You must have used Instagram once in your life, have you noticed that you see a variety of Instagram filters when uploading an image. These filters are designed to improve the quality of the image. These filters are an example of complex machine learning algorithms that are deployed in production to serve Instagram. So if these filters are created by machine learning algorithms, it means that we can also create Instagram filters with Python.
In this article, I’ll walk you through how to create beautiful Instagram filters using machine learning. The best part of this task is that we are using Python. The biggest advantage of using such a popular language like Python is that you will get packages for almost every task.
Creating Instagram Filters with Python
While building a neural network to create Instagram filters is a complex task. In this article, I will use the Instafilter library in Python which will help us to use Instagram filters with Python.
If you want to how we can create such amazing filters with Python without using the Instafilter package just mention in the comments section below. Now let’s see how we can use the Instafilter library in Python to create Instagram Filters with Python.
You can easily install this library by using the pip command – pip install instafilter. I hope you will not get any errors while installing this library.
The other library we need for creating Instagram filters is the Open Source Computer Vision Library of Python which is OpenCV. If you have never worked with OpenCV you can easily install it by using a pip command – pip install opencv-python. To use OpenCV we do not import it by the same name, we import it by the name of cv2 (import cv2). Let’s create Instagram filters with Python:
Code language: PHP (php)
from instafilter import Instafilter model = Instafilter("Lo-fi") new_image = model("image.jpg") # To save the image, use cv2 import cv2 cv2.imwrite("modified_image.jpg", new_image)
Your saved images will look like:
I hope you liked this article on how we can create Instagram filters. Feel Free to ask your valuable questions in the comments section below.