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restore_complete_3Dimage.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 12 22:51:06 2018
Restroing the large scale image from sub-blocks which is
reconstructed from the 3d-VDSR.
@author: wdd
@Copyright Notice:Please contact [email protected] before you reprint this program
"""
import utils
import numpy as np
import argparse
import os
from PIL import Image
parser = argparse.ArgumentParser(description="restroing the large scale image")
parser.add_argument("--oripath", type=str, default='test/testset/test1',help="path to original image ")
parser.add_argument('--interpath',type=str,default='saved_crop_imgs_1_low',help='path to interpolation image ')
parser.add_argument('--imagesize',type=str,default=400,help='size of reconstructed image')
parser.add_argument('--block_size',type=int,default=100,help='reconstrucion size per time')
parser.add_argument("--hei", type=int, default=2580, help="h")
parser.add_argument("--wid", type=int, default=2580, help="w")
parser.add_argument("--dep", type=int, default=40, help="d")
parser.add_argument('--memo',type=str,default='wdd')
opt=parser.parse_args()
# print(opt.interpath, opt.oripath)
#dataset_interp=utils.read_imagecollection('/home/wdd/pytorch-vdsr-3d/testset/x2interp/test1x2')
num,h,w=(opt.hei,opt.wid,opt.dep)
batch_generate_size=opt.block_size
reconstruction_output=np.zeros((num,h,w))
default_path='result/3D_VDSR_'#此处注意需要修改
sub_name=opt.memo
#utils.read_imagecollection('/home/wdd/pytorch-vdsr-3d/3D_VDSR_001')
for count_d in range((num//batch_generate_size)):
for count_h in range((h//batch_generate_size)):
for count_w in range((w//batch_generate_size)):
pixel_start_d = count_d*batch_generate_size
pixel_end_d = (count_d+1)*batch_generate_size
pixel_start_h = count_h*batch_generate_size
pixel_end_h = (count_h+1)*batch_generate_size
pixel_start_w = count_w*batch_generate_size
pixel_end_w = (count_w+1)*batch_generate_size
sub_block = utils.read_imagecollection(file_path=default_path+str(count_d)+str(count_h)+str(count_w), image_format='bmp')
# os.remove('3D_VDSR_'+str(count_d)+str(count_h)+str(count_w))
#print ('current path is:'+'3D_VDSR_'+str(count_d)+str(count_h)+str(count_w),'shape of sub_block is:',sub_block.shape)
reconstruction_output[pixel_start_d:pixel_end_d, pixel_start_h:pixel_end_h, pixel_start_w:pixel_end_w] = sub_block
dataset_ori = utils.read_imagecollection(opt.oripath)
dataset_interp = utils.read_imagecollection(opt.interpath, image_format='bmp')#读取interp path 路径,文件后缀要注意bmp或是jpg！！
#print ('======>Read original image from : ',opt.oripath,' Read low resolution images from : ',opt.interpath)
#print ('PSNR of interp:',utils.PSNR(dataset_interp[:reconstruction_size,:reconstruction_size,:reconstruction_size],dataset_ori[:reconstruction_size,:reconstruction_size,:reconstruction_size]))
# print ('PSNR of reconstructor:',utils.PSNR(reconstruction_output,dataset_ori[:reconstruction_size,:reconstruction_size,:reconstruction_size]))
print (utils.PSNR(reconstruction_output,dataset_ori[:num,:h,:w]))
# Image.fromarray(reconstruction_output[..., 100]).show()
# Image.fromarray(dataset_interp[..., 100]).show()
utils.generate_2Dimage(save_mode=os.path.join(default_path, sub_name), array_like=reconstruction_output)