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Deep Learning-Based Diagram Recognizer

Objective:

To automatically recognize, classify, and extract information from diagrams, flowcharts, and technical drawings using deep learning, enabling intelligent analysis and digitization of visual information.

Why Choose This Project:

  • Diagram interpretation is essential in education, research, and engineering documentation.

  • Reduces manual effort in understanding and annotating diagrams.

  • Integrates computer vision, deep learning, and pattern recognition — highly practical for AI-based applications.

  • Can be extended to convert diagrams into editable digital formats.

Key Features:

Feature Description
Diagram Classification Automatically classify types of diagrams (flowchart, UML, circuit, organizational).
Shape & Symbol Recognition Detect shapes, arrows, connectors, and symbols in diagrams.
Text Extraction (OCR) Extract textual information embedded in diagrams.
Editable Output Convert recognized diagrams into editable digital formats (e.g., SVG, JSON).
Interactive Dashboard View recognized diagrams and their extracted information.
Multi-format Support Supports images (PNG, JPG) and PDFs.

Technology Stack:

  • Frontend: HTML, CSS, JavaScript, Bootstrap / React.js.

  • Backend: Python with Flask or Django.

  • Deep Learning / CV:

    • Model Frameworks: TensorFlow, Keras, or PyTorch.

    • Object Detection & Classification: YOLO, Faster R-CNN, or Mask R-CNN.

    • OCR: Tesseract OCR, EasyOCR.

  • Database: MySQL / PostgreSQL / MongoDB for storing diagrams and extracted data.

  • Optional: OpenCV for image preprocessing and noise reduction.

Working Flow:

  1. Diagram Upload

    • Users upload diagram images or PDFs to the system.

  2. Preprocessing

    • Image enhancement, resizing, noise removal, binarization, and edge detection.

  3. Deep Learning-Based Detection

    • Detect shapes, arrows, and connectors using object detection models.

  4. Text Extraction

    • Apply OCR to extract textual labels from diagrams.

  5. Diagram Classification

    • Classify the diagram type (flowchart, circuit, UML, etc.) using a CNN-based classifier.

  6. Output Generation

    • Generate structured output (JSON, SVG) representing diagram components and relationships.

  7. Visualization & Dashboard

    • Display original diagram alongside recognized components and extracted text.

Main Modules:

  1. Upload & Preprocessing Module

  2. Shape & Symbol Detection Module

  3. Text Extraction (OCR) Module

  4. Diagram Classification Module

  5. Output Generation & Visualization Module

Security Features:

  • Secure upload to prevent malicious files.

  • Role-based access to view sensitive diagrams.

  • Data encryption for stored diagrams and extracted information.

This Course Fee:

₹ 2499 /-

Project includes:
  • Customization Icon Customization Fully
  • Security Icon Security High
  • Speed Icon Performance Fast
  • Updates Icon Future Updates Free
  • Users Icon Total Buyers 500+
  • Support Icon Support Lifetime
Secure Payment:
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