Python Deep Learning Cookbook

How to do it...

1. Let's import the libraries first:

import numpy as npimport pandas as pdimport globimport cv2import matplotlib.pyplot as pltfrom sklearn.preprocessing import LabelBinarizerfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_scorefrom keras.models import Sequential, load_modelfrom keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, MaxPooling2D, Lambda, Cropping2Dfrom keras.utils import np_utilsfrom keras import backend as Kfrom keras.callbacks import EarlyStoppingfrom keras import optimizers

2. Load the dataset and plot the first rows of the CSV:

DATA_DIR = 'Data/object-detection-crowdai/'labels = pd.read_csv(DATA_DIR + 'labels.csv', usecols=[0,1,2,3,4,5])# We will only localize ...