Dijkstra Image Graph Pathfinding

This project implements an image-based graph detection system using Dijkstra's algorithm to find the shortest path between two nodes in a weighted, undirected graph drawn on an image.

The system:

• Detects nodes (black circles with labels) and edge weights (red numbers),
• Extracts valid connections using image processing and OCR,
• Applies Dijkstra’s algorithm to compute the shortest path,
• Draws the resulting path directly onto the original image.

All logic, explanation, and usage instructions are contained in the notebook file (dijkstra_image_pathfinding.ipynb).

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Libraries Used

• OpenCV (cv2) – image processing, shape detection, drawing
• pytesseract – OCR to detect node labels and edge weights
• NumPy – numerical operations, distance calculations
• math – geometric computations
• Google Colab patch (cv2_imshow) – used to display images in Google Colab

Note: If you're using Jupyter Notebook locally, replace cv2_imshow() with matplotlib.pyplot.imshow() or cv2.imshow() as needed, since cv2_imshow() is specific to Google Colab.

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How to Use

1. Upload or create an image with a graph following the drawing rules described in the notebook.
2. Open the notebook in Google Colab (recommended) or Jupyter Notebook.
3. Run all cells — the script will:
   • Detect graph structure,
   • Apply Dijkstra’s algorithm,
   • Output the original image with the shortest path highlighted.

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📝 License

This project is open-source and licensed under the MIT License.