![]() ![]() linspace ( 0, 360, 360 * smooth ) for i in angles : a = i * np. shape if len ( shape ) = 3 : row, col, channels = shape else : row, col = shape channels = 1 angles = np. array ( color ) if type ( img ) != type ( None ): shape = img. Provide numpy array instead." ) ix = center + rad angles = 360 cvalue = np. """ if type ( img ) = None : raise ValueError ( "Image can not be None. Smooth: how smooth should our circle be?(smooth * 360 angles in 0 to 360) Enough of this theory, let’s write that in code.Īll the stories given above are already found in the polar form.ĭef circle ( img = None, center = ( 0, 0 ), rad = 10, border = 4, color =, smooth = 2 ): """Ī method to create a circle on a give image.īorder: border of the circle, if -ve, circle is filled ![]() Hence we ignore all (x, y) values that lie other than the first quadrant. Hence, the coordinate value for p1 will be:Īnd on the image plane, the coordinate starts from (0, 0) and we don’t have a -ve quadrant. And to find the x-coordinate of p3 we can solve it.Īnd in our case, when the circle is not in the center then our (x, y) coordinate or p1 will be (h, k) far from the plane’s center. then the x coordinate of p1 will be equal to the x coordinate of p3. We can do that by thinking that c is the origin. The below figure shows a zoomed version of that situation.īut what we need is the coordinate values of p1. At that time we can apply Pythagoras’ theorem. But when the points p1 and p2 are so near that the distance between them is nearly zero (or the limit tends to 0) then the point p3 will be at p2. Here we know the length of 2 lines but not the line p1p3. Additionally, p3 is perpendicular to the line joining p2 and the center. Circle’s center is on (h, k) its radius is r, and there are 2 points on circumference p1, p2, and the third point is drawn on the radius line joining p2 and center. Let’s take an example of the above circle on the 2d plane. Find the new point on the circumference and make that point’s color on the circle color if the point is on the first quadrant.Find the distance between two points on the circumference by Pythagoras’ theorem.Convert angle to radian from degree (NumPy geometric functions take radian).Prepare smoothness * 360 angles for the circle (of course 0 to 360). ![]() Read an input image, get a radius for a circle, get a center point, get a border, get a smoothness value and get a color value for it.I will be using the concept of polar form. Here I will be using the simple concept of drawing a circle. So if we zoom the shapes we start to see the pixels crystal clear. Computer Graphics doesn’t care about what it needs is a number. A circle in the simple term can be thought of as a shape where infinite points are present and the distance between two consecutive points is infinitesimally small and points are arranged at an angle where consecutive points will be near 0 to 360 angle. Now onto the first shape on Drawing Simple Geometrical Shapes on Python.ĭoes everyone know what a circle is but only a few care how it originated? Thanks to Euclid and his contribution to modern Mathematics. # lets read our new image that we are going to use for drawing simple shape read_image ( "./cb.jpg", mode = 0 ) cv = ip. readmode = " ) return cimg ip = ImageProcessing () img = ip. Using primary-grade mathematics, I will start drawing simple geometrical shapes on python and compare them with OpenCV’s own methods.Ĭlass ImageProcessing : def _init_ ( self ): self.Writing an Image Processing Class from Scratch on Python.So it will be helpful to view that one also. The method I am including here will be added to the previous Image Processing Class (which is also given below) I have used to do Convolution and Colorspace changes. And the author also introduced the awesome book The Housekeeper and the Professor. Author really has a great way of describing the mathematical terms and I have learned a lot of concepts on Mathematics from there. In fact I am going to use some simple geometrical concepts to draw these basic shapes using only NumPy and Matplotlib.Īlso, I have to mention the awesome book named The Journey of X: A Guided Tour of Mathematics by Steven Strogatz. ![]() I am highly inspired by the book named Image Operators: Image Processing in Python by Jason M. Now is the time to start drawing simple geometrical shapes on python like circles, rectangles, ellipses and get the flashback of childhood. Last time I did Convolution operations from Scratch and RGB to GrayScale conversion, etc. Now in this series of tasks, I am going to tackle some of the interesting image processing concepts from scratch using Python and then will compare them with the popular OpenCV framework. Drawing Simple Geometrical Shapes on Python Using NumPy and Visualize Itĭrawing Simple Geometrical Shapes on Python from scratch, have you tried it? ![]()
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