tanyar09
d6b1e85998
This commit introduces a new confidence calibration system that converts DeepFace distance values into actual match probabilities, addressing previous misleading confidence percentages. Key changes include the addition of calibration methods in `FaceProcessor`, updates to the `IdentifyPanel` and `AutoMatchPanel` to utilize calibrated confidence, and new configuration settings in `config.py`. The README has been updated to document these enhancements, ensuring users see more realistic match probabilities throughout the application.
72 lines
2.4 KiB
Python
Executable File
72 lines
2.4 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Launcher script for PunimTag Dashboard
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Adds project root to Python path and launches the dashboard
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"""
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import os
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import sys
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import warnings
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from pathlib import Path
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# Suppress TensorFlow warnings (must be before DeepFace import)
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
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warnings.filterwarnings('ignore')
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# Add project root to Python path
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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# Now import required modules
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from src.gui.dashboard_gui import DashboardGUI
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from src.gui.gui_core import GUICore
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from src.core.database import DatabaseManager
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from src.core.face_processing import FaceProcessor
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from src.core.photo_management import PhotoManager
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from src.core.tag_management import TagManager
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from src.core.search_stats import SearchStats
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from src.core.config import DEFAULT_DB_PATH
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if __name__ == "__main__":
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# Initialize all required components
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gui_core = GUICore()
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db_manager = DatabaseManager(DEFAULT_DB_PATH, verbose=0)
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# Initialize face_processor without detector/model (will be updated by GUI)
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face_processor = FaceProcessor(db_manager, verbose=0)
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photo_manager = PhotoManager(db_manager, verbose=0)
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tag_manager = TagManager(db_manager, verbose=0)
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search_stats = SearchStats(db_manager)
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# Define callback functions for scan and process operations
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def on_scan(folder, recursive):
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"""Callback for scanning photos"""
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return photo_manager.scan_folder(folder, recursive)
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def on_process(limit=None, stop_event=None, progress_callback=None,
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detector_backend=None, model_name=None):
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"""Callback for processing faces with DeepFace settings"""
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# Update face_processor settings if provided
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if detector_backend:
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face_processor.detector_backend = detector_backend
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if model_name:
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face_processor.model_name = model_name
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return face_processor.process_faces(
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limit=limit, # Pass None if no limit is specified
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stop_event=stop_event,
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progress_callback=progress_callback
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)
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# Create and run dashboard
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app = DashboardGUI(
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gui_core=gui_core,
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db_manager=db_manager,
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face_processor=face_processor,
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on_scan=on_scan,
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on_process=on_process,
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search_stats=search_stats,
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tag_manager=tag_manager
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)
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app.open()
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