license: other
license_name: aplux-model-farm-license
license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf
pipeline_tag: image-segmentation
tags:
- AIoT
- QNN
SAM2-Unet-tiny: Semantic Segmentation
SAM2-Unet is a hybrid segmentation model integrating the Segment Anything Model (SAM) with U-Net, optimized for medical image segmentation and few-shot learning. It incorporates SAM's visual prompt mechanism into U-Net's encoder-decoder structure, enabling dynamic target guidance via interactive point/box inputs while retaining skip connections for multi-scale feature fusion. Lightweight adapters fine-tune SAM's pretrained weights to enhance sensitivity to low-contrast regions in medical images (e.g., CT/MRI) and reduce reliance on large annotated datasets. Supporting zero-shot transfer and few-shot tuning, it improves Dice scores by ~8% over traditional U-Net on BraTS and ISIC benchmarks with low computational overhead, ideal for clinical diagnostics and real-time lesion localization.
Source model
- Input shape: 1x3x352x352
- Number of parameters: 28.38M
- Model size: 119.42M
- Output shape: 1x1x352x352
The source model can be found here
Performance Reference
Please search model by model name in Model Farm
Inference & Model Conversion
Please search model by model name in Model Farm
License
Source Model: APACHE-2.0
Deployable Model: APLUX-MODEL-FARM-LICENSE