Building an object recognizer

Now that we trained an ERF model, let's go ahead and build an object recognizer that can recognize the content of unknown images.

How to do it…

1. Create a new Python file, and import the following packages:

   import argparse 
   import cPickle as pickle 
   
   import cv2
   import numpy as np
   
   import build_features as bf
   from trainer import ERFTrainer 

2. Define the argument parser:

   def build_arg_parser():
       parser = argparse.ArgumentParser(description='Extracts features \
   from each line and classifies the data')
       parser.add_argument("--input-image", dest="input_image", required=True,
   help="Input image to be classified")
       parser.add_argument("--model-file", dest="model_file", required=True,
   help="Input file containing the trained model")
       parser.add_argument("--codebook-file", dest="codebook_file", 
   required=True, help="Input file containing the codebook")
       return parser

3. Define a class to handle the image tag extraction functions:

   class ImageTagExtractor(object):
       def...