Models — Samtool Supported

npy_label = retrieve_label(label_dir="./your_label_dir", image_filename="image.jpg")

Supports universal low-level flashing and FRP bypassing on both budget and mid-tier MediaTek and Unisoc setups. Chronological Rollout of Supported Smartphone Models

(e.g., SM-G9980 BIT D, SM-N981U BIT D, SM-N986U BIT D) samtool supported models

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Meta AI released SAM with a vision transformer (ViT) backbone trained on the massive SA-1B dataset. The original release includes three primary model sizes, balancing computational cost against segmentation accuracy. ViT-B (Base) : ~91 million npy_label = retrieve_label(label_dir="

: Integrated to target specialized entry-level hardware variants. 2. Core Functional Matrix by Model Group

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Because Samsung utilizes vastly different firmware architectures across different regions, a single model name (e.g., Galaxy S22) can have completely separate underlying chipsets.

: Modifies the Consumer Software Customization (CSC) matrix code variables. This unlocks specific localized carrier features, modifications, and radio bands without requiring regional device swaps.

: MobileSAM replaces the heavy image encoder of the original SAM with a distilled, lightweight version. It reduces the encoder size by over 60x, allowing it to run smoothly on mobile devices and in-browser WebGL setups under 10ms per click. EfficientSAM Backbone : Masked Autoencoder (MAE) pre-trained light ViT

: Standard SAM often fails on medical scans due to low contrast and unfamiliar grayscale structures. MedSAM is fine-tuned on millions of medical image-mask pairs, becoming the gold standard for automated anatomical segmentation. Remote Sensing: SAM-Geo / HQ-SAM