Classifying objects in images

In this recipe, we will show you to classify objects in using a CNN. We will train the network from scratch to classify five different flower types in images. The images have different sizes. For this recipe, we will be using Keras.

How to do it...

1. Create a new Python file and import the necessary libraries:

import numpy as np
import glob
import cv2
import matplotlib.pyplot as plt

from sklearn.preprocessing import LabelBinarizer
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

import keras
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, MaxPooling2D, Lambda, Cropping2D
from keras.utils import np_utils
from keras import optimizers

SEED = 2017

2. Next, we load the dataset and extract the labels:

# Specify data directory and extract all file names
DATA_DIR = '../Data/'
images = glob.glob(DATA_DIR + "flower_photos/*/*.jpg")
# Extract labels from file...