tayafindmy.blogg.se

Easy contour python
Easy contour python




easy contour python
  1. #EASY CONTOUR PYTHON HOW TO#
  2. #EASY CONTOUR PYTHON CODE#
  3. #EASY CONTOUR PYTHON DOWNLOAD#
  4. #EASY CONTOUR PYTHON FREE#

We are keeping these functions separate so that our code remains as clean and readable as possible. This Python file contains a few utility functions that we can execute when required. Utility Functions for Image Foreground Extraction using OpenCV Contour DetectionĪll the code here will go into the utils.py file. We will start with the utils.py Python script and then move into the main extract_foreground.py file. Image Foreground Extraction using OpenCV Contour Detectionįrom here onward, we will get into the details of the two Python files while writing the code for them. From the next section onward, we will move into the coding part of this tutorial.

#EASY CONTOUR PYTHON FREE#

All the images are taken from Pixabay and are free to use.

#EASY CONTOUR PYTHON DOWNLOAD#

  • And finally, the outputs folder will contain the output images after we run our Python scripts.Ĭoming to the input images, you can download them by clicking the button below.Īfter downloading, just unzip the file inside your project directory and you are good to go.
  • The input folder contains the input images that we will be using in this tutorial.
  • Directly inside the parent project directory, we have two Python files, extract_foreground.py and utils.py.
  • We will be using the following directory structure for this tutorial. If you are using any of the newer versions and face issues, then try installing version 4.2.0.32 and you will be able to proceed smoothly. At least, I have faced some errors regarding the same a few times. Sometimes, the very recent versions of opencv-python have issues with the imshow() function.

    easy contour python

    Although I recommend using the same version that I am using, still you should not be facing any issues if using any 4.x versions. That is the OpenCV computer vision library. Libraries and Dependenciesįor this tutorial, there is just one major library that we need. I hope that you are interested to follow this article through to the end. What you see in the bottom-most image is after we have merged the extracted foreground image with a new colorful background. That is when we have extracted only the person from the top image. The middle image shows the foreground image. In figure 1, the top image shows the original unedited image which has a white background. The image shows how after extracting the image of the person we can also apply a new background and make it look better. An example showing image foreground extraction using OpenCV contour detection technique. So, you can expect something like the following image.įigure 1. Not only that, we will also try to change the background of the resulting foreground to make things a little bit more interesting. We will see in detail how we can achieve image foreground extraction using OpenCV contour detection further into this article. Using contour detection, we can find the pixels surrounding the object that we want to extract and then proceed further. We can do this by using the contour detection technique. After that we can treat it as a foreground image and discard the rest of the things as background image. In simple terms, we need to find the area or pixels bounding the object of interest.

    easy contour python

    So, how are we going to do that without using the Grabcut algorithm? Using OpenCV Contour Detection for Image Foreground Extraction

    easy contour python

    After that, the Grabcut algorithm handles the rest. In Grabcut we provide a rectangular area where the object of interest might be present. You can find more about foreground extraction using Grabcut in this amazing post by Adrian Rosebrock.Īfter reading that article, I thought of doing the same, but without using Grabcut. Grabcut is one of the most popular methods when it comes to computer vision based image foreground extraction. But we can achieve this using pure computer vision techniques as well. Recent deep learning based image segmentation techniques have made this really easier. Using the method of foreground extraction, we try to extract any image or object that is of interest to us, and discard the rest of the background. A Bit of Background and Introductionįoreground extraction is a very popular task in the field of computer vision. We will use the OpenCV computer vision library along with the contour detection technique for this.

    #EASY CONTOUR PYTHON HOW TO#

    In this article, you will get to learn how to carry out image foreground extraction using OpenCV contour detection method.






    Easy contour python