main_train.py

from flask import Flask, render_template, request
from werkzeug import secure_filename
from PIL import Image
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D, BatchNormalization
from keras.layers import Activation, Dropout, Flatten, Dense
from keras.preprocessing.image import ImageDataGenerator
from keras.models import load_model, model_from_json

import numpy as np
import cv2
import webcolors
import time, os
import sys, h5py
import shutil
import random

np.random.seed(0)

from image_preprocess import crack_detection_preprocess_image
from image_preprocess import move_files_test_folder
from image_preprocess import preprocess_img
from CNNclassifier import training

os.environ['KMP_DUPLICATE_LIB_OK']='True'

app = Flask(__name__)

# root
@app.route("/")
def index():
    """
    this is a root dir of my server
    :return: str
    """
    return '''This is training API :
    To start training, go to http://127.0.0.1:5000/crack_detection_train'''

@app.route('/crack_detection_train')
def train_cnn():
    no_files = crack_detection_preprocess_image()
    # print(type(no_files), no_files)
    to_move = float(no_files)*0.2
    # print(int(to_move), type(to_move))
    move_files_test_folder(int(to_move))
    training()

    return 'Training successful'


if __name__ == '__main__':
   app.run(debug=True)