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