I’m working on a project with some friends on a computer vision model where we have an image dataset and we transform the images into black and white and keep the target or ground truth as the original color image. In essence, it’s an image colorization model where we learn parameters to colorize black and white images.
I’ve seen several tutorials regarding ImageFolder and DataLoader but the main problem is that although DataLoader loads the images, the Y_train part (that is, the target) are labels. Meaning that the name of the folder in which the dataset is stored (say, for example, ‘/Dogs/’) will be the target label. However, in my model, the final output should also be an image only.
Hence I want to know what I can do to take the image dataset and make a black and white copy of each image to keep as input for the CNN later on and have the original color image as the final target output image.
For reference, we are using the ~500 MB Places2 validation set as our main data.