There is no virtual limit to the type of objects you can detect in your images and videos. However, to obtain an acceptable level of accuracy, you need a sufficiently large dataset, containing train images that are identical in size.

This would be a time consuming operation if we were to do it all by ourselves (which is entirely possible).

We can avail of ready-made datasets; there are a number of them freely downloadable from various sources:

I'll be using the UIUC dataset in my example, but feel free to explore the Internet for other types of datasets.

Now, let's take a look at an example:

import cv2
import numpy as np
from os.path import join

datapath = "/home/d3athmast3r/dev/python/CarData/TrainImages/"
def path(cls,i):
  return "%s/...