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11 lines
1007 B
Plaintext
11 lines
1007 B
Plaintext
The code here prepares the training images and labels into a format that can be easilly used to train SVR and CCNF regressors.
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Just run "scripts/Prepare_data_wild_all.m" for data needed to train patch experts for in-the-wild experiments.(you have to have the relevant datasets, but they are all available online at http://ibug.doc.ic.ac.uk/resources/facial-point-annotations/)
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Run "scripts/Prepare_data_Multi_PIE_all.m" (you have to have the multi-pie dataset and labels)
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Run "scripts/Prepare_data_general_all.m" (you have to have both of the datasets, and you have to run "scripts/Prepare_data_wild_all.m" and scripts/Prepare_data_Multi_PIE_all.m" first.
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Run "scripts/Prepare_data_menpo_all.m" (you have to have the Menpo challenge training data - https://ibug.doc.ic.ac.uk/resources/2nd-facial-landmark-tracking-competition-menpo-ben/)
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PDM model used is trained on 2D landmark labels using Non-Rigid-Structure for motion (code can be found http://www.cl.cam.ac.uk/~tb346/res/ccnf/pdm_generation.zip) |