草庐IT

step_anchor

全部标签

yolov5 anchors 中 K-means聚类

anchors运行trains.py没有生成anchor原因程序kmeans改动(距离、k-means++)运行trains.py没有生成anchor原因yolov5运行后有一行autoanchor:一些教程的生成图如下训练一开始会先计算BestPossibleRecall(BPR),当BPR时,再在kmean_anchors函数中进行k均值和遗传算法更新anchors。但是我的数据集BPR=0.9997,所以没有生成新的anchors。默认的预设anchors很匹配我的训练数据,anchors就不会在更改,就使用预设的。改了聚类的欧氏距离为iou,和去掉遗传算法,都没有预设的效果好。yolo

Management in Developers' View: Hold the Bag and Step on the Pitfall

Thereisnoshortageoftechnicalprogrammers,butthosewhoexcelinbothtechnologyandmanagementarefew.Someclaimthatmanagementisachallengingtasksincedealingwithmachinesismucheasierthandealingwithhumans,andmanagersmustsatisfyleaders'demandsandconsiderthewholeteam'sfeelings.Frequently,theymustshouldertheburden,o

Management in Developers' View: Hold the Bag and Step on the Pitfall

Thereisnoshortageoftechnicalprogrammers,butthosewhoexcelinbothtechnologyandmanagementarefew.Someclaimthatmanagementisachallengingtasksincedealingwithmachinesismucheasierthandealingwithhumans,andmanagersmustsatisfyleaders'demandsandconsiderthewholeteam'sfeelings.Frequently,theymustshouldertheburden,o

From Internet Leader to User Expert, What Are Google's Next Steps?

AttheopeningceremonyofGoogleI/O2022,thechiefexecutiveofficer,SundarPichai,delivereda2-hourkeynotespeech,"Advancingknowledgeandcomputing."OutliningGoogle'slong-termvision,thespeechalsohintedattheevolutionofInternettechnologyinthepost-pandemicera."Searchyourworld,anywayandanywhere"Thistime,GoogleSearc

From Internet Leader to User Expert, What Are Google's Next Steps?

AttheopeningceremonyofGoogleI/O2022,thechiefexecutiveofficer,SundarPichai,delivereda2-hourkeynotespeech,"Advancingknowledgeandcomputing."OutliningGoogle'slong-termvision,thespeechalsohintedattheevolutionofInternettechnologyinthepost-pandemicera."Searchyourworld,anywayandanywhere"Thistime,GoogleSearc

深度学习之step by step搭建神经网络

声明本文参考Deep-Learning-Specialization-Coursera/Convolution_model_Step_by_Step_v1.ipynbatmain·abdur75648/Deep-Learning-Specialization-Coursera·GitHub,力求理解。资料下载链接:https://pan.baidu.com/s/1LoMe9bS_ig0wB7ubR9m39Q提取码:afhc,请在开始之前下载好所需资料。【博主使用的python版本:3.9.12】,当然也使用tensorflow2.1.神经网络的底层搭建  这里,我们要实现一个拥有卷积层(CON

深度学习之step by step搭建神经网络

声明本文参考Deep-Learning-Specialization-Coursera/Convolution_model_Step_by_Step_v1.ipynbatmain·abdur75648/Deep-Learning-Specialization-Coursera·GitHub,力求理解。资料下载链接:https://pan.baidu.com/s/1LoMe9bS_ig0wB7ubR9m39Q提取码:afhc,请在开始之前下载好所需资料。【博主使用的python版本:3.9.12】,当然也使用tensorflow2.1.神经网络的底层搭建  这里,我们要实现一个拥有卷积层(CON

SAP WM 通过2-Step Picking创建的TO之间的关联关系

SAPWM通过2-StepPicking创建的TO之间的关联关系 SAPWM模块里的2-StepPicking功能,会在Pick环节和Allocation环节创建TO单据来完成拣配事务。这些TO单据之间相互并无直接关联关系,但是有办法查询到彼此。 销售订单736,2个交货单,是通过2-steppicking的方式完成拣配的。如下凭证流,  我们发现只有在Allocation(即第二步)环节创建的TO单据43/44才会显示在该销售订单的凭证流里。如上图。TO#43,  TO#44,  在Pick(即第一步)环节创建的TO#42,由于它不与交货单号关联,所以它不出现在该SO的凭证流里。 TO#42

SAP WM 通过2-Step Picking创建的TO之间的关联关系

SAPWM通过2-StepPicking创建的TO之间的关联关系 SAPWM模块里的2-StepPicking功能,会在Pick环节和Allocation环节创建TO单据来完成拣配事务。这些TO单据之间相互并无直接关联关系,但是有办法查询到彼此。 销售订单736,2个交货单,是通过2-steppicking的方式完成拣配的。如下凭证流,  我们发现只有在Allocation(即第二步)环节创建的TO单据43/44才会显示在该销售订单的凭证流里。如上图。TO#43,  TO#44,  在Pick(即第一步)环节创建的TO#42,由于它不与交货单号关联,所以它不出现在该SO的凭证流里。 TO#42

SAP WM 2-Step Picking流程里创建的Group的分析

SAPWM2-StepPicking流程里创建的Group的分析  SAPWM模块的2-StepPicking流程里,需要根据实际业务情况,首先为外向交货单(OutboundDelivery)或者传输请求(TR)单据创建组(Group)。 很自然就产生了一个需求或者疑问就是,已知一个Groupnumber,如何知道它的具体信息,它是包含了哪些Delivery或者TR,执行完2-StepPicking操作之后如何查询到该组相关的TO单据等等。经查,事务代码LT45就可以解答这些疑问。 执行事务代码LT45,进入如下界面,   输入仓库号,Groupnumber,创建日期等参数,执行,SAP系统进