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---
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](https://github.com/WZH0120/SAM2-UNet)
## Performance Reference
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## Inference & Model Conversion
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## License
- Source Model: [APACHE-2.0](https://github.com/WZH0120/SAM2-UNet/blob/main/LICENSE)
- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |