def anim(func, time_length, interval=0.1, width=400):
img = Image_widget(width=width)
display(img)
start_time = time.time()
for t in np.arange(0, time_length, interval):
frame = Image.fromarray((func(t)*255).astype('uint8'))
img.value = frame._repr_png_()
now = time.time()
if now < start_time+t:
time.sleep(start_time+t-now)
wImg_dst2 = Image(layout=Layout(border="solid"), width="45%")
wImg_dst3 = Image(layout=Layout(border="solid"), width="45%")
items = [wImg_original, wImg_dst]
items2 = [wImg_dst2, wImg_dst3]
Left_image = Box(items)
Right_image = Box(items2)
box = layout(IntSlider_Threshold, Left_image, Right_image)
tab_nest = widgets.Tab()
tab_nest.children = [box]
tab_nest.set_title(0, 'Fast Feature Detect1')
tab_nest
tmpStream = cv2.imencode(".jpeg", src)[1].tostring()
wImg_original.value = tmpStream
display.display(tab_nest)
#Event 선언
threshold = 1
def on_value_change_Threshold(change):
global threshold
threshold = change['new']
make_fastfeature(threshold)
def make_fastfeature(input_threshold):
fastF = cv2.FastFeatureDetector.create(threshold=input_threshold)
