A Python application for scanning and identifying Radar Signatures in Star Citizen. This project reads data from an on-screen capture and identifies related details from a packaged database.
- Screen Capture & OCR: Captures a region of your screen and processes it using OCR.
- Database Integration: Identifies and maps the captured data to stored values in a packaged SQLite database.
- History Tracking: Maintains a searchable history of previous scans.
- Customizable Scan Areas: Allows users to set and adjust scan areas dynamically.
- User-Friendly Interface: Built using PyQt for an intuitive GUI experience.
This project requires the following dependencies:
- Python 3.10+
- PyQt6
- pytesseract
- Pillow
- pyautogui
- SQLite (packaged database)
- Tesseract-OCR 64bit (Included)
- Click on "Search" to start a search based on the value in the search box.
- The system processes the input and identifies corresponding values in the database.
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If you want to do Scans, not just Manual Searches, you must install and setup Tesseract-OCR 64bit which is included in the downloads
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You can include more languages in the installation which will increase its footprint, this improves the Scan accuracy.
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Make sure to install in the default directly to ensure it works correctly.
C:\Program Files\Tesseract-OCR
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Click on the Scan Area Preview Icon in the upper right corner of the "Scan Area of Screen" section.
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Click on the center of the rectangle and drag it around to move it.
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Click on any edge to resize it like a window.
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Move the Scan Area preview over the screen where the Radar Signature pops up.
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This section moves depending on the ship so you want to make sure if the scans aren't working, that it's in the right location.
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Click on the Faded Scan Area Preview Icon in the upper right corner of the "Scan Area of Screen" section to hide the Scan Area preview.
- Click on "Start Scan" to capture data from the predefined screen area.
- The system processes the input and identifies corresponding values in the database.
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Identified elements are displayed in the Results section.
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Previous searches are saved for future reference.
This project is licensed under the MIT License. See the LICENSE file for details.
Developer: Jonathan Alvarado
Special Thanks: Josh Norton for feedback during the creation