def get_features(fnames, featfunc, kernel_type = DEFAULT_SIMFUNC, simfunc = DEFAULT_SIMFUNC, info_str = 'the', ): # -------------------------------------------------------------------------- # -- init # load first vector to get dimensionality fvector0 = get_fvector(fnames[0], featfunc, kernel_type, simfunc=simfunc) if kernel_type == "exp_mu_da": # hack for GB with 204 dims fvector0 = fvector0.reshape(-1, 204) else: fvector0 = fvector0.ravel() featshape = fvector0.shape featsize = fvector0.size # -- helper function # set up progress bar def load_features(x_fnames, info_str): print "-"*80 print "Loading %s data ..." % info_str pbar = ProgressBar(widgets=widgets, maxval=len(x_fnames)) pbar.start() x_features = sp.empty((len(x_fnames),) + featshape, dtype='float32') for i, one_or_two_fnames in enumerate(x_fnames): fvector = get_fvector(one_or_two_fnames, featfunc, kernel_type, simfunc=simfunc) fvector = fvector.reshape(fvector0.shape) x_features[i] = fvector pbar.update(i+1) pbar.finish() print "-"*80 return x_features # -- load features from filenames try: features = load_features(fnames, info_str=info_str) except OverwriteError, err: print err
def load_features(x_fnames, info_str): print "-"*80 print "Loading %s data ..." % info_str pbar = ProgressBar(widgets=widgets, maxval=len(x_fnames)) pbar.start() x_features = sp.empty((len(x_fnames),) + featshape, dtype='float32') for i, one_or_two_fnames in enumerate(x_fnames): fvector = get_fvector(one_or_two_fnames, featfunc, kernel_type, simfunc=simfunc) fvector = fvector.reshape(fvector0.shape) x_features[i] = fvector pbar.update(i+1) pbar.finish() print "-"*80 return x_features