技巧

• https://github.com/rwightman/pytorch-image-models

• 本科生晋升GM记录 & kaggle比赛进阶技巧分享

• 9 Computer Vision Tricks to Improve Performance

• https://github.com/kuangliu/pytorch-cifar

数据

• https://zhuanlan.zhihu.com/p/402511359

• 数据增量: https://github.com/conradry/copy-paste-aug

• 目标检测增强: 正样本增强：根据类别增强、根据大小增强、增强中加入随机概率、无合适anchor的增强、根据匹配好坏的增强

训练

• 首先在小backbone如resnet34/efficientnetb0起步，调节loss/augmentation/metric/lr_scheduler

• 然后再换大模型

分类

检测

mmdetection: https://zhuanlan.zhihu.com/p/337375549

• EDA：分析图片尺寸信息，标签数量、大小信息(根据数据信息决定：anchor，训练尺度， 感受野) https://github.com/Media-Smart/volkscv/tree/master/volkscv/analyzer/statistics

• 模型：yolov5，efficientdet，mmdetection(cascade rcnn)

• 调参：模型，后处理

• 优化：persudo label，TTA，nms，weighted fusion box

• https://github.com/felixBrave/ocr_chinese

• https://github.com/FudanVI/benchmarking-chinese-text-recognition

EDA

• 图像大小分布

• gt-box 大小，长宽比分布

• gt-box与图像大小比例分布

• 特殊性质

后处理

• https://www.kaggle.com/shonenkov/wbf-approach-for-ensemble

入门

• 深度迁移学习实用技巧(Kaggle Paris Day 2022)

• Google-Deep Learning Tuning Playbook

• https://www.kaggle.com/code/phalanx/train-swin-t-pytorch-lightning

https://zhuanlan.zhihu.com/p/266864780 https://www.zybuluo.com/huanghaian/note/1743266 https://github.com/LiChenyang-Github/tianchi_Cervical_Cancer_top4 https://www.kaggle.com/code/youhanlee/unet-resnetblock-hypercolumn-deep-supervision-fold

实践

• https://zhuanlan.zhihu.com/p/409157142

• https://zhuanlan.zhihu.com/p/363354912

• https://kulbear.github.io/archives/protein/

• https://github.com/yl305237731/flexible-yolov5

• https://github.com/bubbliiiing/yolov5-tf2

MM: https://zhuanlan.zhihu.com/p/337375549?utm_source=zhihu&utm_medium=social&utm_oi=896443966524891136

https://towardsdatascience.com/indian-car-license-plate-detection-using-yolo-v5-ae2574578175

• https://github.com/facebookresearch/pytorchvideo