Dirty Pixels: Towards End-to-End Image Processing and Perception

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Deep Learning DirtyPixels
Overview

Dirty Pixels: Towards End-to-End Image Processing and Perception

This repository contains the code for the paper

Dirty Pixels: Towards End-to-End Image Processing and Perception
Steven Diamond, Vincent Sitzmann, Frank Julca-Aguilar, Stephen Boyd, Gordon Wetzstein, Felix Heide
Transactions on Graphics, 2021 | To be presented at SIGGRAPH, 2021


Installation

Clone this repository:

git clone [email protected]:princeton-computational-imaging/DirtyPixels.git

The project was developed using Python 3.6, Tensorflow (v1.12) and Slim. We provide an environment file to install all dependencies (creating an envirnoment called dirtypix):

conda env create -f environment.yml
conda activate dirtypix

Running Experiments

We provide code and data and trained models to reproduce the main results presented at the paper, and instructions on how to use this project for further research:

Citation

If you find our work useful in your research, please cite:

@article{steven:dirtypixels2021,
  title={Dirty Pixels: Towards End-to-End Image Processing and Perception},
  author={Diamond, Steven and Sitzmann, Vincent and Julca-Aguilar, Frank and Boyd, Stephen and Wetzstein, Gordon and Heide, Felix},
  journal={ACM Transactions on Graphics (SIGGRAPH)},
  year={2021},
  publisher={ACM}
}

License

This project is released under MIT License.

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Comments
  • Are you sure the way you provide raw images is not a joke?

    Are you sure the way you provide raw images is not a joke?

    When I look at your sensor_model.py file, I find that the raw image is actually a rgb image generated by a mask. Honestly, this toy quality image leads me to think that the experimental results of the paper are not fair.

    To save time, for people who plan to use this dataset to validate raw images, I suggest you look elsewhere.

    opened by Baboom-l 0
  • Question about reproduction

    Question about reproduction

    I am sorry to bother you. When I retrain the network (isp + mobilenet) following your advice, I got loss=nan from the first step. I didn't modify your code at all.Do you have any advice to make this code work?

    opened by miaoyuchun 0
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