If you need help configuring your development environment for OpenCV, I highly recommend that you read my pip install OpenCV guide - it will have you up and running in a matter of minutes. Luckily, OpenCV is pip-installable: $ pip install opencv-contrib-python To follow along with this guide, you need to have the OpenCV library installed on your system. We will see a complete example of defining our image translation matrix and applying the cv2.warpAffine function later in this guide. Now, if we want to shift an image 7 pixels to the left and 23 pixels up, our translation matrix would look like the following: M = np.float32([Īnd as a final example, let’s suppose we want to translate our image 30 pixels to the left and 12 pixels down: M = np.float32([Īs you can see, defining our affine transformation matrix for image translation is quite easy!Īnd once our transformation matrix is defined, we can simply perform the image translation using the cv2.warpAffine function, like so: shifted = cv2.warpAffine(image, M, (image.shape, image.shape)) Our translation matrix would look like the following (implemented as a NumPy array): M = np.float32([
Positive values for shifts the image to the right.Negative values for the value will shift the image to the left.Figure 1: To translate an image with OpenCV, we must first construct an affine transformation matrix.įor the purposes of translation, all we care about are the and values:
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