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View Code? Open in Web Editor NEW存储一些商品识别的实验结果及日志
License: GNU Lesser General Public License v2.1
存储一些商品识别的实验结果及日志
License: GNU Lesser General Public License v2.1
RP2K数据集收录了50万+张零售商品货架图片,商品种类超过2,000种,是目前零售类数据集中产品种类数量最多的数据集。不同于一般聚焦新产品的数据集,RP2K收录了超过50万张零售商品货架图片,商品种类超过2000种,该数据集是目前零售类数据集中产品种类数量TOP1,同时所有图片均来自于真实场景下的人工采集,针对每种商品,品览提供了十分详细的标注。RP2K致力于帮助物品识别领域进行学术研究,同时为AI物品识别从业者打造真实行业级试炼场。
在真实场景中,准确识别货架上零售产品仍然具有很高的挑战性。
目前Colugo已经发布了基于PP系列模型的基于RP2K的预训练模型,以及相关实验日志,详情见此。欢迎各位开发者参与对RP2K的打榜活动。
相关教程已经发布,您可以通过Goods_Recognition了解PaddleClas的使用方法,PaddleClas的详细使用见其Github官方Repo。
目前ColugoMum最高精度达96.91%,全网最高达97.56%。
Originally posted by @thomas-yanxin in ColugoMum/.github#1
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