0
if not video_mosaic.process(image_input):
print("mosaic failed!")
video_mosaic.reset()
continue
time1 = time.time() * 1000.0
# Get the mosaic image and display the results
boof_mosaic = video_mosaic.get_stitched_image()
ndarray_mosaic = pb.boof_to_ndarray(boof_mosaic)
cv2.imshow("Video Mosaic", ndarray_mosaic)
ret, frame = cap.read()
if not ret:
print "Failed to read frame"
exit(-1)
image_input = tracker.getImageType().create_boof_image(frame.shape[1], frame.shape[0])
while True:
# Capture frame-by-frame
ret, frame = cap.read()
time0 = int(round(time.time() * 1000))
# Convert it into a boofcv image
boof_color = pb.ndarray_to_boof(frame)
time1 = int(round(time.time() * 1000))
# Convert it into the image type required by the tracker
pb.convert_boof_image(boof_color,image_input)
time2 = int(round(time.time() * 1000))
print("time py to boof: "+str(time1-time0)+" boof to boof "+str(time2-time1))
if state == 1:
cv2.rectangle(frame, refPt[0], refPt[1], (0, 255, 0), 2)
elif state == 2:
pts_to_quad()
if not tracker.initialize(image_input,quad):
print "Initialization failed!"
state = 0
else:
print "Success"
state = 3
elif state == 3: