Now that we can classify objects in images, the next step is to and classify (detect) objects in images. In the dataset we used in the previous recipe, the (objects) were clearly visible, mostly centered, and they covered almost the complete image. However, often this is not the case and we'd want to detect one or multiple objects in an image. In the following recipe, we will show you how to detect an object in images using deep learning.
We will be using a dataset with annotated trucks. The images are taken by a camera mounted at the front of a car. We will be using TensorFlow to implement the object detector.
- Let's the first:
import numpy as np import pandas as pd 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 from keras.models import Sequential, load_model from keras.layers import Dense...