I have two images, both with alpha channels. I want to put one image over the other, resulting in a new image with an alpha channel, just as would occur if they were rendered in layers. I would like to do this with the Python Imaging Library, but recommendations in other systems would be fantastic, even the raw math would be a boon; I could use NumPy.
I’m trying to use OpenCV 2.1 to combine two images into one, with the two images placed adjacent to each other. In Python, I’m doing:
I have a set of points that make a shape (closed polyline). Now I want to copy/crop all pixels from some image inside this shape, leaving the rest black/transparent. How do I do this?
I’m using zero padding around my image and convolution kernel, converting them to the Fourier domain, and inverting them back to get the convolved image, see code below. The result, however, is wrong. I was expecting a blurred image, but the output is four shifted quarters. Why is the output wrong, and how can I fix the code?
I am using python-tesseract to extract words from an image. This is a python wrapper for tesseract which is an OCR code.
hi I am building a image classifier for one-class classification in which i’ve used autoencoder while running this model I am getting this error by this line (autoencoder_model.fit) (ValueError: Error when checking target: expected model_2 to have shape (None, 252, 252, 1) but got array with shape (300, 128, 128, 3).)
How do you convert a grayscale OpenCV image to black and white? I see a similar question has already been asked, but I’m using OpenCV 2.3, and the proposed solution no longer seems to work.
minAreaRect in OpenCV returns a rotated rectangle. How do I crop this part of the image which is inside the rectangle?