This GitHub repository demonstrates the utilization of UNETR for multiclass image segmentation on the Landmark Guided Face Parsing dataset (LaPa) dataset. .
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| The block diagram of the Original UNETR model. |
LaPa stands for Landmark guided face Parsing dataset (LaPa). It is a large-scale dataset for human face parsing. It consists of more than 22,000 facial images with abundant variations in expression, pose and occlusion, and each image of LaPa is provided with a 11-category pixel-level label map and 106-point landmarks.
Download the dataset: Landmark guided face Parsing dataset (LaPa)
For more: LaPa-Dataset for face parsing
The sequence in the images below is Input Image, Ground Truth and Prediction.
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- Train on more epochs.
- Increase the input image resolution.
- Apply data augmentation.
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