Lips Segmentation Computer Vision Project

Rahmani Dibansa

Updated 2 years ago

894

views

30

downloads
Classes (2)
BoundingBox
Mask

Metrics

Try This Model
Drop an image or
Description

Here are a few use cases for this project:

  1. 'Mask Compliance Monitoring': By using the Lips Segmentation model, businesses can track whether their employees are appropriately wearing masks in the workplace, potentially feeding into public health initiatives for pandemic control.

  2. 'Cosmetic Testing and Augmentation': The system could be used in beauty apps or virtual platforms which allow users to experiment with different shades of lipstick or other lip cosmetics. It can display accurate virtual results on the user's lips, taking into account dynamic elements such as wrinkles or hair around the lip area.

  3. 'Virtual Reality and Game Development': This model can help designers create more realistic characters by accurately mapping and detecting lip features, including the complex effects of aging, like wrinkles. It can be further used to improve lip-syncing of characters according to the dialogues and expressions.

  4. 'Medical Diagnostics Aid': The 'Lips Segmentation' model can be used in the medical field for diagnostics and treatment planning for cases involving oral diseases, facial reconstructions, or maxillofacial surgeries.

  5. 'Video Conferencing Enhancement': For better video chat conferencing experiences, the model could provide real-time filters, like blurring the background but keeping the user's face, namely the lips, in focus. This would be of interest in professional or social virtual meetings.

Use This Trained Model

Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.

Supervision

Build Computer Vision Applications Faster with Supervision

Visualize and process your model results with our reusable computer vision tools.

Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            lips-segmentation-dqqxf_dataset,
                            title = { Lips Segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { Rahmani Dibansa },
                            howpublished = { \url{ https://universe.roboflow.com/rahmani-dibansa-xze43/lips-segmentation-dqqxf } },
                            url = { https://universe.roboflow.com/rahmani-dibansa-xze43/lips-segmentation-dqqxf },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-11-24 },
                            }