SYNDOF: A MATLAB repository from Zadul

SYNDOF (Synthetic Defocus Blur Image Dataset)

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

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

Deep Defocus Map Estimation using Domain Adaptation
Junyong Lee, Sungkil Lee, Sunghyun Cho and Seungyong Lee, CVPR 2019

Getting Started

Prerequisites

Download and unzip the synthetic datasets 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.

Citation

If you find this code useful, please consider citing:

@InProceedings{Lee_2019_CVPR,
    author = {Lee, Junyong and Lee, Sungkil and Cho, Sunghyun and Lee, Seungyong},
    title = {Deep Defocus Map Estimation Using Domain Adaptation},
    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2019}
}

Contact

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

Resources

All material related to our paper is available via the following links:

Link
Paper PDF
Supplementary Files
Paper Repository
Synthetic Datasets

License

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.

About Coupe Project

Project ‘COUPE’ aims to develop software that evaluates and improves the quality of images and videos based on big visual data. To achieve the goal, we extract sharpness, color, composition features from images and develop technologies for restoring and improving by using them. In addition, personalization technology through user reference analysis is under study.

Please check out other Coupe repositories in our Posgraph github organization.

Zadul/SYNDOF