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SAM2-LipSegmentation
quinncm/SAM2-LipSegmentation
SAM2-LipSegmentation is a machine learning model from quinncm. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Fine-tuned Segment Anything Model 2 (SAM2.1 Hiera Small) weights for semi-automated mouth landmark localization evaluation. These weights were produced by training the model on 1,600 images from the LaPa dataset and 1…
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Updated Sep 13, 2026
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.pt217 MB · 68%
At a glance
- Access
- Public
- Created
- Sep 13, 2026
- Updated
- Sep 13, 2026
- SHA
- 655c5027
Model card
From the Hugging Face model README
SAM2 Lip Segmentation
Fine-tuned Segment Anything Model 2 (SAM2.1 Hiera Small) weights for semi-automated mouth landmark localization evaluation. These weights were produced by training the model on 1,600 images from the LaPa dataset and 1,600 images from the new MetaHuman Lip Segmentation dataset (linked below).
Model and Training Parameters
- Base model: SAM2.1 Hiera Small
- Fine-tuning datasets: Landmark-guided face Parsing dataset (LaPa) and MetaHuman Lip Segmentation Dataset
- Prompt encoder and mask decoder were fine-tuned for 30 epochs
- Learning rate: 1e-5
- Batch size: 8
Included Files
sam2 config file: sam2.1_hiera_s.yaml
weights: finetuned_lip_seg_sam2.1s.pt
sample annotated video: sample_lip_segmentation.mp4
Training Datasets
This model was fine-tuned using MetaHuman Lip Segmentation Dataset. and Landmark-Guided Face Parsing Dataset
Citation
TBD
- Created
- Sep 13, 2026
- Updated
- Sep 13, 2026