v-0.1.0

What's Changed

• Add LoRa to our framework, can use -mod option for specific training ways, including train from scratch, using adapter, LoRa or AdaLoRa
• Release the guidance on how to use LoRa in our framework
• Other code refactoring and optimization.

v0.1.0-alpha

• Added the "-encoder" option, which allows specifying the specific ImageEncoder type. (you can set different encoders for the same '-net')

• Now, you have the flexibility to choose between using adapters or training from scratch by utilizing the -mod option in the command line.

• The framework now embraces MobileSAM with the introduction of the -net mobile_sam option. Moreover, it extends support to vit, tiny_vit, and efficient_vit as encoders. Specifically, when opting for vit or tiny_vit, the framework facilitates Adapter usage (adapter support for efficient_vit will be available in a later release due to its specific structure). Another notable feature is the compatibility with input images of varying resolutions. Successful training and testing have been conducted on ISIC and REFUGE datasets.

• Other code refactoring and optimization.