The beauty of Python Library named Open Cv

The beauty of OpenCV Vol-3. In this final article, i would like to discuss some advance operation which we can perform using OpenCV. Here in this article, we are going to discuss Grabcut foreground extraction, Feature matching, Haar cascade object, MOG background. In my last two articles, i have discussed some basic operations which can be done by using OpenCV like reading an image, loading video source, Drawing and writing on images, thresholding, Canny Edge Detection etc, these were just basic operations which are basically in order to understand how things would look like when you are doing computer vision projects likewise, how does your own model would print the type of object at on a single frame, how do the bounding boxes print on a frame, how do we show the frames while running our model, how do we test our results on a video frame and many more. If you don't get this, i will write a blog in the future on how the computer vision projects work and what are the backend...

The beauty of OpenCV Vol-2: In this article, i would like to talk about some more operations which we can perform using OpenCV. In my last article or the part-1 of this article, I've talked about the various operations which we can perform on images using OpenCV. Now in the second part of the article, i would like to share some more on OpenCV like Thresholding, Canny edge detection, Morphological transformations, Blurring and Smoothing and many more. So without wasting any time, let's get started. ***important thing->  Here's the link of the first part of this article,  https://tdbtech.blogspot.com/2019/02/opencv-part-1-blog.html Color Filtering in OpenCV: Here, we are going to cover some color filtering operations using OpenCV, revisiting bitwise operation, and we will also specify a certain color in order to just show it. Have you guys wondered how the area of green screen removes in the VFX or Superhero based movies?. Just like that, we will filter ...

The beauty of OpenCV: In this article, i have written about the basic but useful operations we can do with OpenCV. OpenCV is a major tool which we can use for major deep learning algorithms. This is part one of the whole topic, for the next one you can see the link at the end. In the part-1, i have discussed some operations on images. In the next part, i have discussed video source operation like canny edge detection, smoothing and blurring, morphological transformation and many more. So without wasting any time let's get started * **important thing:  I have used the jupyter notebook for deployment, if you wish to use your IDE then go on otherwise i will also write one more article on how to install Jupyter notebook using anaconda Introduction: OpenCV (Open source Computer Vision) is a Python programming function mainly aimed at real-time computer vision. This library majorly works on enabling computers to see, visualize and gives the output as the same human eye does. O...