From 4ebb9cbdf1ec2ca83b1e4d01d82a5ada6a407e62 Mon Sep 17 00:00:00 2001 From: "Edward.Aung" Date: Wed, 19 Apr 2023 22:12:38 +1000 Subject: [PATCH 1/2] fixed some circular import in inference --- basicsr/data/ffhq_blind_joint_dataset.py | 2 +- basicsr/models/base_model.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/basicsr/data/ffhq_blind_joint_dataset.py b/basicsr/data/ffhq_blind_joint_dataset.py index 673b52ec..db540a92 100755 --- a/basicsr/data/ffhq_blind_joint_dataset.py +++ b/basicsr/data/ffhq_blind_joint_dataset.py @@ -9,7 +9,7 @@ import torch.utils.data as data from torchvision.transforms.functional import (adjust_brightness, adjust_contrast, adjust_hue, adjust_saturation, normalize) -from basicsr.data import gaussian_kernels as gaussian_kernels +#from basicsr.data import gaussian_kernels as gaussian_kernels from basicsr.data.data_util import paths_from_folder from basicsr.data.transforms import augment, img_rotate from basicsr.metrics.psnr_ssim import calculate_psnr diff --git a/basicsr/models/base_model.py b/basicsr/models/base_model.py index bf1f90ac..b4021175 100644 --- a/basicsr/models/base_model.py +++ b/basicsr/models/base_model.py @@ -5,7 +5,7 @@ from copy import deepcopy from torch.nn.parallel import DataParallel, DistributedDataParallel -from basicsr.models import lr_scheduler as lr_scheduler +#from basicsr.models import lr_scheduler as lr_scheduler from basicsr.utils.dist_util import master_only logger = logging.getLogger('basicsr') From 6ca6c405fddbafb56a1e818eb0c3f40d36de3c71 Mon Sep 17 00:00:00 2001 From: Edward Aung Date: Thu, 24 Apr 2025 10:46:41 +1000 Subject: [PATCH 2/2] make the error goes away --- inference_codeformer.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/inference_codeformer.py b/inference_codeformer.py index 1a38cc95..171b37a5 100644 --- a/inference_codeformer.py +++ b/inference_codeformer.py @@ -259,6 +259,10 @@ def set_realesrgan(): img_list = sorted(glob.glob(os.path.join(result_root, 'final_results', '*.[jp][pn]g'))) for img_path in img_list: img = cv2.imread(img_path) + height, width = img.shape[:2] + wb = width % 2 + hb = height % 2 + img = cv2.copyMakeBorder(img, 0, hb, wb, 0, cv2.BORDER_REFLECT) video_frames.append(img) # write images to video height, width = video_frames[0].shape[:2]