From edf910b1c1d02020b31782ab4c3b6ebf9af8c323 Mon Sep 17 00:00:00 2001 From: tingchunw Date: Tue, 30 Jan 2018 01:30:18 +0000 Subject: change dataset naming convention and add ui model --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'README.md') diff --git a/README.md b/README.md index c6ff340..80b425a 100755 --- a/README.md +++ b/README.md @@ -109,7 +109,7 @@ If only GPUs with 12G memory are available, please use the 12G script (`bash ./s ### Training with your own dataset - If you want to train with your own dataset, please generate label maps which are one-channel whose pixel values correspond to the object labels (i.e. 0,1,...,N-1, where N is the number of labels). This is because we need to generate one-hot vectors from the label maps. Please also specity `--label_nc N` during both training and testing. -- If your input is not a label map, please just specify `--label_nc 0` which will directly use the RGB colors as input. +- If your input is not a label map, please just specify `--label_nc 0` which will directly use the RGB colors as input. The folders should then be named `train_A`, `train_B` instead of `train_label`, `train_img`, where the goal is to translate images from A to B. - If you don't have instance maps or don't want to use them, please specify `--no_instance`. - The default setting for preprocessing is `scale_width`, which will scale the width of all training images to `opt.loadSize` (1024) while keeping the aspect ratio. If you want a different setting, please change it by using the `--resize_or_crop` option. For example, `scale_width_and_crop` first resizes the image to have width `opt.loadSize` and then does random cropping of size `(opt.fineSize, opt.fineSize)`. `crop` skips the resizing step and only performs random cropping. If you don't want any preprocessing, please specify `none`, which will do nothing other than making sure the image is divisible by 32. -- cgit v1.2.3-70-g09d2