TagVideo vs DocWeave

TabVideo - 视频创作的终极助手 TabVideo是专为视频创作者和爱好者设计的完美应用。凭借强大的功能和直观的界面，它为您提供了无缝的体验，可以录制视频、从相册选择媒体，并将文件组织在自定义文件夹中。但这还不是全部 - TabVideo更进一步，通过自动将文件同步到iCloud文档，确保您轻松查找和在电脑上进行编辑。 主要功能： 1. 录制视频：在应用内捕捉高质量的视频。无论是拍摄视频博客、教程还是其他内容，TabVideo提供了方便且用户友好的录制体验。 2. 从相册导入：从设备的相册中选择视频或照片，并轻松地将它们引入TabVideo。访问您现有的媒体文件，并将它们无缝地整合到您的项目中。 3. 可定制的文件夹组织：保持组织和对视频素材的控制。TabVideo允许您创建个性化的文件夹，根据您的偏好对媒体文件进行分类和管理。 4. 无缝iCloud同步：告别手动传输文件的麻烦。TabVideo会自动将您的文件夹和文件同步到iCloud文档，确保您的媒体安全存储，并在所有设备上随时可用。这个功能简化了您的工作流程，使您可以轻松在电脑上访问和编辑素材。 5. 高效的搜索和检索：快速高效地找到合适的片段和照片。TabVideo强大的搜索功能使您可以在文件夹中快速定位特定的媒体文件，为您节省宝贵的时间和精力。 6. 智能分类：TabVideo会自动按类别组织您的媒体文件，进一步简化视频创作过程。享受整齐排列的库的好处，更容易找到和使用所需的素材。 TabVideo是注重效率、组织和流畅工作流程的视频创作者的终极伴侣。它让您专注于创作过程，无需担心文件管理或同步问题。立即下载TabVideo，体验视频创作便捷的新水平。 注意：TabVideo尊重您的隐私，不收集任何个人信息。您的媒体文件安全存储在设备上，并同步到iCloud文档，以方便您使用。

Turn PDFs, images, and paper documents into structured content you can actually edit and reuse. DocWeave runs an AI document recognition model locally on your device. Import PDFs or images, scan paper documents, book pages, and lecture notes with your iPhone or iPad, or capture scrolling webpages and long articles through screen recording. Once the local model is installed, recognition works without an internet connection, and your documents never need to be uploaded to a server. What It Can Do • Scan Paper Documents Automatically detect and continuously capture pages on iPhone and iPad, then add them to the processing queue. Ideal for book pages, lecture notes, receipts, and temporary documents. • Capture Scrolling Content Record scrolling webpages or long articles and automatically stitch them into a long screenshot. Before recognition, you can remove ads, duplicate sections, and irrelevant content. • Understand Complex Layouts Go beyond plain text. DocWeave can recognize paragraph structures, tables, LaTeX formulas, code blocks, and algorithm blocks. • Export in Four Formats Generate reconstructed PDF, Markdown, EPUB, and MinerU packages in one pass—ready for reading, editing, archiving, or further processing. • Preview as Recognition Progresses View structured results as soon as each page is completed, so you can follow the progress and check the reconstructed layout. • Resume After Interruptions If a model download, page capture session, or large document recognition task is interrupted, continue from the saved progress instead of starting over. • Keep Documents on Your Device Model inference, page images, and recognition results are stored locally. Unless you choose to export, share, or send them to another app, your recognized content stays on your device. From capturing paper and importing files to understanding complex layouts and exporting reusable content, DocWeave keeps the entire document workflow on your device. First Use An internet connection is required to download the local recognition model, which is approximately 2.5 GB. The download begins only after you confirm it and can resume if interrupted. Once installed, the model can perform recognition offline. Device Requirements On-device AI recognition requires an A14 / M1 chip or newer and at least 6 GB of RAM. Requirements differ by recognition engine: • OvisOCR2 (faster, lower memory usage): a device with at least 6 GB RAM; keep at least 3 GB of free RAM before loading the model; model files are about 0.6–1 GB (varies by device). • MinerU (full-featured, supports reconstructed PDF export): a device with at least 8 GB RAM; keep at least 5 GB of free RAM before loading the model; the model file is about 2.5 GB. Note: free RAM is not storage; you also need enough storage for the model files and recognition results. Recommended devices: • iPhone 12 Pro / 13 Pro, iPhone 14 or newer (MinerU requires iPhone 15 Pro or newer) • iPad mini (A17 Pro) • iPad Air (M1) or newer • iPad Pro (M1) or newer • Mac with Apple silicon and at least 8 GB of unified memory Devices before A14 are not supported, e.g. iPad Pro (2018/2020, A12X/A12Z chip). Camera scanning and rolling-screen recording capture are only available on iOS/iPadOS. The macOS version supports importing PDFs and images via file picker, drag and drop, or paste.