from buildlib import preprocess, buildshape, config #from buildlib.buildpatch_mosse import build_patches from buildlib.buildpatch import build_patches from buildlib.buildscore import getScoring buildPatches = True buildScoring = True cleanUp = True # create some needed folders for folder in ["cropped", "pcropped", "svmImages"]: if not os.path.exists(os.path.join(config.data_folder, folder)): os.makedirs(os.path.join(config.data_folder, folder)) # preprocess data data_pca, data_patches, meanshape, cropsize = preprocess.preprocess(config.annotations, mirror = True) #dp = {'data_pca' : data_pca, 'data_patches' : data_patches, 'meanshape' : meanshape, 'cropsize' : cropsize} #fi = open("out.data", "w") #pickle.dump(dp, fi) #fi.close() #fi = open("out.data", "r") #data = pickle.load(fi) #fi.close() #data_pca = data['data_pca'] #data_patches = data['data_patches'] #meanshape = data['meanshape'] #cropsize = data['cropsize'] # build shape model
from buildlib import preprocess, buildshape, config #from buildlib.buildpatch_mosse import build_patches from buildlib.buildpatch import build_patches from buildlib.buildscore import getScoring buildPatches = True buildScoring = True cleanUp = True # create some needed folders for folder in ["cropped", "pcropped", "svmImages"]: if not os.path.exists(os.path.join(config.data_folder, folder)): os.makedirs(os.path.join(config.data_folder, folder)) # preprocess data data_pca, data_patches, meanshape, cropsize = preprocess.preprocess( config.annotations, mirror=True) #dp = {'data_pca' : data_pca, 'data_patches' : data_patches, 'meanshape' : meanshape, 'cropsize' : cropsize} #fi = open("out.data", "w") #pickle.dump(dp, fi) #fi.close() #fi = open("out.data", "r") #data = pickle.load(fi) #fi.close() #data_pca = data['data_pca'] #data_patches = data['data_patches'] #meanshape = data['meanshape'] #cropsize = data['cropsize'] # build shape model