def generator(path):
# for j in range(50):
for i in range(1000):
# receive input_a
# input_a = utils.load_image(path + 'chair_rotation_%.2d/chair_rotation_%.2d.png' % (j, j))
input_a = utils.load_image('../../chair.png')
input_a = input_a[:, :, :3]
input_a = input_a.reshape((-1))
input_a = np.tile(input_a, 10)
input_a = input_a.reshape((10, 224, 224, 3))
# receive input_b
# input_b = np.loadtxt(path + 'chair_rotation_%.2d/rendering_metadata_rotation_new_%.2d.txt' % (j, j))
input_b = np.loadtxt(path + 'rendering_metadata_rotation_00.txt')
input_b = input_b[(i * 10):(i * 10 + 10), :]
# receive input_c
# input_c = utils.load_image_com(path + 'chair_rotation_%.2d/chair_rotation_%.2d_trans_%.2d.png' % (j, j, i*8))[:,:,:3]
input_c = utils.load_image_com(path +
'chair_rotation_00_only_%.2d.png' %
(i * 10))[:, :, :3]
for k in range(1, 10, 1):
# input_c = np.concatenate((input_c, utils.load_image_com(path + 'chair_rotation_%.2d/chair_rotation_%.2d_trans_%.2d.png' % (j, j, (i*8 + k)))[:,:,:3]), axis = 0)
input_c = np.concatenate(
(input_c,
utils.load_image_com(path +
'chair_rotation_00_only_%.2d.png' %
(i * 10 + k))[:, :, :3]),
axis=0)
input_c = np.reshape(input_c, (10, 224, 224, 3))
# generate data
yield (input_a, input_b, input_c)
import utils
import numpy as np
from tqdm import tqdm
path = '../../chair_only_rotation_database/chair_rotation_00/'
input_Sym = utils.load_image_com(path + 'chair_rotation_00_only_00.png')[:,:,:3]
for i in tqdm(range(1,1000)):
tmp_image = utils.load_image_com(path + 'chair_rotation_00_only_%.2d.png' % i)[:,:,:3]
input_Sym = np.concatenate((input_Sym,tmp_image),axis = -1)
np.save('/home/gaopeng/dict_image.npy' , input_Sym)
input_Semantic: input_b,
output_img: input_c
})
writer.add_summary(summary, epoch)
# save 5th epoch weight
if ((epoch + 1) % 50 == 0):
saver.save(sess,
checkpoint_dir_1 + 'model_ckpt',
global_step=epoch + 1)
# output image for testing
for i in range(50):
# input_image_test
# input_test = utils.load_image('../../' + 'chair.png')
# input_test = input_test[:,:,:3]
input_test = utils.load_image_com(
'/home/gaopeng/chair_rotation_plus_trans_test_true/chair_source/chair_rotation_source_%.2d.png'
% i)[:, :, :3]
input_test = np.reshape(input_test, (1, 224, 224, 3))
# input_test = input_test.reshape((-1))
# input_test = np.tile(input_test, 10)
# input_test = input_test.reshape((1, 224, 224, 3))
# input_Semantic_test
input_Semantic_test = np.loadtxt(
'/home/gaopeng/chair_rotation_plus_trans_test_true/rendering_destination_rotation_angle.txt'
)
# input_Semantic_test = np.loadtxt(path + 'rendering_metadata_rotation_00.txt')
# input_Semantic_test = input_Semantic_test.reshape((1,6))
input_Semantic_test = input_Semantic_test[(i * 1):(i * 1 + 1), :]
# input_c_test
input_c_test = utils.load_image_com(
'../../chair_rotation_plus_trans_test_true/chair_rotation_true/' +
from pathlib import Path
import os
import utils
import numpy as np
pathlist = Path('../../3D-R2N2/ShapeNet/ShapeNetRendering/').glob('**/*00.png')
print(len(list(pathlist)))
for path in pathlist:
input_a = utils.load_image_com(str(path))[:, :, :3]
print(input_a.shape)
break
