Update README.md

README.md

@@ -1,3 +1,15 @@
+---
+title: DocIQ - Intelligent Document Processing
+emoji: 🧠
+colorFrom: blue
+colorTo: purple
+sdk: streamlit
+sdk_version: "1.40.0"
+python_version: "3.10"
+app_file: app.py
+pinned: false
+---
+
 # 🧠 DocIQ — Intelligent Document Processing
 
 [![Python](https://img.shields.io/badge/Python-3.10%2B-blue.svg)](https://www.python.org/)
@@ -6,103 +18,229 @@
 [![License](https://img.shields.io/badge/License-MIT-purple.svg)](LICENSE)
 [![HF Space](https://img.shields.io/badge/🤗%20Live%20Demo-HuggingFace-orange.svg)](https://huggingface.co/spaces/Goutam112/Text_Extracted)
 
-**DocIQ** is an Intelligent Document Processing (IDP) platform. Upload any document image, use a preset sample, or capture with your webcam — DocIQ extracts text, measures accuracy, detects entities, and exports results in multiple formats.
+**DocIQ** is an Intelligent Document Processing (IDP) platform that transforms document images into structured, searchable, and exportable information.
+
+Upload a document image, select a built-in sample, or capture an image using your webcam. DocIQ performs OCR, evaluates recognition confidence, visualizes detected text, extracts entities, detects sensitive information, and exports the results in multiple formats.
 
 ---
 
 ## ✨ Features
 
-| Feature | Description |
-|---------|-------------|
-| 🎯 **OCR Accuracy Score** | Confidence-weighted accuracy grade (A+ to D) for every scan |
-| 🖼️ **Visual Canvas** | Bounding boxes, confidence heatmap, and reading order overlay on the **original image** |
-| 🔎 **Keyword Search** | Highlight any word instantly on the document canvas |
-| 🗂️ **Entity Extraction** | Auto-detect dates, amounts, invoice numbers, emails, phones |
-| 🛡️ **PII Redaction** | Mask Aadhaar, PAN, credit cards with one toggle |
-| 🧬 **Semantic Embeddings** | 2D word cluster map using sentence-transformers + PCA/t-SNE |
-| 📤 **Multi-Format Export** | Searchable PDF, annotated PDF, JSON, CSV, plain text, ZIP bundle |
-| 📸 **Camera Scanner** | On-demand webcam capture — camera only turns on when you click Enable |
+| Feature                    | Description                                                                         |
+| -------------------------- | ----------------------------------------------------------------------------------- |
+| 🎯 **OCR Accuracy Score**  | Confidence-weighted accuracy grade from A+ to D                                     |
+| 🖼️ **Visual Canvas**      | Bounding boxes, confidence heatmap, and reading-order overlay on the original image |
+| 🔎 **Keyword Search**      | Instantly search and highlight words on the document canvas                         |
+| 🗂️ **Entity Extraction**  | Automatically detect dates, amounts, invoice numbers, emails, and phone numbers     |
+| 🛡️ **PII Redaction**      | Detect and mask sensitive information such as Aadhaar, PAN, and credit-card numbers |
+| 🧬 **Semantic Embeddings** | Generate 2D word-cluster visualizations using sentence-transformers with PCA/t-SNE  |
+| 📤 **Multi-Format Export** | Export searchable PDFs, annotated PDFs, JSON, CSV, plain text, and ZIP bundles      |
+| 📸 **Camera Scanner**      | Capture documents directly through the webcam when the scanner is enabled           |
 
 ---
 
 ## 🚀 Quick Start
 
 ### Run Locally
+
 ```bash
 git clone https://github.com/Goutam16-Withcode/DocIQ---Intelligent-Document-Processing.git
 cd DocIQ---Intelligent-Document-Processing
 pip install -r requirements.txt
 python -m streamlit run app.py
 ```
-Open **http://localhost:8501** in your browser.
 
-### Live Demo
-👉 [huggingface.co/spaces/Goutam112/Text_Extracted](https://huggingface.co/spaces/Goutam112/Text_Extracted)
+Open:
+
+```text
+http://localhost:8501
+```
+
+### 🤗 Live Demo
+
+[DocIQ — Hugging Face Space](https://huggingface.co/spaces/Goutam112/Text_Extracted?utm_source=chatgpt.com)
 
