import tensorflowjs as tfjs
import tensorflow as tf
import os
from os.path import abspath


def getHome():
    backend = os.path.dirname(os.getcwd())
    return os.path.dirname(backend)


model = tf.keras.models.load_model(abspath(getHome() + '/models/num_reader.h5')
    )
tfjs.converters.save_keras_model(model, abspath(getHome() +
    '/models/num_reader'))

98c61f4e2a3d159c68e8e0ee88ab503dca20bb90
<mask token>


def getHome():
    backend = os.path.dirname(os.getcwd())
    return os.path.dirname(backend)


<mask token>

<mask token>


def getHome():
    backend = os.path.dirname(os.getcwd())
    return os.path.dirname(backend)


<mask token>
tfjs.converters.save_keras_model(model, abspath(getHome() +
    '/models/num_reader'))

<mask token>


def getHome():
    backend = os.path.dirname(os.getcwd())
    return os.path.dirname(backend)


model = tf.keras.models.load_model(abspath(getHome() + '/models/num_reader.h5')
    )
tfjs.converters.save_keras_model(model, abspath(getHome() +
    '/models/num_reader'))

import tensorflowjs as tfjs
import tensorflow as tf
import os
from os.path import abspath


def getHome():
    backend = os.path.dirname(os.getcwd())
    return os.path.dirname(backend)


model = tf.keras.models.load_model(abspath(getHome() + '/models/num_reader.h5')
    )
tfjs.converters.save_keras_model(model, abspath(getHome() +
    '/models/num_reader'))
