LapSRN-tensorflow:Tensorflow实施“快速,准确的超高分辨率的深拉普拉斯金字塔网络”的论文

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Tensorflow实施论文“快速,准确的超高分辨率的深拉普拉斯金字塔网络”(CVPR 2017) 这是使用TensorLayer的Tensorflow实现。 原始论文和使用MatConNet的实现可以在他们的上找到。 环境 使用python 3.6和cuda 8.0对实现进行了测试。 下载资料库: $ git clone https://github.com/zjuela/LapSRN-tensorflow.git 火车模型 在config.py文件中指定数据集路径并运行: $ python main.py 使用挑战数据集对预训练模型进行训练。 测试 使用您的测试图像运行: $ python main.py -m test -f TESTIMAGE 结果可以在文件夹./samples/中找到

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