 ---
 
 ## 🔄 How It Works
 
-```
+```text
 Upload / Camera Capture
         ↓
-Show original image (natural colors)
+Display Original Image
         ↓
-Preprocessing (internal — for OCR accuracy only)
-  • EXIF orientation fix
-  • Auto deskew
-  • CLAHE contrast enhancement
-  • Shadow removal (camera mode)
-  • Unsharp mask sharpening
+Image Preprocessing
+        ├── EXIF orientation correction
+        ├── Automatic deskew
+        ├── CLAHE contrast enhancement
+        ├── Shadow removal
+        └── Unsharp-mask sharpening
         ↓
-EasyOCR Neural Inference (GPU accelerated)
-  • Primary pass + fallback high-sensitivity pass
+EasyOCR Neural Inference
+        ├── Primary OCR pass
+        └── High-sensitivity fallback pass
         ↓
-Structured Output
-  • Bounding boxes on original image
-  • Accuracy grade + confidence breakdown
-  • Entity extraction & PII redaction
-  • Export (PDF / JSON / CSV / ZIP)
+Structured Document Output
+        ├── Bounding boxes
+        ├── Confidence analysis
+        ├── OCR quality grade
+        ├── Entity extraction
+        ├── PII detection/redaction
+        └── Multi-format export
 ```
 
 ---
 
 ## 📊 OCR Quality Grades
 
-| Grade | Accuracy | Meaning |
-|:-----:|:--------:|---------|
-| **A+** | 90–100% | Exceptional — production ready |
-| **A** | 80–89% | High accuracy — standard documents |
-| **B** | 68–79% | Good — minor noise or tilt |
-| **C** | 50–67% | Moderate — review recommended |
-| **D** | < 50% | Low — retake with better lighting |
+|  Grade | Accuracy | Meaning                                         |
+| :----: | :------: | ----------------------------------------------- |
+| **A+** |  90–100% | Exceptional recognition confidence              |
+|  **A** |  80–89%  | High recognition confidence                     |
+|  **B** |  68–79%  | Good recognition with possible minor errors     |
+|  **C** |  50–67%  | Moderate recognition; manual review recommended |
+|  **D** |   < 50%  | Low recognition; better image quality may help  |
+
+> **Note:** The grade is an application-level confidence metric and should not be interpreted as a formal benchmark of OCR accuracy against ground-truth annotations.
+
+---
+
+## 🧠 Processing Pipeline
+
+DocIQ separates the image shown to the user from the image transformations used internally for OCR.
+
+### 1. Image Acquisition
+
+Documents can be provided through:
+
+* 📁 File upload
+* 🧪 Built-in sample documents
+* 📸 Webcam capture
+
+### 2. Preprocessing
+
+The OCR pipeline can apply several image-processing operations:
+
+* EXIF orientation correction
+* Deskewing
+* CLAHE contrast enhancement
+* Shadow removal for camera images
+* Sharpening
+
+These transformations are performed internally to improve OCR recognition while preserving the original document for visualization.
+
+### 3. OCR
+
+DocIQ uses **EasyOCR with PyTorch** to detect and recognize text.
+
+The OCR output contains:
+
+* Detected text
+* Bounding boxes
+* Confidence scores
+* Reading order information
+
+### 4. Information Extraction
+
+The recognized text is further processed to identify structured information such as:
+
+* Dates
+* Currency amounts
+* Invoice numbers
+* Email addresses
+* Phone numbers
+
+### 5. PII Detection
+
+Potentially sensitive identifiers can be detected and optionally redacted, including:
+
+* Aadhaar numbers
+* PAN numbers
+* Credit-card numbers
+
+### 6. Semantic Analysis
+
+Recognized words can be converted into semantic embeddings and projected into a 2D visualization using dimensionality-reduction techniques such as PCA or t-SNE.
+
+---
+
+## 📤 Export Formats
+
+DocIQ supports multiple output formats:
+
+| Format             | Use Case                                     |
+| ------------------ | -------------------------------------------- |
+| **Searchable PDF** | Searchable version of the extracted document |
+| **Annotated PDF**  | Document with OCR annotations                |
+| **JSON**           | Structured OCR and entity data               |
+| **CSV**            | Tabular extraction results                   |
+| **TXT**            | Plain-text OCR output                        |
+| **ZIP**            | Bundle of multiple generated outputs         |
 
 ---
 
 ## 📁 Project Structure
 
-```
+```text
 DocIQ/
-├── app.py              # Main Streamlit UI
+├── app.py              # Main Streamlit application
 ├── requirements.txt    # Python dependencies
 └── src/
     ├── preprocessor.py # Image enhancement pipeline
-    ├── ocr_engine.py   # EasyOCR engine + accuracy metrics
+    ├── ocr_engine.py   # EasyOCR engine and OCR metrics
     ├── visualizer.py   # Bounding boxes, heatmap, reading order
-    ├── extractor.py    # Entity & invoice field extraction
-    ├── embedder.py     # Semantic embeddings & clustering
+    ├── extractor.py    # Entity and invoice field extraction
+    ├── embedder.py     # Semantic embeddings and clustering
     ├── exporter.py     # PDF, JSON, CSV, ZIP export
     └── sample_docs.py  # Built-in sample document generator
 ```
 
 ---
 
+## ⚙️ Technology Stack
+
+* **Python 3.10+**
+* **Streamlit**
+* **PyTorch**
+* **EasyOCR**
+* **OpenCV**
+* **NumPy**
+* **Pandas**
+* **Sentence Transformers**
+* **PCA / t-SNE**
+* **ReportLab**
+* **JSON / CSV processing**
+
+---
+
 ## 🛡️ Privacy
 
-All OCR processing, image filtering, and vector embeddings run **entirely locally**. No images or text are sent to any external server.
+DocIQ is designed with local processing in mind.
+
+OCR processing, image preprocessing, and embedding generation are performed within the application environment. The application does not intentionally send uploaded document images or extracted text to external APIs as part of the core processing pipeline.
+
+When deploying the application to a hosted environment such as Hugging Face Spaces, uploaded data is processed within that hosted runtime. Users should therefore avoid uploading sensitive documents unless they understand the hosting environment and its data-retention policies.
+
+---
+
+## 🤗 Hugging Face Space
+
+**Live Demo:**
+
+[Open DocIQ on Hugging Face](https://huggingface.co/spaces/Goutam112/Text_Extracted?utm_source=chatgpt.com)
 
 ---
 
 ## 📄 License
 
 MIT License — open source and free to use.
+
+---
+
+## 🔗 Project Repository
+
+[DocIQ GitHub Repository](https://github.com/Goutam16-Withcode/DocIQ---Intelligent-Document-Processing?utm_source=chatgpt.com)
+
+---
+
+Check out the configuration reference at [Hugging Face Spaces Configuration Reference](https://huggingface.co/docs/hub/spaces-config-reference?utm_source=chatgpt.com)