def balance(self, repeats=5, threshold=10):
balanced = False
window = images.Displayer('Levelling')
center = (0, 0)
distance = 0
while balanced is False:
centers = []
for f in range(repeats):
self.f = f
self.shaker.change_duty(self.start)
time.sleep(5)
self.shaker.ramp(self.start, self.end, self.rate, record=False,
stop_at_end=False)
time.sleep(5)
im = self.im()
center = self.find_center(im)
centers.append(center)
mean_center = np.mean(centers, axis=0).astype(np.int32)
annotated_im = self.annotate_image(im, center,
mean_center, distance,
centers)
window.update_im(annotated_im)
mean_center = np.mean(centers, axis=0).astype(np.int32)
instruction, distance = self.find_instruction(mean_center)
annotated_im = self.annotate_image(im, center, mean_center,
distance, centers)
window.update_im(annotated_im)
if distance > threshold:
self.run_instruction(instruction)
else:
balanced = True
print('BALANCED')
print(datetime.datetime.now())
self.shaker.change_duty(0)
def balance(self, repeats=5, threshold=10):
balanced = False
window = images.Displayer('Levelling')
center = (0, 0)
while balanced is False:
centers = []
self.shaker.ramp(630, 500, 0.5)
for f in range(repeats):
self.f = f
time.sleep(0.1)
im = self.get_frame()
center = self.get_center(im)
centers.append(center)
mean_center = np.mean(centers, axis=0)
instruction, distance = self.find_instruction(mean_center)
annotated_im = self.annotate_image(im, center, mean_center,
distance, centers)
window.update_im(annotated_im)
if distance > threshold:
self.run_instruction(instruction)
time.sleep(10)
else:
balanced = True
print('BALANCED')
print(datetime.datetime.now())
self.shaker.change_duty(0)
N = min(NL, NS)
def get_crop_result(vid):
frame = vid.read_next_frame()
frame = ndimage.rotate(frame, -120, reshape=False)
crop_result = images.crop_rectangle(frame)
vid.set_frame(0)
return crop_result
def fix_frame(frame):
frame = ndimage.rotate(frame, -120, reshape=False)
frame = images.crop_and_mask(frame, crop_result.bbox, crop_result.mask)
return frame
crop_result = get_crop_result(liquid)
window = images.Displayer('frames')
for f in range(N):
liquid_frame = liquid.read_next_frame()
liquid_frame = fix_frame(liquid_frame)
solid_frame = solid.read_next_frame()
solid_frame = fix_frame(solid_frame)
frames = images.vstack(liquid_frame, solid_frame)
window.update_im(frames)