SoftCo: Enterprise Invoice and P2P Automation Software
For companies that process over 20,000 invoices per year
SoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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Get full visibility and control over your tasks and projects with Wrike.
A cloud-based collaboration, work management, and project management software
Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Image annotation for polygon, rectangle, circle, line and point. Image flag annotation for classification and cleaning. Video annotation. (video annotation). GUI customization (predefined labels / flags, auto-saving, label validation, etc). Exporting VOC-format dataset for semantic/instance segmentation.
This application is a professional tool with a graphical user interface that enables anonymization of faces using the Deface Engine. Cross-Platform Compatible (Linux-Windows)
NOTE: To use on Windows, first install Python. Then, if necessary, install “pip install deface” (only if necessary).
Graphical image annotation tool and label object bounding boxes
LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML files in PASCAL VOC format, the format used by ImageNet. Besides, it also supports YOLO and CreateML formats. Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8. However, Python 3 or above and PyQt5 are strongly recommended. Virtualenv can avoid a lot of the QT / Python version issues. ...