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利用Segment Anything(SAM)模型进行快速标注

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Frontiers in Neuroinformatics 2022: Local Label Point Correction for Edge Detection of Overlapping Cervical Cells

High-Resolution Image Synthesis with Latent Diffusion Models

Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).

Tools for tissue image stain normalisation and augmentation in Python 3

Interactive convnet features visualization for Keras

assistant tools for attention visualization in deep learning

Implementation of ICCV21 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers

Official code for Conformer: Local Features Coupling Global Representations for Visual Recognition

pytorch implementation of Recurrent Attention CNN.

Cervix93 Cytology Dataset and the Baseline Method

A fuzzy distance-based ensemble of deep models for cervical cancer detection published in Computer Methods and Programs in Biomedicine, Elsevier

Based on our paper on "A Fuzzy Rank-based Ensemble of CNN Models for Classification of Cervical Cytology" published in Nature- Scientific Reports.

Datasets, Transforms and Models specific to Computer Vision

Google Brain AutoML

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Adapting Segment Anything Model for Medical Image Segmentation

A central hub for gathering and showcasing amazing projects that extend OpenMMLab with SAM and other exciting features.

This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

Codes for CVPR2023 paper "Directional Connectivity-based Segmentation of Medical Images"

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Unsupervised Semantic Segmentation by Distilling Feature Correspondences

Segment Anything in Medical Images

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

This is the repository for the ICLR2023 accepted paper -- Medical Image Understanding With Pretrained VLM