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()
