https://github.com/randomtask2000/kohya_prep
Little image extractor and tagger from selfie video as input. The resulting images are meant to be used by Kohya to create a LoRA for something like SDLX
https://github.com/randomtask2000/kohya_prep
Last synced: 4 months ago
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Little image extractor and tagger from selfie video as input. The resulting images are meant to be used by Kohya to create a LoRA for something like SDLX
- Host: GitHub
- URL: https://github.com/randomtask2000/kohya_prep
- Owner: randomtask2000
- License: mit
- Created: 2024-01-22T20:29:03.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-02-24T14:15:03.000Z (almost 2 years ago)
- Last Synced: 2025-01-23T08:44:10.891Z (about 1 year ago)
- Language: Python
- Size: 13.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Kohya LoRA preprocessing
## mov2Images.py
Little image extractor and tagger from selfie video as input. The resulting images are meant to be used by Kohya to create a LoRA for something like SDLX. The images reduced to 512x512.
## resizeImages.py
Resizes images from a directory to an output directory. The images are reduced to 768x768.
# Face Feature Extraction Program Installation & Execution Guide
This guide provides instructions on how to install the necessary dependencies and run the face feature extraction program.
## Dependencies
- Python 3.7 or higher
- OpenCV
- Face Recognition
- NumPy
## Installation
First, ensure that you have Python 3.7 or higher installed on your system. You can download Python from the official website at https://www.python.org/downloads/.
After installing Python, you can install the required Python packages using `pip`. Open a terminal or command prompt and run the following commands:
```sh
pip install opencv-python
pip install face_recognition
pip install numpy
```
## Note
The image or video file path should point to a valid `.png`, `.jpg`, `.jpeg`, or `.mov` file.
The output directory should be a valid directory on your filesystem where the program has write access.
If processing a video, the program will process each frame asynchronously and may take some time to complete, depending on the video length and resolution.
Make sure to copy the Python script into a file named `create.py` and follow the installation guide above to set up your environment. After installation, you'll be able to run the script as instructed.
## Enjoy!
Make this better if you can - cheers!