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README.md

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+---
+license: apache-2.0
+---
+---
+
+# 📄 Invoice Image Dataset (N8N-Friendly Streaming Format)
+
+This repository contains a large-scale collection of invoice images stored in a **simple, sequential, machine-friendly structure** designed specifically for workflow automation tools such as **n8n**, Airflow, Make.com, and other ETL/automation systems.
+
+The dataset is formatted to allow **easy, reliable, and high-performance pulling of individual invoice files one-by-one**, without needing to download the entire dataset.
+
+---
+
+## 📁 Directory Structure
+
+All invoice images are stored inside a single directory:
+
+```
+images/
+│
+├── invoice_00000001.png
+├── invoice_00000002.png
+├── invoice_00000003.png
+├── invoice_00000004.png
+└── ...
+```
+
+### ✅ Naming Format
+
+Each invoice follows a **fixed-length 8-digit numbering scheme**:
+
+```
+invoice_00000000.format
+```
+
+* Zero-padded (`06d` or more) numbering supports **millions of invoices** without renaming.
+* `format` can be `.png`, `.jpg`, `.jpeg`, `.webp`, depending on original source.
+* Each file is **independent** and can be downloaded individually.
+
+---
+
+## 🎯 Purpose of This Dataset
+
+This dataset acts as a **normalized, unified output repository** for invoice images collected and standardized from multiple sources:
+
+* Other Hugging Face datasets
+* GitHub repositories
+* Parquet datasets containing embedded images
+* Third-party OCR datasets
+* Custom pipelines
+
+Each invoice is extracted, normalized, renamed, and uploaded in a consistent structure.
+
+---
+
+## 🔌 Why This Format Is Perfect for n8n Workflows
+
+Most automation tools (including **n8n**) struggle with:
+
+* datasets stored in large compressed files (ZIPs, JSONL, Parquet)
+* datasets where images must be decoded from arrays/blobs
+* datasets requiring full-dataset downloads
+
+This repo is intentionally built to support **file-by-file streaming**, so n8n can:
+
+### ✔ Pull one file at a time
+
+Example URL:
+
+```
+https://huggingface.co/datasets/<USER>/<REPO>/resolve/main/images/invoice_00000042.png
+```
+
+### ✔ Process invoices sequentially
+
+You can loop:
+
+1 → 2 → 3 → 4 → ...
+
+As long as the file exists, n8n continues; when it fails (404), it stops — perfect for paginated workflows.
+
+### ✔ Avoid handling large downloads
+
+Each invoice is an independent file.
+
+### ✔ Use lightweight logic
+
+You only need a simple incrementing counter in n8n.
+
+---
+
+## 🧩 Example n8n Workflow Logic
+
+1. Start with variable:
+
+   ```
+   index = 1
+   ```
+
+2. Construct file URL:
+
+   ```
+   url = https://huggingface.co/datasets/<USER>/<REPO>/resolve/main/images/invoice_<index padded>.png
+   ```
+
+3. HTTP GET → process invoice
+
+4. Increment index
+
+5. Repeat until HTTP GET returns 404
+
+6. Stop workflow automatically
+
+This allows n8n to **stream** invoices from Hugging Face like a controlled queue.
+
+---
+
+## 📦 What This Dataset Contains
+
+* Only raw invoice images
+* No labels
+* No associated OCR text
+* No metadata
+
+This repository is intended specifically as an **output target** for standardized invoices — not as an annotated machine learning dataset.
+
+---
+
+## ⚙️ How It Was Generated
+
+A controlled pipeline:
+
+1. Loads invoices from multiple formats (HF dataset, Parquet, GitHub, OCR outputs, etc.)
+2. Extracts image data
+3. Converts and normalizes to `.png` or `.jpg`
+4. Saves to `images/invoice_XXXXXXXX.format`
+5. Uploads each file individually using the Hugging Face API
+6. Logs progress so the job can resume at any index
+
+Designed with:
+
+* Kaggle execution compatibility
+* Resume-safe operation
+* Support for millions of invoices
+* No Git requirements (uploads via HF API)
+
+---
+
+## 📬 Contact / Usage Notes
+
+This dataset is meant for:
+
+* ETL automation
+* Synthetic invoice processing pipelines
+* AI model pre-processing
+* OCR experiments
+* Workflow system testing (n8n, make.com)
+
+If you use this dataset in your workflow, feel free to reference or credit the repo.
+
+---