1. A computer-implemented method for synthesizing a portrait sketch from a photo, comprising: dividing the photo into a set of photo patches; forming, from a set of training photos and a set of training sketches, a MRF network model for each of the photo patch, wherein the MRF network model includes: a shape prior of the portrait sketch, first matching information between each of the photo patches and a set of training photo patches pre-divided from a set of training photos; second matching information between each of the photo patches and a set of training sketch patches pre-divided from a set of training sketches; optimizing the MRF network model to select, from the set of training sketches, a set of ly matched training sketch patches for each of the photo patches; and synthesizing the portrait sketch from the selected training sketch patches, wherein the shape prior is determined through the following steps: detecting the predefined landmarks on the training sketches and the photo; determining the shape prior via a kernel density estimation if a landmark f falls into a patch i on the photo: E P ⁢ ⁢ i ⁡ ( y i ) = λ P ⁢ ln [ 1 2 ⁢ π ⁢ N i ⁢ ∑ k = 1 N i ⁢ exp ( - ( β ⁡ ( y i s ) - β k , f ) 2 h f 2 ) ] where N t is the number of training sketches, β(y i s ) is a statistic on the sketch patch y i s ; β k,f is a statistic on a sketch patch centered at the landmark f in a sketch image k; h f is a bandwidth of the landmark f; and λ P is a metric scale to normalize the prior shape.