/3d-photo-inpainting

[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting

Primary LanguagePythonOtherNOASSERTION

3D effects generation from a single 2D image

Reference Paper: 3D Photography using Context-aware Layered Depth Inpainting
Meng-Li Shih, Shih-Yang Su, Johannes Kopf, and Jia-Bin Huang
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

Prerequisites

  • Linux (tested on Ubuntu 18.04.4 LTS)
  • Python 3.7 (tested on 3.7.4)
  • PyTorch 1.4.0 (tested on 1.4.0 for execution)

and the Python dependencies listed in requirements.txt

  • To get started, please run the following commands: 
    conda create -n 3DP python=3.7 anaconda
conda activate 3DP
pip install -r requirements.txt
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit==10.1.243 -c pytorch
  • Next, please download the model weight using the following command: 
    chmod +x download.sh
./download.sh

Quick start

Please follow the instructions in this section. This should allow to execute our results. For more detailed instructions, please refer to DOCUMENTATION.md.

Execute

  1. Put .jpg files (e.g., test.jpg) into the image folder.
    • E.g., image/moon.jpg
  2. Run the following command 
    python app.py
    • Note: The 3D photo generation process usually takes about 5-10 minutes depending on the available computing resources.
  3. Go to the http://127.0.0.1:5000/, upload a potrait image, hit run.
  4. The results are stored in the following directories:
    • Corresponding depth map estimated by MiDaS
      • E.g. depth/moon.npy, depth/moon.png
      • User could edit depth/moon.png manually.
        • Remember to set the following two flags as listed below if user wants to use manually edited depth/moon.png as input for 3D Photo.
          • depth_format: '.png'
          • require_midas: False
    • Inpainted 3D mesh (Optional: User need to switch on the flag save_ply)
      • E.g. mesh/moon.ply
    • Rendered videos with zoom-in motion
      • E.g. video/moon_zoom-in.mp4
    • Rendered videos with swing motion
      • E.g. video/moon_swing.mp4
    • Rendered videos with circle motion
      • E.g. video/moon_circle.mp4
    • Rendered videos with dolly zoom-in effect
      • E.g. video/moon_dolly-zoom-in.mp4
      • Note: We assume that the object of focus is located at the center of the image.
  5. (Optional) If you want to change the default configuration. Please read DOCUMENTATION.md and modified argument.yml.

License

This work is licensed under MIT License. See LICENSE for details.

If you find our code/models useful, please consider citing our paper:

@inproceedings{Shih3DP20,
  author = {Shih, Meng-Li and Su, Shih-Yang and Kopf, Johannes and Huang, Jia-Bin},
  title = {3D Photography using Context-aware Layered Depth Inpainting},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020}
}

Acknowledgments