Compare PDFspy vs. RectLabel

PDFspy serves as the premier utility for obtaining detailed information about your PDF files. It has the capability to extract a thorough array of attributes from a PDF document and convert them into an XML-based format. It supports PDF 1.7/ISO 32000 standards, including versions from Acrobat 9 through DC. The latest update introduces the Element feature, which displays CMYK separations utilized by both text and vector elements. Additionally, a new feature has been added to indicate the total number of shading objects present in a PDF file. If the -o option is not employed, a restored output will be sent to stdout, and it is advisable to use the -quiet option for writing to stdout. The calculation of page labels has been corrected, and there is now an enhanced algorithm for extracting text. Furthermore, it computes color simulation values for ICCBased, separation, and DeviceN color spaces, while also improving support for Unicode, ISO Latin, and the AdobePDF character sets. The utility now offers insights into font usage, including details on name, type, embedding and subset status, as well as Unicode utilization. It features an asset management system that allows users to extract page counts, metadata, and font and image details. Moreover, PDFspy includes document management capabilities to identify text or image-only documents and to extract comments, making it an invaluable tool for anyone working with PDF files. This comprehensive functionality makes PDFspy essential for effective PDF document analysis and management.

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