https://github.com/xiaohk/FaceData

A macOS app to parse face landmarks from a video for training GANs
https://github.com/xiaohk/FaceData

annotator gans macos swift vision

Last synced: about 2 months ago
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A macOS app to parse face landmarks from a video for training GANs

• Host: GitHub
• URL: https://github.com/xiaohk/FaceData
• Owner: xiaohk
• License: mit
• Created: 2017-11-26T20:52:58.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-08-31T22:00:47.000Z (almost 3 years ago)
• Last Synced: 2024-01-29T15:12:50.727Z (5 months ago)
• Topics: annotator, gans, macos, swift, vision
• Language: Swift
• Homepage:
• Size: 22.5 MB
• Stars: 75
• Watchers: 5
• Forks: 8
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

Lists

• open-source-mac-os-apps - Face Data - macOS application used to auto-annotate landmarks from a video. ![swift_icon] (Applications / Video)

README

        
# Face Data

A macOS application used to auto-annotate landmarks from a video. Those landmarks can further be used as training data for Generative Adversarial Networks (GANs).

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5348316.svg)](https://doi.org/10.5281/zenodo.5348316)

[![License](https://img.shields.io/badge/License-MIT-red)](https://github.com/xiaohk/FaceData/blob/master/LICENSE)



	



## Getting Started

### Installing

You can either download the binary file from [`Rease`](https://github.com/xiaohk/FaceData/releases) or build the source code using Xcode.

### Use



	



|              | Description                                                                                                                                                        |

|--------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|

| Video Path   | Path to the video file, currently only support `.mp4` files. Use `Select File` to generate path using a file browsing panel.                                       |

| Output Path  | Path to the output directory, this app will create `origin` and `landmarks` two sub-directories. Use `Select Folder` to generate path using a file browsing panel. |

| Start Second | An integer value indicating from which second to start capturing frames from the video, default is 0 (from the beginning)                                          |

| End Second   | This app would not extract frames after this second. Default is the duration of the video.                                                                         |

| # of Frames  | Integer value of how many frames you want to generate. Default is 100 frames.                                                                                      |

| Start        | Start the process.                                                                                                                                                 |

| Cancel       | Stop the process.                                                                                                                                                  |

### Output

- Two sub-directories `origin` and `landmark` will be created in the specified output directory.

- `origin` contains the original frames extracted from the video, with file name: `img001.png`.

- `landmark` contains the landmark image drawn based on the corresponding frame in `origin`, with file name: `img001lm.png`.

- If there is no face detected in one original frame, the corresponding file name in `landmark` is `no_face_img001lm.png`.

### Output Images Processing

You will probably want to process the generated images to fit the size restriction for you GANs model. You can refer the Python script `crop.py`.

## Built With

* [Apple Vision Library](https://developer.apple.com/documentation/vision) - Easy to reproduce the landmarks in iOS devices

* [Apple AV Foundation](https://developer.apple.com/av-foundation/) - Also use lower level image format (`CGImage`) to  make codes portable to Cocoa Touch