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BM2g.py
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BM2g.py
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# import matlab.engine
import argparse
import torch
from torch.autograd import Variable
import numpy as np
import time, math, glob
# import scipy.io as sio
from skimage import color,io
from torchvision import transforms
from PIL import Image
import os
from tqdm import tqdm
import cv2
def PSNR(pred, gt, shave_border=0):
height, width = pred.shape[:2]
pred = pred[shave_border:height - shave_border, shave_border:width - shave_border]
gt = gt[shave_border:height - shave_border, shave_border:width - shave_border]
imdff = pred - gt
rmse = math.sqrt(np.mean(imdff ** 2))
if rmse == 0:
return 100
return 20 * math.log10(255.0 / rmse)
# opt = parser.parse_args()
cuda = True
if cuda and not torch.cuda.is_available():
raise Exception("No GPU found, please run without --cuda")
def valid(model,valid_clear,valid_moire,name):
ims = os.listdir(valid_clear)
psnrs = []
for im in tqdm(ims[:]):
clear = im
moire = clear
im_clear = Image.open(valid_clear+clear)
im_moire = Image.open(valid_moire+moire)
use_Y = False
if use_Y:
im_clear = np.array(im_clear)
im_moire = np.array(im_moire)
cy = color.rgb2ycbcr(im_clear)[:,:,0]
my = color.rgb2ycbcr(im_moire)[:,:,0]
im_clear = Image.fromarray(cy)
im_moire = Image.fromarray(my)
if name == None:
name_append = 'tmp.bmp'
else:
name_append= os.path.join(name,moire)
psnr = demoire(model,im_clear,im_moire,use_Y,name)
psnrs.append(psnr)
return psnrs
def demoire(model,im_clear,im_moire,use_Y,name):
if name == None:
name = 'tmp.bmp'
im_array = np.array(im_moire)
TS = transforms.Compose([transforms.ToTensor()])
if use_Y:
im_input = TS(im_moire).view(-1,1,im_array.shape[0],im_array.shape[1])
else:
im_input = TS(im_moire).view(-1,3,im_array.shape[0],im_array.shape[1])
if cuda:
model = model.cuda()
im_input = im_input.cuda()
else:
model = model.cpu()
start_time = time.time()
# dm,clear = model(im_input)
with torch.no_grad():
clears = model(im_input)
clear = clears[0]
elapsed_time = time.time() - start_time
clear = clear.cpu()
im_h = clear.data[0].numpy().astype(np.float32)
im_h = im_h*255.
im_h = np.clip(im_h, 0., 255.)
im_h = im_h.transpose(1,2,0)
if use_Y:
im_h = im_h[:,:,0]
io.imsave('./'+name,im_h/255.)
nim = io.imread('./'+name)
psnr = PSNR(nim,np.array(im_clear))
return psnr