A collection of AI-enhanced tools pertaining to an ongoing research on the impact of different Carotene levels on the perception of attractiveness and health.
The repo consists of:
- A Face Morphing tool: A tool designed to provide latent-based morphs of individuals providing a means to anonymize participants in research studies. The tool utilizes a method called Pivotal Tuning Inversion to create near perfect recreations of participant's faces in W+ space; enabling non-linear interpolation between three particpants at a time.
- A Face Masking tool: Designed to apply progressively stronger tints to targeted areas of an image to simulate various shades along the CIELAB colour space in accordance with established methodologies. The tool utilizes a pretrained Facial Segmentation model to accurately mask skin areas while preserving natural features such as the eyes, lips, and hair.
- Create a copy of the kaggle notebook from here
- Enable
Internetunder the Settings tab - Select
GPU P100as theGPU ACCELERATORoption under the settings tab - Upload a zip file with a nested folders containing three images each. The names of these files are unimportant. An example of this is seen below:
Zip File
> Morph_1_Folder
> Person1.png
> Person2.png
> Person3.png
> Morph_2_Folder
> ...
- Start PTI
- The notebook WILL crash on the first run. Run the second code cell again and it will function correctly
- Download the results.
- Git clone this repository
git clone https://github.com/RubinInsert/FaceMasker
- OR, Download it manually from github
- Move into the directory with the python code On Windows, this would be:
cd <Folder Directory>
- Install the requirements
pip install -r requirements.txt
- Ensure your folder structure has the following format. Not all folders are required to run the program. However, any morph images must be found at the end of a correct folder trail like
Input Folder > Male > Caucasian > 18-24 > M1.pngand must be named correctly asM1.png-M10.png:
Input Folder
> Male
> Caucasian
> 18-24
> 25-34
> 35-44
> 45-54
> 55-64
> 65 and over
> African
> ...
> Asian
> ...
> Female
> ...
- Run the program using
python3 main.py -input "Example_Folder_Input/" -output "Example_Folder_Output/" -color_tint 2.36,0,0 -thread_count 2input dictates the input folder
output dictates the output folder
color_tint dictates what colour to apply to masked faces at each step. If more than one value is zero, the processing time will be longer.
thread_count dictates how much processing is allocated to the program. 2-4 is generally a reasonable value.
