# coding: utf-8
import os
import sys
import re
import base64
import json
from io import BytesIO
from function.modules import json_parser
from function.modules import Client
from keras.preprocessing import image
from PIL import Image
import numpy as np
client = Client('fackAPI', silent=True)
run = client.run
train = client.train
predict = client.predict
work_path = 'function/'
default_path =work_path
# default_path =''
def handle(conf):
def base64_to_image(base64_str, grayscale, target_size):
base64_data = re.sub('^data:image/.+;base64,', '', base64_str)
byte_data = base64.b64decode(base64_data)
image_data = BytesIO(byte_data)
img = image.load_img(image_data, grayscale, target_size)
return image.img_to_array(img)
# You can use other public modules via our Client object with module's identifier
# and parameters.
# For more detailes, please see our online document - https://momodel.github.io/mo/#
import os
import sys
# Import necessary packages
from function.modules import json_parser
from function.modules import Client
# Initialise Client object
client = Client(api_key='5asdfoasd0fnd0983',
project_id='5af2abafe13823a5f1687062',
user_ID='zhaofengli',
project_type='app',
source_file_path='3_Develop_and_Deploy_your_first_App.ipynb',
silent=True)
# Make run/train/predict commnad alias for furthur use
run = client.run
train = client.train
predict = client.predict
# Run a importred module
# e.g.
# conf = json_parser('{"rgb_image":null,"gray_image":null}')
# result = run('zhaofengli/new_gender_classifier/0.0.2', conf)
#
# 'conf' is the parameters in dict form for the imported module
# '[user_id]/[imported_module_name]/[version]' is the identifier of the imported module