8,000+episodes . Document OCR . Seal Scan Classification Archive . Office Automation Digital Staff
| Dataset Name | Office Document Processing Dataset |
| Total Data Volume | 8,000+ episodes |
| Data Type | Video, OCR, stamp/signature testing, approval status, process steps |
| Video Specifications | 1920×1080 @ 30 FPS |
| Delivery Format | LeRobot 3.0 / RLDS / HDF5 / JSON Metadata |
| License Type | Licensed Data or Custom Projects |
Each piece of data contains complete structured fields, covering all requirements from basic metadata to professional analysis.
| Field Category | Typical Fields |
|---|---|
| Office Operations Video | Videos, desktop perspectives, document type, operator role, office scenes, light conditions |
| Document OCR Content | Text content, stamp location, signature detection, table structure, instrument fields, layout type, key information extraction |
| Process Step Description | Time stamp and result of steps such as printing, stamping, scanning, classification, filing, approval of flow, abnormal break mark |
| Approval and status | Approval nodes, pass/rejection of markings, unusual reasons, processing time, system intercepts, flow records |
| Metadata and Compliance | Sector code, document number, scope of authorization, data synthesis/de-identification marker, compliance level |
The following is a de-identified structured JSON sample illustrating the typical data format.
Other Organiser
"OFF-2026-0018922",
"office": "finance dept",
"doc type": "inview",
"video": "rgb 0018922.mp4", "deepth 0018922.mkv", "fps":
"ocr":
"text": "Example Technology Ltd. Amount: ¥12.500.00",
"stamp boxes": [120, 80, 220, 140], "signature": true, "table cells": [...]
{\cHFFFFFF}{\cH00FFFF}
"steps": Chuckles
"time": 3.2, "action": "print", "status": "done",
"time": 8.5, "action": "stamp", "status": "done",
"time": 15.1, "action": "scan", "status": "done",
"time": 22.4, "action": "archive", "status": "done"
I don't know.
"approval": "node": "manager", "result": "approved", "comment": "approved"
♪ I'm sorry ♪Trains RPA+ visual models to perform duplicate office tasks such as printing, stamping, scanning, archiving, etc.
OCR, with the training model for document interpretation, including on invoice, contract, form, etc., for the analysis of the data on the layout.
Training in visual data for seal authenticity, signature existential testing and compliance review models.
Model for recommendations for detection and optimization of anomalies in the process of training in step and status data.
The automated classification and retrieval system for archive actions and location data training entity files.
Video, OCR, AI assistant who can understand the office scenes in the status data training.
Changsha Langhui Information Technology Co., Ltd. The DataAssetsAPI platform is dedicated to providing high-quality, compliant data assets for AI companies and research institutions. It supports flexible combination by dimension and by quantity scale.
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