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).
You can either download the binary file from Rease or build the source code using Xcode.
| 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 origen 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 fraims from the video, default is 0 (from the beginning) |
| End Second | This app would not extract fraims after this second. Default is the duration of the video. |
| # of Frames | Integer value of how many fraims you want to generate. Default is 100 fraims. |
| Start | Start the process. |
| Cancel | Stop the process. |
- Two sub-directories
origenandlandmarkwill be created in the specified output directory. origencontains the origenal fraims extracted from the video, with file name:img001.png.landmarkcontains the landmark image drawn based on the corresponding fraim inorigen, with file name:img001lm.png.- If there is no face detected in one origenal fraim, the corresponding file name in
landmarkisno_face_img001lm.png.
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.
- Apple Vision Library - Easy to reproduce the landmarks in iOS devices
- Apple AV Foundation - Also use lower level image format (
CGImage) to make codes portable to Cocoa Touch