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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:
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Diagram interpretation is essential in education, research, and engineering documentation.
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Reduces manual effort in understanding and annotating diagrams.
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Integrates computer vision, deep learning, and pattern recognition — highly practical for AI-based applications.
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Can be extended to convert diagrams into editable digital formats.
Key Features:
| Feature | Description |
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| 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:
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Frontend: HTML, CSS, JavaScript, Bootstrap / React.js.
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Backend: Python with Flask or Django.
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Deep Learning / CV:
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Model Frameworks: TensorFlow, Keras, or PyTorch.
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Object Detection & Classification: YOLO, Faster R-CNN, or Mask R-CNN.
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OCR: Tesseract OCR, EasyOCR.
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Database: MySQL / PostgreSQL / MongoDB for storing diagrams and extracted data.
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Optional: OpenCV for image preprocessing and noise reduction.
Working Flow:
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Diagram Upload
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Users upload diagram images or PDFs to the system.
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Preprocessing
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Image enhancement, resizing, noise removal, binarization, and edge detection.
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Deep Learning-Based Detection
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Detect shapes, arrows, and connectors using object detection models.
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Text Extraction
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Apply OCR to extract textual labels from diagrams.
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Diagram Classification
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Classify the diagram type (flowchart, circuit, UML, etc.) using a CNN-based classifier.
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Output Generation
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Generate structured output (JSON, SVG) representing diagram components and relationships.
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Visualization & Dashboard
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Display original diagram alongside recognized components and extracted text.
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Main Modules:
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Upload & Preprocessing Module
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Shape & Symbol Detection Module
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Text Extraction (OCR) Module
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Diagram Classification Module
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Output Generation & Visualization Module
Security Features:
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Secure upload to prevent malicious files.
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Role-based access to view sensitive diagrams.
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Data encryption for stored diagrams and extracted information.