Pytorch 使用opnecv读入图像由HWC转为BCHW格式方式

def __getitem__(self, idx):
    '''Load image.
    Args:
     idx: (int) image index.
    img_org = Image.open(self.root_src + 'reference_cutBlock' + fname_org)
    Returns:
     img: (tensor) image tensor.
     loc_targets: (tensor) location targets.
     cls_targets: (tensor) class label targets.
    '''
    # Load image
    fname_org = self.fnames[idx]
    img_org = cv2.imread(self.root_src + 'dn_dataset/' + fname_org)
    # img_org = np.asarray(img_org)
 
    coin = np.random.randint(0, 50)
    img_dis = skimage.util.random_noise(img_org, mode='gaussian', seed=None,
                      var=(coin / 255.0) ** 2) # add gaussian noise
 
    # img_dis = img_dis[:, :, (2, 1, 0)] # bgr012 to rgb210
    img_dis = img_dis.transpose([2, 0, 1]) # hwc to chw
    img_dis = img_dis[(2, 1, 0), :, :] # bgr012 to rgb210
 
    img_org = img_org[:, :, (2, 1, 0)]/255.0 # bgr012 to rgb210
    img_org = img_org.transpose([2, 0, 1]) # hwc to chw
 
    img_dis = torch.from_numpy(img_dis).float()
    img_org = torch.from_numpy(img_org).float()
    # fname_org_dis = self.fnames_dis[idx]
    # img_dis = Image.open(self.root_src + 'distorted_train_block/' + fname_org_dis)
 
    # if img_org.mode != 'RGB':
    #   img_org = img_org.convert('RGB')
    #
    # if img_dis.mode != 'RGB':
    #   img_dis = img_dis.convert('RGB')
    # img_org = self.transform(img_org)
    # img_dis = self.transform(img_dis)
 
    return img_dis, img_org