Text Animation in Python

Animation-Text

class Signal: # <1>
    go = True

def spin(msg, signal):  # <2>
    write, flush = sys.stdout.write, sys.stdout.flush
    for char in itertools.cycle('|/-\\'):  # <3>
        status = char + ' ' + msg
        write(status)
        flush()
        time.sleep(.1)
        write('\x08' * len(status))  # <4>
        if not signal.go:
              break
    write(' ' * len(status) + '\x08' * len(status))  # <6>


def slow_function():  # <7>
    # pretend waiting a long time for I/O
    time.sleep(3)  # <8>
    return 42


def supervisor():  # <9>
    signal = Signal()
    spinner = threading.Thread(target=spin,
                               args=('thinking!', signal))
    print('spinner object:', spinner)  # <10>
    spinner.start()  # <11>
    result = slow_function()  # <12>
    signal.go = False  # <13>
    spinner.join()  # <14>
    return result


def main():
    result = supervisor()  # <15>
    print('Answer:', result)


if __name__ == '__main__':
    main()

---

PaddleGAN

python -m pip install munch scikit-image

python -m pip install paddlepaddle-gpu==2.2.2

import paddle
#paddle.set_device('cpu')
paddle.set_device('gpu')
from ppgan.apps import DeOldifyPredictor
deoldify = DeOldifyPredictor()
pred = deoldify.run_image("/mnt/8A26661926660713/Deng/Cell_segmentation/lgl4wd5d1_c2.tif")
pred.save('deoldify_result.jpg')

$$\frac{r_C×C +rG×G}{(1-r_{CG})(C+G)}=r_T$$
$C=53012;\ r_C=38.27%$
$G=19742.5;\ r_G=13%$
$TM=73304;\ r_{T}=36.7%$
$r_{CG}=10.725%$

$(G+C)*(1-r_{CG})=64951.58$
$\frac{38.27%×53012 + 13%19742.5}{(1-10.725%)(53012+19742.5)}≈38.811%$