on a per-dataset basis • Allows you to split, merge, and edit datasets • Annotation • A simple user interface that allows you to focus on classification tasks • Ability to work securely with authority functions • Data Augmentation • Amplification of data that does not loss the characteristics of the inspection image • Learning • Process to train model without expertise • Analytical • Analyze the accuracy of a trained model • Download the appropriate learning model • Inference • Install into inspection equipment for fast off-line processing Storage Preprocessing Annotation Training Analytical
resources against requests • Low-cost deployments Features Web Browser Google Chrome, Firefox Network Cloud: >= 10 Mbps (download, upload) On-premises: >= 100 Mbps RAM >= 4GB Client System Requirements Application Foundation Separation of application and data, multi- tenant with DB division realized reliable data separation and scalability. A社 Computing Resources B社 C社 Authorization Service
use of computing resources • Capitalization as production equipment • Independent on stability of internet line Features OS Linux (Red Hat Linux Series, Ubuntu etc.) Processing Unit GPU: NVIDIA GPU (CUDA 9.0) RAM >= 16GB Storage HDD (>=2TB), SSD for cache(>=400GB) Additional outer storage for backup Network >= 100 Mbps Application Environment Virtualizing: Docker System Requirements Manager Administrator Operator Machine Image Data knowledge Manage Collaborate through LAN ※ only for distribution in Japan
organization • Account privilege management is limited to administrators only • Controls authority group by group according to roles such as annotation work only, image upload only Organization Manager Group Operator Group Machine Group
TensorFlowTM • Learning of large-scale data set of several million scale • A network model suitable developed for print quality inspection • Prevent a faulty product from being put on the market by biased numerical optimization method • General-purpose trained model for application to small lot multi-product • It is also possible to any deep learning engine （It may be necessary to develop another API.） ※TensorFlowTM is developed by Google LLC, is an open-source software library for dataflow and differentiable programming across a range of tasks.
inspection images and narrowing down to necessary functions, you can concentrate on image classification work and efficiently perform annotation work. • The progress of work can be checked in real time by the administrator.
operations of data sets do not excessively consume storage capacity Reference as virtual data Linked Real Object RDB ＋ Strorage Collect / Annotation Preprocess / Augmentation Training Inference / Analyze Light operating experience even if massive images
POODL SDK • API documentation We are also developing applications using POODL, implementing SDK into inspection machine, and providing support for linkage with other systems. Cloud Computing Service AWS (EC2, Batch, ECS, S3, RDS) Container / Virtualization Docker Web Application (Back-end) PHP(Laravel Framework) GUI (Front-end) Vue.js (element-ui) Database MySQL Machine Learning / Data Analyze AWS Batch, AWS ECS, Python (Tensorflow, Keras, numpy, pandas) Application Environment C#.NET (Windows Forms, WPF), Python, Node.js Image Processing OpenCV, HALCON Technology Base