besterror = [0, float('inf'), float('inf')] # nepoch, medX, medQ if opt.model == 'posenet': testepochs = numpy.arange(1, 2000 + 1) else: testepochs = numpy.arange(1, 2000 + 1) testfile = open(os.path.join(results_dir, 'test_median.txt'), 'a') testfile.write('epoch medX medQ\n') testfile.write('==================\n') model = create_model(opt) visualizer = Visualizer(opt) for testepoch in testepochs: model.load_network(model.netG, 'G', testepoch) visualizer.change_log_path(testepoch) # test # err_pos = [] # err_ori = [] err = [] print("epoch: " + str(testepoch)) for i, data in enumerate(dataset): model.set_input(data) model.test() img_path = model.get_image_paths()[0] print('\t%04d/%04d: process image... %s' % (i, len(dataset), img_path), end='\r') image_path = img_path.split('/')[-2] + '/' + img_path.split('/')[-1] pose = model.get_current_pose() visualizer.save_estimated_pose(image_path, pose) err_p, err_o = model.get_current_errors()
os.makedirs(results_dir) testepochs = ['latest'] besterror = [0, float('inf'), float('inf')] # nepoch, medX, medQ testepochs = numpy.arange(150, 501, 5) testfile = open(os.path.join(results_dir, 'test_median.txt'), 'a') testfile.write('epoch medX medQ\n') testfile.write('==================\n') model = create_model(opt) visualizer = Visualizer(opt) for testepoch in testepochs: opt.which_epoch = testepoch model.load_network(model.netG, 'G', opt.which_epoch) visualizer.change_log_path(opt.which_epoch) # test # err_pos = [] # err_ori = [] err = [] print("epoch: " + str(opt.which_epoch)) for i, data in enumerate(dataset): model.set_input(data) model.test() img_path = model.get_image_paths()[0] print('\t%04d/%04d: process image... %s' % (i, len(dataset), img_path), end='\r') image_path = img_path.split('/')[-2] + '/' + img_path.split('/')[-1] pose = model.get_current_pose() visualizer.save_estimated_pose(image_path, pose) err_p, err_o = model.get_current_errors()