I'm trying to replicate the results of Fully Convolutional Network (FCN) for Semantic Segmentation using TensorFlow.
I'm stuck on feeding training images into the computation graph. The fully convolutional network used VOC PASCAL dataset for training. However, the training images in the dataset are of varied sizes.
I just want to ask if they preprocessed the training images to make them have the same size and how they preprocessed the images. If not, did they just feed batches of images of different sizes into the FCN? Is it possible to feed images of different sizes in one batch into a computation graph in TensorFlow? Is it possible to do that using queue input rather than placeholder?
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