#!/bin/python2 # Convert MNIST handwritten database to SVM-light format import util util.load_data() data = util.train_sample(0xFFFFFFFF) + util.test_sample(0xFFFFFFF) resolution_list = [4, 8, 16] lim_list = [200, 2000, 20000] for c_res in resolution_list: pr = [] e_in = [] e_out = [] for sz in lim_list: t_set = util.train_sample(sz) l = len(t_set) f = open(str(c_res) + str(sz) + "vectors.dat","w") for i in range(0, l): t_set[i] = (t_set[i][0], util.resize(t_set[i][1], c_res)) img = t_set[i] if img[0] == 1: f.write("-1 ") else: f.write("1 ") for k in range(0, len(img[1])): if (img[1][k] > 0):
exit() util.load_data() res_ein = [] res_eout = [] for c_res in resolution_list: pr = [] e_in = [] e_out = [] print "Image resolution: " + str(c_res) + "x" + str(c_res) for sz in lim_list: print " Sample size: " + str(sz) print " Trainnig..." t_set = util.train_sample(sz) l = len(t_set) for i in range(0, l): t_set[i] = (t_set[i][0], util.resize(t_set[i][1], c_res)) x = get_x(t_set) print " Testing..." e_i = test_x(x, t_set) t_set = util.test_sample(sz) l = len(t_set) for i in range(0, l): t_set[i] = (t_set[i][0], util.resize(t_set[i][1], c_res)) e_o = test_x(x, t_set) e_in.append(e_i) e_out.append(e_o)