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SYNDOF

The official matlab implementation of SYNDOF generation used in the paper, 'Deep Defocus Map Estimation using Domain Adaptation', CVPR 2019

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/learn @codeslake/SYNDOF
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0/100

Supported Platforms

Universal

README

SYNDOF (Synthetic Defocus Blur Image Dataset)<br><sub>Paper | Supp | DMENet Repo</sub>

This repository contains the official matlab implementation of SYNDOF generation used in the following paper:

Deep Defocus Map Estimation using Domain Adaptation<br> Junyong Lee<sup>1</sup>, Sungkil Lee<sup>2</sup>, Sunghyun Cho<sup>3</sup>, and Seungyong Lee<sup>1</sup><br> <sup>1</sup>POSTECH, <sup>2</sup>Sungkyunkwan University, <sup>3</sup>DGIST<br> IEEE Computer Vision and Pattern Recognition (CVPR) 2019<br>

Teaser image Picture: Outputs generated from our code– from left to right, synthetic input, defocus map output and defocused image.

Getting Started

Prerequisites

Tested environment

Matlab

  • Download and unzip the synthetic datasets (OneDrive | Dropbox) under ./data:
    ├── data
    │   ├── synthetic_datasets
    │   │   ├── ...
    

SYNDOF Generation

  • On matlab console, type

    # max_coc, input_offset, output_offset, is_random_gen, is_gpu, gpu_num
    generate_blur_by_depth(29, 'data', 'out', false, true, 1)
    
  • check the results under ./out, which is structured as,

    ├── ...
    ├── out
    │  ├── blur_map/                    # directory for output defocus map
    │  ├── blur_map_binary/             # directory for binarized defocus map
    │  ├── blur_map_norm/               # directory for normalized defocus map
    │  ├── depth_decomposed/            # directory for decomposed depth
    │  ├── image/                       # directory for input image (with its modified name)
    

Reading SYNDOF

  • We rounded real values of defocus map into the nearest 10-th. When you read a defocus map, for example in python, read the file as follows:
    image = (np.float32(cv2.imread(file_name, cv2.IMREAD_UNCHANGED))/10.)[:, :, 1]
    image = image / 7. # 7 = (maxCoC - 1) / 4, where maxCoC is 29 in this case.
    

Contact

Open an issue for any inquiries. You may also have contact with junyonglee@postech.ac.kr

License

License CC BY-NC<br> This software is being made available under the terms in the LICENSE file. Any exemptions to these terms require a license from the Pohang University of Science and Technology.

Citation

If you find this code useful, please consider citing:

@InProceedings{Lee2019DMENet,
    author    = {Junyong Lee and Sungkil Lee and Sunghyun Cho and Seungyong Lee},
    title     = {Deep Defocus Map Estimation Using Domain Adaptation},
    booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year      = {2019}
}
View on GitHub
GitHub Stars55
CategoryDevelopment
Updated2mo ago
Forks9

Languages

MATLAB

Security Score

95/100

Audited on Jan 19, 2026

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