visualization of the generated image.

[pzz2011]

I used the modified code below to generate the ouput image of the model, but got images filled by noise. I checked the code a lot of time but didn't find any problem. So can u help me?

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)

def colorize(y, ycbcr):
    img = np.zeros((y.shape[0], y.shape[1], 3))
    img[:,:,0] = y
    img[:,:,1] = ycbcr[:,:,1]
    img[:,:,2] = ycbcr[:,:,2]
    img = Image.fromarray(img, "YCbCr").convert("RGB")
    return img

for image_name in image_list:
    print("Processing ", image_name)
    im_gt_y = sio.loadmat(image_name)['im_gt_y']
    im_b_y = sio.loadmat(image_name)['im_b_y']
    im_l_y = sio.loadmat(image_name)['im_l_y']
    im_b_ycbcr = sio.loadmat(image_name)['im_b_ycbcr']

    im_b_ycbcr = im_b_ycbcr*255.
    im_b_ycbcr[im_b_ycbcr<0] = 0
    im_b_ycbcr[im_b_ycbcr>255.] = 255.

    im_gt_y = im_gt_y.astype(float)
    im_b_y = im_b_y.astype(float)
    im_l_y = im_l_y.astype(float)

    psnr_bicubic = PSNR(im_gt_y, im_b_y,shave_border=opt.scale)
    avg_psnr_bicubic += psnr_bicubic

    im_input = im_l_y/255.

    im_input = Variable(torch.from_numpy(im_input).float()).view(1, -1, im_input.shape[0], im_input.shape[1])

    if cuda:
        model = model.cuda()
        im_input = im_input.cuda()
    else:
        model = model.cpu()

   start_time = time.time()
    HR_2x, HR_4x = model(im_input)
    elapsed_time = time.time() - start_time
    avg_elapsed_time += elapsed_time

    HR_4x = HR_4x.cpu()

    im_h_y = HR_4x.data[0].numpy().astype(np.float32)

    im_h_y = im_h_y*255.
    im_h_y[im_h_y<0] = 0
    im_h_y[im_h_y>255.] = 255.
    im_h_y = im_h_y[0,:,:]


    psnr_predicted = PSNR(im_gt_y, im_h_y,shave_border=opt.scale)
    avg_psnr_predicted += psnr_predicted

    im_h = colorize(im_h_y, im_b_ycbcr)

    im_h.save("store path") ==========>   save the np array as array

[twtygqyy]

The type of output should be np.uint8

[pzz2011]

thanks.

[zjb0829]

@pzz2011 Excuse me, did you generate the picture successfully