thy960112 / mdbn Goto Github PK

import torch
from torch import nn as nn
from torch.nn import functional as F

from basicsr.archs.vgg_arch import VGGFeatureExtractor
from basicsr.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss

$ python basicsr/test.py -opt options/test/MDBN/test_MDBN_x2.yml
C:\Python310\lib\site-packages\torchvision\transforms\functional_tensor.py:5: UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in 0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in torchvision.transforms.v2.functional.
  warnings.warn(
Disable distributed.
Path already exists. Rename it to C:\MDBN-main\results\001_MDBN_x2_archived_20231009_203813
2023-10-09 20:38:13,476 INFO:
                ____                _       _____  ____
               / __ ) ____ _ _____ (_)_____/ ___/ / __ \
              / __  |/ __ `// ___// // ___/\__ \ / /_/ /
             / /_/ // /_/ /(__  )/ // /__ ___/ // _, _/
            /_____/ \__,_//____//_/ \___//____//_/ |_|
     ______                   __   __                 __      __
    / ____/____   ____   ____/ /  / /   __  __ _____ / /__   / /
   / / __ / __ \ / __ \ / __  /  / /   / / / // ___// //_/  / /
  / /_/ // /_/ // /_/ // /_/ /  / /___/ /_/ // /__ / /<    /_/
  \____/ \____/ \____/ \____/  /_____/\____/ \___//_/|_|  (_)

Version Information:
        BasicSR: 1.4.2
        PyTorch: 2.0.1+cu118
        TorchVision: 0.15.2+cu118
2023-10-09 20:38:13,476 INFO:
  name: 001_MDBN_x2
  model_type: SRModel
  scale: 2
  num_gpu: 1
  manual_seed: 2023
  datasets:[
    test_1:[
      name: Set5
      type: PairedImageDataset
      dataroot_gt: datasets/Set5/GTmod12
      dataroot_lq: datasets/Set5/LRbicx2
      io_backend:[
        type: disk
      ]
      phase: test
      scale: 2
    ]
  ]
  network_g:[
    type: MDBN
    num_in_ch: 3
    num_out_ch: 3
    num_feat: 64
    num_block: 6
    upscale: 2
    res_scale: 1.0
  ]
  path:[
    pretrain_network_g: experiments/pretrained_models/MDBN_x2.pth
    strict_load_g: True
    results_root: C:\MDBN-main\results\001_MDBN_x2
    log: C:\MDBN-main\results\001_MDBN_x2
    visualization: C:\MDBN-main\results\001_MDBN_x2\visualization
  ]
  val:[
    save_img: True
    suffix: None
    metrics:[
      psnr:[
        type: calculate_psnr
        crop_border: 4
        test_y_channel: ture
      ]
      ssim:[
        type: calculate_ssim
        crop_border: 4
        test_y_channel: ture
      ]
    ]
  ]
  dist: False
  rank: 0
  world_size: 1
  auto_resume: False
  is_train: False

2023-10-09 20:38:13,476 INFO: Dataset [PairedImageDataset] - Set5 is built.
2023-10-09 20:38:13,476 INFO: Number of test images in Set5: 2
Name MDBN is not found, use name: MDBN_basicsr!
Traceback (most recent call last):
  File "C:\MDBN-main\basicsr\test.py", line 45, in <module>
    test_pipeline(root_path)
  File "C:\MDBN-main\basicsr\test.py", line 35, in test_pipeline
    model = build_model(opt)
  File "C:\Python310\lib\site-packages\basicsr\models\__init__.py", line 26, in build_model
    model = MODEL_REGISTRY.get(opt['model_type'])(opt)
  File "C:\Python310\lib\site-packages\basicsr\models\sr_model.py", line 22, in __init__
    self.net_g = build_network(opt['network_g'])
  File "C:\Python310\lib\site-packages\basicsr\archs\__init__.py", line 22, in build_network
    net = ARCH_REGISTRY.get(network_type)(**opt)
  File "C:\Python310\lib\site-packages\basicsr\utils\registry.py", line 71, in get
    raise KeyError(f"No object named '{name}' found in '{self._name}' registry!")
KeyError: "No object named 'MDBN' found in 'arch' registry!"