face parsing

Introduction

The Face Parsing model is a semantic segmentation tool fine-tuned from the NVIDIA/MIT-B5 model using the CelebAMask-HQ dataset. It is designed for face parsing tasks, providing detailed segmentation of facial features. The model is available for both Python and browser-based applications through Transformers.js.

Architecture

The Face Parsing model is a transformer-based semantic segmentation model. It utilizes the Segformer architecture, which is optimized for image segmentation tasks. The model can operate in different environments, including PyTorch and ONNX, making it versatile for various deployment scenarios.

Training

The model is fine-tuned using the CelebAMask-HQ dataset, which consists of high-quality images of celebrities. This dataset is large but may not encompass a diverse range of facial features due to its focus on celebrity images. The model captures various facial features, including skin, nose, eyes, eyebrows, ears, mouth, and other accessories.

Guide: Running Locally

Python

1. Environment Setup: Ensure you have Python with PyTorch and Transformers installed. Use a virtual environment for better dependency management.
2. Device Selection: The script automatically selects a CUDA-enabled GPU if available, otherwise, it defaults to the CPU.
3. Model Loading:

   from transformers import SegformerImageProcessor, SegformerForSemanticSegmentation
   
   image_processor = SegformerImageProcessor.from_pretrained("jonathandinu/face-parsing")
   model = SegformerForSemanticSegmentation.from_pretrained("jonathandinu/face-parsing")
   

4. Inference: Load an image and process it through the model to obtain segmentation labels. Visualize using matplotlib.

Browser (Transformers.js)

1. Setup: Use dynamic imports to load the Transformers.js library.
2. Inference: Utilize the pipeline function to perform image segmentation asynchronously in the browser.

Cloud GPUs

For enhanced performance, especially for larger datasets or higher throughput, consider using cloud-based GPUs such as those provided by AWS, Google Cloud, or Azure.

License

The Face Parsing model is licensed for non-commercial research and educational purposes, as specified by the model developer, Jonathan Dinu. Users should refer to the associated documentation and original research papers for further details.