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Description
The initial step in your process should always be modeling your data, as applications may come and go, but data remains constant. After successfully implementing your model, your CubicWeb application will operate, allowing you to gradually introduce valuable features for your users. RQL, which is based on your application model, is a concise language that emphasizes the attributes and connections inherent in the data. While it shares similarities with SPARQL, RQL is generally more user-friendly. Once a RQL query retrieves a data graph, various views can be applied to present the information in the most pertinent format. This design principle is fundamental to the entire CubicWeb architecture. Permissions are intricately defined within the data model, allowing for exceptional precision. Furthermore, any RQL query made to the engine automatically undergoes security checks to ensure safe handling. CubicWeb utilizes a conventional SQL database for data storage and management, with PostgreSQL being the favored choice among its users. By leveraging these capabilities, CubicWeb not only enhances functionality but also prioritizes security and data integrity.
Description
An offline tool designed for image annotation facilitates both object detection and segmentation tasks. Users can create shapes like polygons, cubic bezier curves, line segments, and individual points for precise labeling. It allows for the drawing of oriented bounding boxes specifically tailored for aerial imagery. The tool also features the ability to mark key points that can be connected by skeletons, as well as the capacity to color pixels using brushes or superpixels. It supports reading and writing in PASCAL VOC XML and YOLO text formats, ensuring compatibility with various machine learning formats. In addition, users can export their work to CreateML for object detection and image classification, as well as to COCO, Labelme, YOLO, DOTA, and CSV formats. The tool also provides options to export indexed color mask images and grayscale mask images to suit different project needs. Users can easily adjust settings related to objects, attributes, hotkeys, and fast labeling for improved efficiency. The label dialog is customizable, allowing for a seamless combination with attributes, and one-click buttons expedite the process of selecting object names. With an impressive auto-suggest feature that considers over 5000 object names, searching for objects, attributes, and image names can be done in a gallery view for convenience. Automatic labeling capabilities are powered by Core ML models, and the tool includes automatic text recognition through OCR technology. Additionally, it has functionalities to convert videos into image frames and perform image augmentation. Language support extends to English, Chinese, Korean, and 11 other languages, making it accessible to a diverse user base while enhancing productivity across different regions. This comprehensive feature set emp
API Access
Has API
No
API Access
Has API
No
Integrations
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
CubicWeb
Website
www.cubicweb.org
Vendor Details
Company Name
RectLabel
Country
United States
Website
rectlabel.com
