文件名称:CGfft
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介绍说明--下载内容均来自于网络,请自行研究使用
Within each folder, first run gendata.m (in Matlab) to generate the appropriate data files. Then, run gclabel.cpp to estimate the shadow map and normal field. Finally, run genheight.m in Matlab to integrate the normal field. The light source directions and some other parameters are hard coded in gclabel.cpp.
For other datasets of your own, you can generate the input files and the graph cuts optimization code similar to the examples shown above.
For other datasets of your own, you can generate the input files and the graph cuts optimization code similar to the examples shown above.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
padMatrix.m
padPatch.m
cgLearnFFT.m
compute_h_noLoop2.m
normalize_h.m
padPatch.m
cgLearnFFT.m
compute_h_noLoop2.m
normalize_h.m