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Add element detection for identifying interactive UI elements in terminal screens. The system uses visual style segmentation and pattern classification to identify buttons, inputs, and toggles. Key components (crates/pilotty-core/src/elements/): - grid: maps vt100 screen to typed cells with style info - segment: clusters adjacent cells by visual style - classify: pattern-matches clusters to element types - Element: output type with kind, position, text, confidence Detection patterns: - Buttons: [OK], <Cancel>, inverse-video text, underlined text - Inputs: underscore runs (____), cursor-containing regions - Toggles: [x], [ ], (o), ( ) checkbox/radio patterns Classification priority ensures pattern recognition takes precedence over cursor position (cursor on button = focused button, not input). Elements include row/col for direct use with click command. Confidence scores indicate detection certainty (1.0 = high, 0.6 = low). Known limitation: ncurses apps that style brackets differently from interior text (e.g., dialog) may not detect buttons correctly.
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Add element detection for identifying interactive UI elements in terminal screens. The system uses visual style segmentation and pattern classification to identify buttons, inputs, and toggles.
Key components (crates/pilotty-core/src/elements/):
Detection patterns:
Classification priority ensures pattern recognition takes precedence over cursor position (cursor on button = focused button, not input).
Elements include confidence scores and optional focused/checked state.
Known limitation: ncurses apps that style brackets differently from interior text (e.g., dialog) may not detect buttons correctly.