Intrinsic Image Harmonization

Related tags

Deep LearningIntrinsicHarmony
Overview

Intrinsic Image Harmonization [Paper]

Zonghui Guo, Haiyong Zheng, Yufeng Jiang, Zhaorui Gu, Bing Zheng

Here we provide PyTorch implementation and the trained model of our framework.

Prerequisites

  • Linux
  • Python 3
  • CPU or NVIDIA GPU + CUDA CuDNN

Train/Test

CUDA_VISIBLE_DEVICES=0 python train.py --model retinexltifpm  --name retinexltifpm_allihd  --dataset_root <dataset_dir> --dataset_name IHD --batch_size xx --init_port xxxx
  • Test the model
CUDA_VISIBLE_DEVICES=0 python test.py --model retinexltifpm  --name retinexltifpm_allihd  --dataset_root <dataset_dir> --dataset_name IHD --batch_size xx --init_port xxxx

Apply a pre-trained model

  • Download the pretrained model from Google Drive or BaiduCloud (access code: 20m6), and put net_G.pth in the directory checkpoints/experiment. Run:
CUDA_VISIBLE_DEVICES=0 python test.py --model retinexltifpm  --name experiment  --dataset_root <dataset_dir> --dataset_name IHD --batch_size xx --init_port xxxx

Evaluation

We provide the code in ih_evaluation.py. Run:

CUDA_VISIBLE_DEVICES=0 python evaluation/ih_evaluation.py --dataroot <dataset_dir> --result_root  results/experiment/test_latest/images/ --evaluation_type our --dataset_name ALL

Quantitative Result

Dataset Metrics Composite Ours
(iHarmony4)		 Ours
(iHarmony4+HVIDIT)
HCOCO PSNR
MSE
fMSE 		33.99
69.37
996.59 		37.61
23.25
386.39 		37.77
21.84
367.38
HAdobe5k PSNR
MSE
fMSE 		28.52
345.54
2051.61 		36.20
42.21
296.76 		36.49
39.53
266.49
HFlickr PSNR
MSE
fMSE 		28.43
264.35
1574.37 		31.74
100.86
676.71 		32.08
96.87
635.60
Hday2night PSNR
MSE
fMSE 		34.36
109.65
1409.98 		36.48
50.64
755.88 		36.60
50.37
763.33
HVIDIT PSNR
MSE
fMSE 		38.72
53.12
1604.41 		-
-
- 		41.83
22.49
691.06
ALL PSNR
MSE
fMSE 		32.07
167.39
1386.12 		36.53
37.95
399.34 		36.96
35.33
388.50

Bibtex

If you use this code for your research, please cite our papers.

@InProceedings{Guo_2021_CVPR,
    author    = {Guo, Zonghui and Zheng, Haiyong and Jiang, Yufeng and Gu, Zhaorui and Zheng, Bing},
    title     = {Intrinsic Image Harmonization},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {16367-16376}
}

Acknowledgement

For some of the data modules and model functions used in this source code, we need to acknowledge the repo of DoveNet and CycleGAN.

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Comments
  • Model Inference

    Model Inference

    Hello, is there a way to infer the model by reading an image and passing the image and its mask to the model and getting the harmonized output? Without the need to store the image's path in a text file and reading it from the text file then loading the image?

    opened by AhmedHashish123 2
  • visdom interface is blank

    visdom interface is blank

    first，thanks for your excellent work！ When I execute the training code, the visdom interface does not display the result picture and the training loss. it works when I execute the code of dovenet. could you tell me how to solve this problem? thanks again

    opened by Ligouhi 0
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