We have introduced how to detect object using python opencv. However, it only can detect one object each time from an image. In this tutorial, we will introduce how to detect multiple objects from an image.
We have introduced six object detection algorithms in opencv. In this tutorial, we will use these six algorithms to detect object from an image.
In this tutorial, we will introduce how to replace a part of big image using an small image or numpy array, which is very useful when you plan to recognize objects from images.
In this tutorial, we will introduce how to replace some value in a big numpy array using a small numpy array or matrix, which is very useful when you are processing images in python.
TensorFlow tf.fill() function allows us to create a tensor with a scalar value filled. In this tutorial, we will introduce how to use it in tensorflow application.
We can use wordpress AMP plugin to create amp pages for our sites. However, this plugin can not allow us to add google adsense amp code. In this tutorial, we will tell you how to do.
In python opencv, we can use cv2.matchTemplate() to match images. Here are six template matching algorithms we can use. In this tutorial, we will discuss these algorithms.
OpenCV cv2.minMaxLoc() is often used to find the maximum and minimum value in a numpy array. In this tutorial, we will use an example to show you how to use this function.
OpenCV is a powerful tool to process images. In this tutorial, we will introduce how to read an image to numpy ndarray.
When you use your finger to touch the screen of an android phone. What is the coordinate of the position you have touched? In this tutorial, we will use python and adb to get the touch coordinate.