Code for fish recognition

After explaining the main building blocks for our fish recognition example, we are ready to see all the code pieces connected together and see how we managed to build such a complex system with just a few lines of code:

#Loading the required libraries along with the deep learning platform Keras with TensorFlow as backend
import numpy as np
np.random.seed(2017)
import os
import glob
import cv2
import pandas as pd
import time
import warnings
from sklearn.cross_validation import KFold
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.optimizers import SGD
from keras.callbacks import EarlyStopping
from keras.utils import np_utils
from sklearn.metrics import log_loss
from keras import __version__ as keras_version
# Parameters
# ----------
# x : type
#    Description of parameter `x`.
def rezize_image(img_path):
  img = cv2.imread(img_path...