The article writes about the process on how to code an image recognition system and its applications. So let us begin now.
Introduction Of Code Image Recognition
The image recognition system is used to identify the image. This image you are passing through the image recognition system.
The image recognition system can be used for identifying the following:
- People,
- animals and any other objects.
The image recognition systems are widely used in security systems, offices, and many more places.
So we will have the step-by-step process of coding the image recognition system.
Step-by-step process of Image Recognition System
STEP 1: Set The Environment For Coding
First, you need to set the environment for coding. You can use any language you want. You can use Python, Java, C++, etc. For this article, I will take Python as an example. The reason is that Python is easy to learn and use in coding.
Also, you need to install the following packages in the environment:
PIL (Python Imaging Library)
OpenCV (Open Source Computer Vision Library)
Numpy (A library of scientific computing routines for python)
Scipy (A library of scientific computing routines for python)
Keras (A high-level neural networks API, written in Python and capable of running on top of either TensorFlow or Theano).
STEP 2: Set The Image Recognition System
Environment
First, in the image recognition system, you need to set an environment for recognizing images.
So for setting this environment, you need to create two files.
file1 file2
You can name them as you want. And the name of the files should be given as “TestImageRecognition.py”.
STEP 3: Create The Test Image And Store It Into The File
First, create an image with any drawing tool like paint, etc., and save it in jpg format in your desktop folder. The name of the file should be given as “testImageRecognition.jpg”.
You need to set the size of the image to 300 x 300 pixels for this tutorial. You can also use one of the images that you have already created for testing the system if you want.
So now we have our test image with us and we will move on to step 4 for coding our image recognition system.
STEP 4: Coding The Image Recognition System In Python
In this step, we will start coding our image recognition system in Python. First, create a new file and name it as “imageRecognition.py ” and save it in your desktop folder. Or anywhere you want inside your system directory where your Python program is located.
The code is nothing but a small part of a larger code that creates an artificial neural network from scratch using TensorFlow or TFLearn. A high-level computer vision API based on Google’s internal TensorFlow framework.
Also, it runs it using a GPU on a custom dataset of images belonging to one of four categories: airplanes, cars, cats, and dogs.
This part of the code is taken from the official website of the project.
The important thing to note is that all libraries are imported at the very beginning of the program, including Keras itself. Also, an argument is passed to the constructor function for specifying the path to the TensorFlow backend. It is worth noting that if you want to run it with Theano, you can remove Keras.backend.tensorflow_backend().
STEP 5: Defining The Image Recognition System in Python Code
Next in the code, we define the image recognition system in Python. This system is used for identifying images through a neural network. There are total of four categories in this image recognition system which are:
- Airplanes
- Cars
- Cats
- Dogs
So you need to define these four categories in your code. You do this by using four separate lists. These are lists of strings that represent these categories.
So all you need to do is define these lists of strings and assign them with the names of their corresponding categories. This way you will have all categories listed with their respective names in your code.
It should look similar to this:“classA = [‘Airplane’, ‘Airplanes’, ‘Plane’, ‘Planes’] classB = [‘Car’, ‘Cars’, ‘Automobile’, ‘Automobiles’] classC = [‘Cat’, ‘Kitten’, ‘Catnip’, ‘Kitty’] classD = [‘Dog’, ‘Puppy’, ‘Canine’, ‘Puppies’]”
STEP 6: Set The Number Of Classes In The Image Recognition System In Python Code
Next in the code, you need to set the number of classes in the image recognition system. This number is used to classify different types of images in a particular category.
This number is used to classify different types of images in a particular category. So you need to set the number of classes in your image recognition system for identifying images. You can take a number that will give a fair number of images from each category.
