However, if you intend on using Matplotlib, the plt.imshow function assumes the image is in RGB order. This works fine when using the cv2.imshow function.
In the Python bindings of OpenCV, images are represented as NumPy arrays in BGR order. Skeleton = imutils.skeletonize(gray, size=(3, 3)) Gray = cv2.cvtColor(logo, cv2.COLOR_BGR2GRAY) An optional argument, structuring, can be used to control the structuring element - it defaults to cv2.MORPH_RECT, but can be any valid structuring element. The first argument, size is the size of the structuring element kernel. OpenCV does not provide a function to explicitly construct the skeleton, but does provide the morphological and binary functions to do so.įor convenience, the skeletonize function of imutils can be used to construct the topological skeleton of the image. Skeletonization is the process of constructing the "topological skeleton" of an object in an image, where the object is presumed to be white on a black background. Resized = imutils.resize(workspace, width=width)Ĭv2.imshow("Width=%dpx" % (width), resized) Output: Example: # loop over varying widths to resize the image to
This resize function of imutils maintains the aspect ratio and provides the keyword arguments width and height so the image can be resized to the intended width/height while (1) maintaining aspect ratio and (2) ensuring the dimensions of the image do not have to be explicitly computed by the developer.Īnother optional keyword argument, inter, can be used to specify interpolation method as well. However, special care needs to be taken to ensure that the aspect ratio is maintained. Resizing an image in OpenCV is accomplished by calling the cv2.resize function. Rotated = imutils.rotate(bridge, angle=angle)Ĭv2.imshow("Angle=%d" % (angle), rotated) Output: Example: # loop over the angles to rotate the image The rotate function in imutils helps resolve this problem.
#Resize image opencv code#
These calculation calls can quickly add up and make your code bulky and less readable. Further care has to be taken to supply the (x, y)-coordinate of the point the image is to be rotated about. Rotating an image in OpenCV is accomplished by making a call to cv2.getRotationMatrix2D and cv2.warpAffine. Translated = anslate(workspace, 25, -75) Output:
Example: # translate the image x=25 pixels to the right and y=75 pixels up Instead of manually constructing the translation matrix M and calling cv2.warpAffine, you can simply make a call to the translate function of imutils. To translate an image in OpenCV you would need to supply the (x, y)-shift, denoted as (t x, t y) to construct the translation matrix M:Īnd from there, you would need to apply the cv2.warpAffine function. Translation is the shifting of an image in either the x or y direction. The contourArea function could therefore be accessed via: cv2.contourArea Translation Imutils.find_function("contour") Output: 1. Let's find all function names that contain the text contour: import imutils The find_function method allows you to quickly search function names across modules (and optionally sub-modules) to find the function you are looking for. OpenCV can be a big, hard to navigate library, especially if you are just getting started learning computer vision and image processing.
#Resize image opencv install#
Provided you already have NumPy, SciPy, Matplotlib, and OpenCV already installed, the imutils package is completely pip-installable: $ pip install imutils Finding function OpenCV functions by name
#Resize image opencv series#
A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and both Python 2.7 and Python 3.įor more information, along with a detailed code review check out the following posts on the blog:
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