PyTorch扩展用于快速研发原型和Kaggle农业

test-time-augmentation 开源项目推荐(36 个)
test-time-augmentation 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 36 个仓库Collection of awesome test-time (domain/batch/instance) adaptation methods
Image Test Time Augmentation with PyTorch!
Code Implementation for EmbedSeg, an Instance Segmentation Method for Microscopy Images
Test-Time Augmentation library for Pytorch
Efficient Test-Time Scaling for Small Vision-Language Models, official implementation of the ICLR'26 paper, test-time scaling via test-time augmentation
My modified version of YoloV5 training, cross-validation and inference with Pseudo Labelling pytorch pipelines used in GWD Kaggle Competition
Wheat detection using Faster RCNN
Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.
A curated collection of Test-Time Adaptation (TTA) papers, methods, and resources, updated monthly with the latest research.
Source code for the CIKM 2024 paper "Post-Training Embedding Enhancement for Long-Tail Recommendation."
My modified version of EfficientDet training, cross-validation and inference with Pseudo Labelling pytorch pipelines used in GWD Kaggle Competition
End-to-end HCR R&D: from HOG+XGBoost baseline to CNN hyperparameter optimization and Ensemble+TTA, achieving 93.16% accuracy with rigorous error analysis.
ARC-Test-Time-Training (ARC-TTT)
Object Detection and Bounding Box Prediction using YOLO5 and EfficientDet , Image Augmentations and Test Time Augmentations
Image recognition used to distinguish between bees and wasps in photographs
A modern implementation of ECCV 2018 paper: "Hierarchical Relational Networks for Group Activity Recognition and Retrieval".
AIC-2026 Track 4 solution: CLIP ViT-B/32 + LoRA with ELR/DSPT/DeFT robust losses, GMM sample selection and MultiScaleTTA on noisy fine-grained labels.
Test time augmentation with Tensorflow keras models for segmentation tasks. This package also enables creation of keras layers for GPU acceleration
High-performance LPR system optimized for Indian license plates, achieving 97% character accuracy. Features a hybrid pipeline using YOLOv11 and Mamba-SSM (State Space Models) with built-in regex correction and Beam Search decoding.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/test-time-augmentation。
- 该话题在 GitHub 上共有 36 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 4262 Star,覆盖 2 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。