From 9054cf9b0c327a5077fd0793abe178f400da3315 Mon Sep 17 00:00:00 2001 From: tingchunw Date: Mon, 4 Dec 2017 16:52:46 -0800 Subject: first commit --- precompute_feature_maps.py | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100755 precompute_feature_maps.py (limited to 'precompute_feature_maps.py') diff --git a/precompute_feature_maps.py b/precompute_feature_maps.py new file mode 100755 index 0000000..a631b9c --- /dev/null +++ b/precompute_feature_maps.py @@ -0,0 +1,36 @@ +### Copyright (C) 2017 NVIDIA Corporation. All rights reserved. +### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode). +from options.train_options import TrainOptions +from data.data_loader import CreateDataLoader +from models.models import create_model +import numpy as np +import os, time +import util.util as util +from torch.autograd import Variable +import torch.nn as nn + +opt = TrainOptions().parse() +opt.nThreads = 1 +opt.batchSize = 1 +opt.serial_batches = True +opt.no_flip = True +opt.instance_feat = True + +name = 'features' +save_path = os.path.join(opt.checkpoints_dir, opt.name) + +############ Initialize ######### +data_loader = CreateDataLoader(opt) +dataset = data_loader.load_data() +dataset_size = len(data_loader) +model = create_model(opt) +util.mkdirs(os.path.join(opt.dataroot, opt.phase + '_feat')) + +######## Save precomputed feature maps for 1024p training ####### +for i, data in enumerate(dataset): + print('%d / %d images' % (i+1, dataset_size)) + feat_map = model.module.netE.forward(Variable(data['image'].cuda(), volatile=True), data['inst'].cuda()) + feat_map = nn.Upsample(scale_factor=2, mode='nearest')(feat_map) + image_numpy = util.tensor2im(feat_map.data[0]) + save_path = data['path'][0].replace('/train_label/', '/train_feat/') + util.save_image(image_numpy, save_path) \ No newline at end of file -- cgit v1.2.3-70-g09d2